commit 65e99d982967103048deeca8511f754fb5aaef1e
parent 610675b9bf50c3d02af9b98bea89cc116b005740
Author: Steven Atkinson <[email protected]>
Date: Sat, 4 Feb 2023 20:05:58 -0800
Apply LLVM style to codebase (#56)
* Apply LLVM style
* Additions to formatter script, got the template project too
* Revert "Additions to formatter script, got the template project too"
This reverts commit 19f1b604c8fb76eb59d331ca9baeb18278e40d77.
* Revert "Apply LLVM style"
This reverts commit f0a7a25d84b23c26b085bc9607d400848b85fa93.
* Apply LLVM style, add a formatting helper script
Diffstat:
34 files changed, 11362 insertions(+), 2871 deletions(-)
diff --git a/NeuralAmpModeler/Colors.h b/NeuralAmpModeler/Colors.h
@@ -12,61 +12,63 @@
#include "IGraphicsStructs.h"
namespace PluginColors {
- // COLORS!
- const iplug::igraphics::IColor OFF_WHITE(255, 243, 246, 249); // Material UI because Heidi said so
+// COLORS!
+const iplug::igraphics::IColor
+ OFF_WHITE(255, 243, 246, 249); // Material UI because Heidi said so
- // From group photo
- //const iplug::igraphics::IColor NAM_5(255, 206, 194, 224); // Languid Lavendar
- //const iplug::igraphics::IColor NAM_4(255, 30, 30, 39); // Raisin Black
- //const iplug::igraphics::IColor NAM_3(255, 48, 43, 96); // Space Cadet
- //const iplug::igraphics::IColor NAM_2(255, 3, 2, 1); // Black
- //const iplug::igraphics::IColor NAM_1(255, 18, 15, 18); // Smoky Black
+// From group photo
+// const iplug::igraphics::IColor NAM_5(255, 206, 194, 224); // Languid
+// Lavendar const iplug::igraphics::IColor NAM_4(255, 30, 30, 39); // Raisin
+// Black const iplug::igraphics::IColor NAM_3(255, 48, 43, 96); // Space Cadet
+// const iplug::igraphics::IColor NAM_2(255, 3, 2, 1); // Black
+// const iplug::igraphics::IColor NAM_1(255, 18, 15, 18); // Smoky Black
- // Blue palette "Microsoft"
- //const iplug::igraphics::IColor NAM_1(255, 13, 27, 42); // Black Fogra 29
- //const iplug::igraphics::IColor NAM_2(255, 27, 38, 59); // Oxford Blue
- //const iplug::igraphics::IColor NAM_3(255, 65, 90, 119); // Bedazzled Blue
- //const iplug::igraphics::IColor NAM_4(255, 119, 141, 169); // Shadow Blue
- //const iplug::igraphics::IColor NAM_5(224, 225, 221, 224); // Platinum
+// Blue palette "Microsoft"
+// const iplug::igraphics::IColor NAM_1(255, 13, 27, 42); // Black Fogra 29
+// const iplug::igraphics::IColor NAM_2(255, 27, 38, 59); // Oxford Blue
+// const iplug::igraphics::IColor NAM_3(255, 65, 90, 119); // Bedazzled Blue
+// const iplug::igraphics::IColor NAM_4(255, 119, 141, 169); // Shadow Blue
+// const iplug::igraphics::IColor NAM_5(224, 225, 221, 224); // Platinum
- // Dark theme
- //const iplug::igraphics::IColor NAM_1(255, 26, 20, 35); // Xiketic
- //const iplug::igraphics::IColor NAM_2(255, 55, 37, 73); // Dark Purple
- //const iplug::igraphics::IColor NAM_3(255, 119, 76, 96); // Twilight Lavendar
- //const iplug::igraphics::IColor NAM_4(255, 183, 93, 105); // Popstar
- //const iplug::igraphics::IColor NAM_5(224, 234, 205, 194); // Unbleached Silk
+// Dark theme
+// const iplug::igraphics::IColor NAM_1(255, 26, 20, 35); // Xiketic
+// const iplug::igraphics::IColor NAM_2(255, 55, 37, 73); // Dark Purple
+// const iplug::igraphics::IColor NAM_3(255, 119, 76, 96); // Twilight Lavendar
+// const iplug::igraphics::IColor NAM_4(255, 183, 93, 105); // Popstar
+// const iplug::igraphics::IColor NAM_5(224, 234, 205, 194); // Unbleached Silk
- //const iplug::igraphics::IColor MOUSEOVER = NAM_5.WithOpacity(0.3);
+// const iplug::igraphics::IColor MOUSEOVER = NAM_5.WithOpacity(0.3);
- // My 3 colors (purple)
- //const iplug::igraphics::IColor NAM_1(255, 18, 17, 19); // Smoky Black
- //const iplug::igraphics::IColor NAM_2(255, 115, 93, 120); // Old Lavendar
- //const iplug::igraphics::IColor NAM_3(255, 189, 185, 196); // Lavendar Gray
- // Alts
- //const iplug::igraphics::IColor NAM_2(255, 34, 39, 37); // Charleston Green
- //const iplug::igraphics::IColor NAM_2(255, 114, 161, 229); // Little Boy Blue
- //const iplug::igraphics::IColor NAM_3(255, 247, 247, 242); // Baby Powder
- //const iplug::igraphics::IColor NAM_3(255, 230, 220, 249); // Pale Purple Pantone
- //const iplug::igraphics::IColor NAM_3(255, 218, 203, 246); // Lavender Blue
+// My 3 colors (purple)
+// const iplug::igraphics::IColor NAM_1(255, 18, 17, 19); // Smoky Black
+// const iplug::igraphics::IColor NAM_2(255, 115, 93, 120); // Old Lavendar
+// const iplug::igraphics::IColor NAM_3(255, 189, 185, 196); // Lavendar Gray
+// Alts
+// const iplug::igraphics::IColor NAM_2(255, 34, 39, 37); // Charleston Green
+// const iplug::igraphics::IColor NAM_2(255, 114, 161, 229); // Little Boy Blue
+// const iplug::igraphics::IColor NAM_3(255, 247, 247, 242); // Baby Powder
+// const iplug::igraphics::IColor NAM_3(255, 230, 220, 249); // Pale Purple
+// Pantone const iplug::igraphics::IColor NAM_3(255, 218, 203, 246); //
+// Lavender Blue
- //Blue mode
- const iplug::igraphics::IColor NAM_1(255, 29, 26, 31); // Raisin Black
- const iplug::igraphics::IColor NAM_2(255, 80, 133, 232); // Azure
- const iplug::igraphics::IColor NAM_3(255, 162, 178, 191); // Cadet Blue Crayola
- // Alts
- //const iplug::igraphics::IColor NAM_1(255, 18, 17, 19); // Smoky Black
- //const iplug::igraphics::IColor NAM_2(255, 126, 188, 230); // Camel
- //const iplug::igraphics::IColor NAM_2(255, 152, 202, 235); // Pale Cerulean
- //const iplug::igraphics::IColor NAM_2(255, 46, 116, 163); // French Blue
- //const iplug::igraphics::IColor NAM_2(255, 80, 171, 232); // Blue Jeans
- //const iplug::igraphics::IColor NAM_3(255, 189, 185, 196); // Aero
- //const iplug::igraphics::IColor NAM_3(255, 221, 237, 248); // Alice Blue
- //const iplug::igraphics::IColor NAM_3(255, 207, 220, 229); // Beau Blue
- //const iplug::igraphics::IColor NAM_3(255, 187, 199, 208); // Silver Sand
+// Blue mode
+const iplug::igraphics::IColor NAM_1(255, 29, 26, 31); // Raisin Black
+const iplug::igraphics::IColor NAM_2(255, 80, 133, 232); // Azure
+const iplug::igraphics::IColor NAM_3(255, 162, 178, 191); // Cadet Blue Crayola
+// Alts
+// const iplug::igraphics::IColor NAM_1(255, 18, 17, 19); // Smoky Black
+// const iplug::igraphics::IColor NAM_2(255, 126, 188, 230); // Camel
+// const iplug::igraphics::IColor NAM_2(255, 152, 202, 235); // Pale Cerulean
+// const iplug::igraphics::IColor NAM_2(255, 46, 116, 163); // French Blue
+// const iplug::igraphics::IColor NAM_2(255, 80, 171, 232); // Blue Jeans
+// const iplug::igraphics::IColor NAM_3(255, 189, 185, 196); // Aero
+// const iplug::igraphics::IColor NAM_3(255, 221, 237, 248); // Alice Blue
+// const iplug::igraphics::IColor NAM_3(255, 207, 220, 229); // Beau Blue
+// const iplug::igraphics::IColor NAM_3(255, 187, 199, 208); // Silver Sand
- // Misc
- const iplug::igraphics::IColor MOUSEOVER = NAM_3.WithOpacity(0.3);
- const iplug::igraphics::IColor HELP_TEXT = iplug::igraphics::COLOR_WHITE;
-};
+// Misc
+const iplug::igraphics::IColor MOUSEOVER = NAM_3.WithOpacity(0.3);
+const iplug::igraphics::IColor HELP_TEXT = iplug::igraphics::COLOR_WHITE;
+}; // namespace PluginColors
#endif /* Colors_h */
diff --git a/NeuralAmpModeler/NeuralAmpModeler.cpp b/NeuralAmpModeler/NeuralAmpModeler.cpp
@@ -1,27 +1,28 @@
-#include <algorithm> // std::clamp
+#include <algorithm> // std::clamp
+#include <cmath>
#include <filesystem>
#include <iostream>
#include <utility>
-#include <cmath>
+#include "Colors.h"
+#include "IControls.h"
+// clang-format off
+// These includes need to happen in this order or else the latter won't know
+// a bunch of stuff.
#include "NeuralAmpModeler.h"
#include "IPlug_include_in_plug_src.h"
-#include "IControls.h"
-#include "Colors.h"
+// clang-format on
using namespace iplug;
using namespace igraphics;
-class IRolloverSVGButtonControl : public ISVGButtonControl
-{
+class IRolloverSVGButtonControl : public ISVGButtonControl {
public:
- IRolloverSVGButtonControl(const IRECT& bounds, IActionFunction af, const ISVG& svg)
- : ISVGButtonControl(bounds, af, svg, svg)
- {
- }
-
- void Draw(IGraphics& g) override
- {
+ IRolloverSVGButtonControl(const IRECT &bounds, IActionFunction af,
+ const ISVG &svg)
+ : ISVGButtonControl(bounds, af, svg, svg) {}
+
+ void Draw(IGraphics &g) override {
if (mMouseIsOver)
g.FillRect(PluginColors::MOUSEOVER, mRECT);
@@ -29,16 +30,13 @@ public:
}
};
-class IRolloverCircleSVGButtonControl : public ISVGButtonControl
-{
+class IRolloverCircleSVGButtonControl : public ISVGButtonControl {
public:
- IRolloverCircleSVGButtonControl(const IRECT& bounds, IActionFunction af, const ISVG& svg)
- : ISVGButtonControl(bounds, af, svg, svg)
- {
- }
-
- void Draw(IGraphics& g) override
- {
+ IRolloverCircleSVGButtonControl(const IRECT &bounds, IActionFunction af,
+ const ISVG &svg)
+ : ISVGButtonControl(bounds, af, svg, svg) {}
+
+ void Draw(IGraphics &g) override {
if (mMouseIsOver)
g.FillEllipse(PluginColors::MOUSEOVER, mRECT);
@@ -46,83 +44,66 @@ public:
}
};
-class IVUpdateableLabelControl : public IVLabelControl
-{
+class IVUpdateableLabelControl : public IVLabelControl {
public:
- IVUpdateableLabelControl(const IRECT& bounds, const char* str, const IVStyle& style)
- : IVLabelControl(bounds, str, style)
- {
- }
-
- void OnMsgFromDelegate(int msgTag, int dataSize, const void* pData)
- {
- SetStr(reinterpret_cast<const char*>(pData));
+ IVUpdateableLabelControl(const IRECT &bounds, const char *str,
+ const IVStyle &style)
+ : IVLabelControl(bounds, str, style) {}
+
+ void OnMsgFromDelegate(int msgTag, int dataSize, const void *pData) {
+ SetStr(reinterpret_cast<const char *>(pData));
}
};
-
// Styles
const IVColorSpec activeColorSpec{
- DEFAULT_BGCOLOR, // Background
- PluginColors::NAM_1, // Foreground
+ DEFAULT_BGCOLOR, // Background
+ PluginColors::NAM_1, // Foreground
PluginColors::NAM_2.WithOpacity(0.4f), // Pressed
- PluginColors::NAM_3, // Frame
- PluginColors::MOUSEOVER, // Highlight
- DEFAULT_SHCOLOR, // Shadow
- PluginColors::NAM_2, // Extra 1
- COLOR_RED, // Extra 2
- DEFAULT_X3COLOR // Extra 3
+ PluginColors::NAM_3, // Frame
+ PluginColors::MOUSEOVER, // Highlight
+ DEFAULT_SHCOLOR, // Shadow
+ PluginColors::NAM_2, // Extra 1
+ COLOR_RED, // Extra 2
+ DEFAULT_X3COLOR // Extra 3
};
const IVColorSpec inactiveColorSpec{
- DEFAULT_BGCOLOR, // Background
- PluginColors::NAM_1,//.WithOpacity(0.5f), // Foreground
- PluginColors::NAM_1, // Pressed
- PluginColors::NAM_3.WithOpacity(0.5f), // Frame
- PluginColors::NAM_1, // Highlight
- DEFAULT_SHCOLOR.WithOpacity(0.5f), // Shadow
- PluginColors::NAM_2.WithOpacity(0.5f), // Extra 1
- COLOR_RED.WithOpacity(0.5f), // Extra 2
- DEFAULT_X3COLOR.WithOpacity(0.5f) // Extra 3
-};
-const IVStyle style = IVStyle{
- true, // Show label
- true, // Show value
- activeColorSpec,
- {DEFAULT_TEXT_SIZE + 5.f, EVAlign::Middle, PluginColors::NAM_3}, // Knob label text
- {DEFAULT_TEXT_SIZE + 5.f, EVAlign::Bottom, PluginColors::NAM_3}, // Knob value text
- DEFAULT_HIDE_CURSOR,
- DEFAULT_DRAW_FRAME,
- false,
- DEFAULT_EMBOSS,
- 0.2f,
- 2.f,
- DEFAULT_SHADOW_OFFSET,
- DEFAULT_WIDGET_FRAC,
-DEFAULT_WIDGET_ANGLE
+ DEFAULT_BGCOLOR, // Background
+ PluginColors::NAM_1, //.WithOpacity(0.5f), // Foreground
+ PluginColors::NAM_1, // Pressed
+ PluginColors::NAM_3.WithOpacity(0.5f), // Frame
+ PluginColors::NAM_1, // Highlight
+ DEFAULT_SHCOLOR.WithOpacity(0.5f), // Shadow
+ PluginColors::NAM_2.WithOpacity(0.5f), // Extra 1
+ COLOR_RED.WithOpacity(0.5f), // Extra 2
+ DEFAULT_X3COLOR.WithOpacity(0.5f) // Extra 3
};
+const IVStyle style = IVStyle{true, // Show label
+ true, // Show value
+ activeColorSpec,
+ {DEFAULT_TEXT_SIZE + 5.f, EVAlign::Middle,
+ PluginColors::NAM_3}, // Knob label text
+ {DEFAULT_TEXT_SIZE + 5.f, EVAlign::Bottom,
+ PluginColors::NAM_3}, // Knob value text
+ DEFAULT_HIDE_CURSOR,
+ DEFAULT_DRAW_FRAME,
+ false,
+ DEFAULT_EMBOSS,
+ 0.2f,
+ 2.f,
+ DEFAULT_SHADOW_OFFSET,
+ DEFAULT_WIDGET_FRAC,
+ DEFAULT_WIDGET_ANGLE};
const IVStyle styleInactive = style.WithColors(inactiveColorSpec);
-NeuralAmpModeler::NeuralAmpModeler(const InstanceInfo& info)
-: Plugin(info, MakeConfig(kNumParams, kNumPresets)),
- mInputPointers(nullptr),
- mOutputPointers(nullptr),
- mNAM(nullptr),
- mIR(nullptr),
- mStagedNAM(nullptr),
- mStagedIR(nullptr),
- mFlagRemoveNAM(false),
- mFlagRemoveIR(false),
- mDefaultNAMString("Select model..."),
- mDefaultIRString("Select IR..."),
- mToneBass(),
- mToneMid(),
- mToneTreble(),
- mNAMPath(),
- mNAMLegacyPath(),
- mIRPath(),
- mInputSender(),
- mOutputSender()
-{
+NeuralAmpModeler::NeuralAmpModeler(const InstanceInfo &info)
+ : Plugin(info, MakeConfig(kNumParams, kNumPresets)),
+ mInputPointers(nullptr), mOutputPointers(nullptr), mNAM(nullptr),
+ mIR(nullptr), mStagedNAM(nullptr), mStagedIR(nullptr),
+ mFlagRemoveNAM(false), mFlagRemoveIR(false),
+ mDefaultNAMString("Select model..."), mDefaultIRString("Select IR..."),
+ mToneBass(), mToneMid(), mToneTreble(), mNAMPath(), mNAMLegacyPath(),
+ mIRPath(), mInputSender(), mOutputSender() {
GetParam(kInputLevel)->InitGain("Input", 0.0, -20.0, 20.0, 0.1);
GetParam(kToneBass)->InitDouble("Bass", 5.0, 0.0, 10.0, 0.1);
GetParam(kToneMid)->InitDouble("Middle", 5.0, 0.0, 10.0, 0.1);
@@ -130,19 +111,20 @@ NeuralAmpModeler::NeuralAmpModeler(const InstanceInfo& info)
GetParam(kOutputLevel)->InitGain("Output", 0.0, -40.0, 40.0, 0.1);
GetParam(kEQActive)->InitBool("ToneStack", false);
-// try {
-// this->mDSP = get_hard_dsp();
-// }
-// catch (std::exception& e) {
-// std::cerr << "Failed to read hard coded DSP" << std::endl;
-// std::cerr << e.what() << std::endl;
-// }
-
+ // try {
+ // this->mDSP = get_hard_dsp();
+ // }
+ // catch (std::exception& e) {
+ // std::cerr << "Failed to read hard coded DSP" << std::endl;
+ // std::cerr << e.what() << std::endl;
+ // }
+
mMakeGraphicsFunc = [&]() {
- return MakeGraphics(*this, PLUG_WIDTH, PLUG_HEIGHT, PLUG_FPS, GetScaleForScreen(PLUG_WIDTH, PLUG_HEIGHT));
+ return MakeGraphics(*this, PLUG_WIDTH, PLUG_HEIGHT, PLUG_FPS,
+ GetScaleForScreen(PLUG_WIDTH, PLUG_HEIGHT));
};
-
- mLayoutFunc = [&](IGraphics* pGraphics) {
+
+ mLayoutFunc = [&](IGraphics *pGraphics) {
pGraphics->AttachCornerResizer(EUIResizerMode::Scale, false);
pGraphics->AttachPanelBackground(COLOR_BLACK);
pGraphics->EnableMouseOver(true);
@@ -156,69 +138,97 @@ NeuralAmpModeler::NeuralAmpModeler(const InstanceInfo& info)
const auto content = mainArea.GetPadded(-10);
const float titleHeight = 50.0f;
const auto titleLabel = content.GetFromTop(titleHeight);
-
+
// Areas for knobs
const float knobHalfPad = 10.0f;
const float knobPad = 2.0f * knobHalfPad;
const float knobHalfHeight = 70.0f;
const float knobHeight = 2.0f * knobHalfHeight;
- const auto knobs = content.GetFromTop(knobHeight).GetReducedFromLeft(knobPad).GetReducedFromRight(knobPad).GetTranslated(0.0f, titleHeight);
- const IRECT inputKnobArea = knobs.GetGridCell(0, kInputLevel, 1, numKnobs).GetPadded(-10);
- const IRECT bassKnobArea = knobs.GetGridCell(0, kToneBass, 1, numKnobs).GetPadded(-10);
- const IRECT middleKnobArea = knobs.GetGridCell(0, kToneMid, 1, numKnobs).GetPadded(-10);
- const IRECT trebleKnobArea = knobs.GetGridCell(0, kToneTreble, 1, numKnobs).GetPadded(-10);
- const IRECT outputKnobArea = knobs.GetGridCell(0, kOutputLevel, 1, numKnobs).GetPadded(-10);
+ const auto knobs = content.GetFromTop(knobHeight)
+ .GetReducedFromLeft(knobPad)
+ .GetReducedFromRight(knobPad)
+ .GetTranslated(0.0f, titleHeight);
+ const IRECT inputKnobArea =
+ knobs.GetGridCell(0, kInputLevel, 1, numKnobs).GetPadded(-10);
+ const IRECT bassKnobArea =
+ knobs.GetGridCell(0, kToneBass, 1, numKnobs).GetPadded(-10);
+ const IRECT middleKnobArea =
+ knobs.GetGridCell(0, kToneMid, 1, numKnobs).GetPadded(-10);
+ const IRECT trebleKnobArea =
+ knobs.GetGridCell(0, kToneTreble, 1, numKnobs).GetPadded(-10);
+ const IRECT outputKnobArea =
+ knobs.GetGridCell(0, kOutputLevel, 1, numKnobs).GetPadded(-10);
// Area for EQ toggle
const float eqAreaHeight = 40.0f;
const float eqAreaHalfWidth = 60.0f;
- const IRECT eqToggleArea = knobs.GetFromBottom(eqAreaHeight).GetTranslated(0.0f, eqAreaHeight).GetMidHPadded(eqAreaHalfWidth);
-
+ const IRECT eqToggleArea = knobs.GetFromBottom(eqAreaHeight)
+ .GetTranslated(0.0f, eqAreaHeight)
+ .GetMidHPadded(eqAreaHalfWidth);
+
// Areas for model and IR
const float fileWidth = 250.0f;
const float fileHeight = 30.0f;
const float fileSpace = 10.0f;
- const IRECT modelArea = content.GetFromBottom(2.0f * fileHeight + fileSpace).GetFromTop(fileHeight).GetMidHPadded(fileWidth);
- const IRECT irArea = content.GetFromBottom(fileHeight).GetMidHPadded(fileWidth);
-
+ const IRECT modelArea = content.GetFromBottom(2.0f * fileHeight + fileSpace)
+ .GetFromTop(fileHeight)
+ .GetMidHPadded(fileWidth);
+ const IRECT irArea =
+ content.GetFromBottom(fileHeight).GetMidHPadded(fileWidth);
+
// Areas for meters
const float meterHalfHeight = 0.5f * 250.0f;
- const IRECT inputMeterArea = inputKnobArea.GetFromLeft(knobHalfPad).GetMidHPadded(knobHalfPad).GetMidVPadded(meterHalfHeight).GetTranslated(-knobPad, 0.0f);
- const IRECT outputMeterArea = outputKnobArea.GetFromRight(knobHalfPad).GetMidHPadded(knobHalfPad).GetMidVPadded(meterHalfHeight).GetTranslated(knobPad, 0.0f);
-
- //auto tolexPNG = pGraphics->LoadBitmap(TOLEX_FN);
- //pGraphics->AttachControl(new IBitmapControl(pGraphics->GetBounds(), tolexPNG, kNoParameter))->SetBlend(IBlend(EBlend::Default, 0.5));
- // The background inside the outermost border
- pGraphics->AttachControl(new IVPanelControl(mainArea, "", style.WithColor(kFG, PluginColors::NAM_1))); // .WithContrast(-0.75)
- pGraphics->AttachControl(new IVLabelControl(titleLabel, "Neural Amp Modeler", style
- .WithDrawFrame(false)
- .WithValueText({30, EAlign::Center, PluginColors::NAM_3})));
+ const IRECT inputMeterArea = inputKnobArea.GetFromLeft(knobHalfPad)
+ .GetMidHPadded(knobHalfPad)
+ .GetMidVPadded(meterHalfHeight)
+ .GetTranslated(-knobPad, 0.0f);
+ const IRECT outputMeterArea = outputKnobArea.GetFromRight(knobHalfPad)
+ .GetMidHPadded(knobHalfPad)
+ .GetMidVPadded(meterHalfHeight)
+ .GetTranslated(knobPad, 0.0f);
+
+ // auto tolexPNG = pGraphics->LoadBitmap(TOLEX_FN);
+ // pGraphics->AttachControl(new IBitmapControl(pGraphics->GetBounds(),
+ // tolexPNG, kNoParameter))->SetBlend(IBlend(EBlend::Default, 0.5));
+ // The background inside the outermost border
+ pGraphics->AttachControl(new IVPanelControl(
+ mainArea, "",
+ style.WithColor(kFG, PluginColors::NAM_1))); // .WithContrast(-0.75)
+ pGraphics->AttachControl(
+ new IVLabelControl(titleLabel, "Neural Amp Modeler",
+ style.WithDrawFrame(false).WithValueText(
+ {30, EAlign::Center, PluginColors::NAM_3})));
// Model loader button
- auto loadNAM = [&, pGraphics](IControl* pCaller) {
+ auto loadNAM = [&, pGraphics](IControl *pCaller) {
WDL_String filename;
WDL_String path(this->mNAMPath.remove_filepart());
pGraphics->PromptForFile(filename, path);
if (filename.GetLength()) {
- // Sets mNAMPath and mStagedNAM
- bool success = this->_GetNAM(filename);
- // TODO error messages like the IR loader.
- if (!success)
- pGraphics->ShowMessageBox("Failed to load NAM model. If the model is an old \"directory-style\" model, it can be converted using the utility at https://github.com/sdatkinson/nam-model-utility", "Failed to load model!", kMB_OK);
+ // Sets mNAMPath and mStagedNAM
+ bool success = this->_GetNAM(filename);
+ // TODO error messages like the IR loader.
+ if (!success)
+ pGraphics->ShowMessageBox(
+ "Failed to load NAM model. If the model is an old "
+ "\"directory-style\" model, it can be converted using the "
+ "utility at https://github.com/sdatkinson/nam-model-utility",
+ "Failed to load model!", kMB_OK);
}
};
#if defined OS_MAC
// Legacy directory-based loader.
- auto loadNAMLegacy = [&, pGraphics](IControl* pCaller) {
+ auto loadNAMLegacy = [&, pGraphics](IControl *pCaller) {
WDL_String dir;
- pGraphics->PromptForDirectory(dir, [&](const WDL_String& fileName, const WDL_String& path){
- if (path.GetLength())
- _GetNAMLegacy(path);
- });
+ pGraphics->PromptForDirectory(
+ dir, [&](const WDL_String &fileName, const WDL_String &path) {
+ if (path.GetLength())
+ _GetNAMLegacy(path);
+ });
};
#endif
// IR loader button
- auto loadIR = [&, pGraphics](IControl* pCaller) {
+ auto loadIR = [&, pGraphics](IControl *pCaller) {
WDL_String fileName;
WDL_String path(this->mIRPath.remove_filepart());
pGraphics->PromptForFile(fileName, path);
@@ -226,269 +236,345 @@ NeuralAmpModeler::NeuralAmpModeler(const InstanceInfo& info)
this->mIRPath = fileName;
const dsp::wav::LoadReturnCode retCode = this->_GetIR(fileName);
if (retCode != dsp::wav::LoadReturnCode::SUCCESS) {
- std::stringstream message;
- message << "Failed to load IR file " << fileName.Get() << ":\n";
- switch (retCode) {
- case (dsp::wav::LoadReturnCode::ERROR_OPENING):
- message << "Failed to open file (is it being used by another program?)";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_NOT_RIFF):
- message << "File is not a WAV file.";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_NOT_WAVE):
- message << "File is not a WAV file.";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_MISSING_FMT):
- message << "File is missing expected format chunk.";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_INVALID_FILE):
- message << "WAV file contents are invalid.";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_IEEE_FLOAT):
- message << "Unsupported file format \"IEEE float\"";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_ALAW):
- message << "Unsupported file format \"A-law\"";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_MULAW):
- message << "Unsupported file format \"mu-law\"";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_EXTENSIBLE):
- message << "Unsupported file format \"extensible\"";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_NOT_MONO):
- message << "File is not mono.";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_BITS_PER_SAMPLE):
- message << "Unsupported bits per sample";
- break;
- case (dsp::wav::LoadReturnCode::ERROR_OTHER):
- message << "???";
- break;
- default:
- message << "???";
- break;
- }
- pGraphics->ShowMessageBox(message.str().c_str(), "Failed to load IR!", kMB_OK);
+ std::stringstream message;
+ message << "Failed to load IR file " << fileName.Get() << ":\n";
+ switch (retCode) {
+ case (dsp::wav::LoadReturnCode::ERROR_OPENING):
+ message
+ << "Failed to open file (is it being used by another program?)";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_NOT_RIFF):
+ message << "File is not a WAV file.";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_NOT_WAVE):
+ message << "File is not a WAV file.";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_MISSING_FMT):
+ message << "File is missing expected format chunk.";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_INVALID_FILE):
+ message << "WAV file contents are invalid.";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_IEEE_FLOAT):
+ message << "Unsupported file format \"IEEE float\"";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_ALAW):
+ message << "Unsupported file format \"A-law\"";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_MULAW):
+ message << "Unsupported file format \"mu-law\"";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_EXTENSIBLE):
+ message << "Unsupported file format \"extensible\"";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_NOT_MONO):
+ message << "File is not mono.";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_BITS_PER_SAMPLE):
+ message << "Unsupported bits per sample";
+ break;
+ case (dsp::wav::LoadReturnCode::ERROR_OTHER):
+ message << "???";
+ break;
+ default:
+ message << "???";
+ break;
+ }
+ pGraphics->ShowMessageBox(message.str().c_str(), "Failed to load IR!",
+ kMB_OK);
}
}
};
// Model-clearing function
- auto ClearNAM = [&, pGraphics](IControl* pCaller) {
+ auto ClearNAM = [&, pGraphics](IControl *pCaller) {
this->mFlagRemoveNAM = true;
};
// IR-clearing function
- auto ClearIR = [&, pGraphics](IControl* pCaller) {
+ auto ClearIR = [&, pGraphics](IControl *pCaller) {
this->mFlagRemoveIR = true;
};
-
+
// Graphics objects for what NAM is loaded
- const float iconWidth = fileHeight; // Square icon
- pGraphics->AttachControl(new IVPanelControl(modelArea, "", style.WithColor(kFG, PluginColors::NAM_1)));
- pGraphics->AttachControl(new IRolloverSVGButtonControl(modelArea.GetFromLeft(iconWidth).GetPadded(-2.f), loadNAM, fileSVG));
+ const float iconWidth = fileHeight; // Square icon
+ pGraphics->AttachControl(new IVPanelControl(
+ modelArea, "", style.WithColor(kFG, PluginColors::NAM_1)));
+ pGraphics->AttachControl(new IRolloverSVGButtonControl(
+ modelArea.GetFromLeft(iconWidth).GetPadded(-2.f), loadNAM, fileSVG));
#if defined OS_MAC
- // Extra button for legacy model loading since Sandboxing prevent the Windows way of doing it.
- pGraphics->AttachControl(new IRolloverSVGButtonControl(modelArea.GetFromLeft(iconWidth).GetTranslated(iconWidth, 0.0f).GetPadded(-2.f), loadNAMLegacy, folderSVG));
+ // Extra button for legacy model loading since Sandboxing prevent the
+ // Windows way of doing it.
+ pGraphics->AttachControl(
+ new IRolloverSVGButtonControl(modelArea.GetFromLeft(iconWidth)
+ .GetTranslated(iconWidth, 0.0f)
+ .GetPadded(-2.f),
+ loadNAMLegacy, folderSVG));
#endif
- pGraphics->AttachControl(new IRolloverSVGButtonControl(modelArea.GetFromRight(iconWidth).GetPadded(-2.f), ClearNAM, closeButtonSVG));
- pGraphics->AttachControl(new IVUpdateableLabelControl(modelArea.GetReducedFromLeft(iconWidth).GetReducedFromRight(iconWidth), this->mDefaultNAMString.Get(), style.WithDrawFrame(false).WithValueText(style.valueText.WithVAlign(EVAlign::Middle))), kCtrlTagModelName);
+ pGraphics->AttachControl(new IRolloverSVGButtonControl(
+ modelArea.GetFromRight(iconWidth).GetPadded(-2.f), ClearNAM,
+ closeButtonSVG));
+ pGraphics->AttachControl(
+ new IVUpdateableLabelControl(
+ modelArea.GetReducedFromLeft(iconWidth).GetReducedFromRight(
+ iconWidth),
+ this->mDefaultNAMString.Get(),
+ style.WithDrawFrame(false).WithValueText(
+ style.valueText.WithVAlign(EVAlign::Middle))),
+ kCtrlTagModelName);
// IR
- pGraphics->AttachControl(new IVPanelControl(irArea, "", style.WithColor(kFG, PluginColors::NAM_1)));
- pGraphics->AttachControl(new IRolloverSVGButtonControl(irArea.GetFromLeft(iconWidth).GetPadded(-2.f), loadIR, fileSVG));
- pGraphics->AttachControl(new IRolloverSVGButtonControl(irArea.GetFromRight(iconWidth).GetPadded(-2.f), ClearIR, closeButtonSVG));
- pGraphics->AttachControl(new IVUpdateableLabelControl(irArea.GetReducedFromLeft(iconWidth).GetReducedFromRight(iconWidth), this->mDefaultIRString.Get(), style.WithDrawFrame(false).WithValueText(style.valueText.WithVAlign(EVAlign::Middle))), kCtrlTagIRName);
+ pGraphics->AttachControl(new IVPanelControl(
+ irArea, "", style.WithColor(kFG, PluginColors::NAM_1)));
+ pGraphics->AttachControl(new IRolloverSVGButtonControl(
+ irArea.GetFromLeft(iconWidth).GetPadded(-2.f), loadIR, fileSVG));
+ pGraphics->AttachControl(new IRolloverSVGButtonControl(
+ irArea.GetFromRight(iconWidth).GetPadded(-2.f), ClearIR,
+ closeButtonSVG));
+ pGraphics->AttachControl(
+ new IVUpdateableLabelControl(
+ irArea.GetReducedFromLeft(iconWidth).GetReducedFromRight(iconWidth),
+ this->mDefaultIRString.Get(),
+ style.WithDrawFrame(false).WithValueText(
+ style.valueText.WithVAlign(EVAlign::Middle))),
+ kCtrlTagIRName);
// Tone stack toggle
- IVSlideSwitchControl* toneStackSlider = new IVSlideSwitchControl(
- eqToggleArea,
- kEQActive,
- "EQ",
- style,
- true, // valueInButton
- EDirection::Horizontal
- );
+ IVSlideSwitchControl *toneStackSlider =
+ new IVSlideSwitchControl(eqToggleArea, kEQActive, "EQ", style,
+ true, // valueInButton
+ EDirection::Horizontal);
pGraphics->AttachControl(toneStackSlider);
-
+
// The knobs
- pGraphics->AttachControl(new IVKnobControl(inputKnobArea, kInputLevel, "", style));
+ pGraphics->AttachControl(
+ new IVKnobControl(inputKnobArea, kInputLevel, "", style));
const bool toneStackIsActive = this->GetParam(kEQActive)->Value();
- const IVStyle toneStackInitialStyle = toneStackIsActive ? style : styleInactive;
- IVKnobControl* bassControl = new IVKnobControl(bassKnobArea, kToneBass, "", toneStackInitialStyle);
- IVKnobControl* middleControl = new IVKnobControl(middleKnobArea, kToneMid, "", toneStackInitialStyle);
- IVKnobControl* trebleControl = new IVKnobControl(trebleKnobArea, kToneTreble, "", toneStackInitialStyle);
+ const IVStyle toneStackInitialStyle =
+ toneStackIsActive ? style : styleInactive;
+ IVKnobControl *bassControl =
+ new IVKnobControl(bassKnobArea, kToneBass, "", toneStackInitialStyle);
+ IVKnobControl *middleControl =
+ new IVKnobControl(middleKnobArea, kToneMid, "", toneStackInitialStyle);
+ IVKnobControl *trebleControl = new IVKnobControl(
+ trebleKnobArea, kToneTreble, "", toneStackInitialStyle);
pGraphics->AttachControl(bassControl);
pGraphics->AttachControl(middleControl);
pGraphics->AttachControl(trebleControl);
- pGraphics->AttachControl(new IVKnobControl(outputKnobArea, kOutputLevel, "", style));
-
- // Extend the slider action function to set the style of the knobs
- auto setKnobStyles = [&, pGraphics, bassControl, middleControl, trebleControl](IControl* pCaller) {
- const bool toneStackActive = pCaller->GetValue() > 0;
- const IVStyle toneStackStyle = toneStackActive ? style : styleInactive;
- bassControl->SetStyle(toneStackStyle);
- middleControl->SetStyle(toneStackStyle);
- trebleControl->SetStyle(toneStackStyle);
-
- bassControl->SetDirty(false);
- middleControl->SetDirty(false);
- trebleControl->SetDirty(false);
+ pGraphics->AttachControl(
+ new IVKnobControl(outputKnobArea, kOutputLevel, "", style));
+
+ // Extend the slider action function to set the style of the knobs
+ auto setKnobStyles = [&, pGraphics, bassControl, middleControl,
+ trebleControl](IControl *pCaller) {
+ const bool toneStackActive = pCaller->GetValue() > 0;
+ const IVStyle toneStackStyle = toneStackActive ? style : styleInactive;
+ bassControl->SetStyle(toneStackStyle);
+ middleControl->SetStyle(toneStackStyle);
+ trebleControl->SetStyle(toneStackStyle);
+
+ bassControl->SetDirty(false);
+ middleControl->SetDirty(false);
+ trebleControl->SetDirty(false);
};
auto defaultToneStackSliderAction = toneStackSlider->GetActionFunction();
- auto toneStackAction = [defaultToneStackSliderAction, setKnobStyles](IControl* pCaller) {
- defaultToneStackSliderAction(pCaller);
- setKnobStyles(pCaller);
+ auto toneStackAction = [defaultToneStackSliderAction,
+ setKnobStyles](IControl *pCaller) {
+ defaultToneStackSliderAction(pCaller);
+ setKnobStyles(pCaller);
};
toneStackSlider->SetActionFunction(toneStackAction);
// The meters
const float meterMin = -60.0f;
const float meterMax = -0.01f;
- pGraphics->AttachControl(new IVPeakAvgMeterControl(inputMeterArea, "", style.WithWidgetFrac(0.5)
- .WithShowValue(false)
- .WithColor(kFG, PluginColors::NAM_2), EDirection::Vertical, {}, 0, meterMin, meterMax, {}), kCtrlTagInputMeter)
- ->As<IVPeakAvgMeterControl<>>()->SetPeakSize(2.0f);
- pGraphics->AttachControl(new IVPeakAvgMeterControl(outputMeterArea, "", style.WithWidgetFrac(0.5)
- .WithShowValue(false)
- .WithColor(kFG, PluginColors::NAM_2), EDirection::Vertical, {}, 0, meterMin, meterMax, {}), kCtrlTagOutputMeter)
- ->As<IVPeakAvgMeterControl<>>()->SetPeakSize(2.0f);
-
-// Help/about box
- pGraphics->AttachControl(new IRolloverCircleSVGButtonControl(mainArea.GetFromTRHC(50, 50).GetCentredInside(20, 20), [pGraphics](IControl* pCaller){
- pGraphics->GetControlWithTag(kCtrlTagAboutBox)->As<IAboutBoxControl>()->HideAnimated(false);
- }, helpSVG));
-
- pGraphics->AttachControl(new IAboutBoxControl(b,
- COLOR_GRAY,
- // AttachFunc
- [](IContainerBase* pParent, const IRECT& r) {
- pParent->AddChildControl(new IPanelControl(IRECT(), IPattern::CreateLinearGradient(r, EDirection::Vertical, { {PluginColors::NAM_3, 0.f}, {PluginColors::NAM_1, 1.f} })));
-
- pParent->AddChildControl(new IVPanelControl(IRECT(), "", style.WithColor(kFR, PluginColors::NAM_3.WithOpacity(0.1f)).WithColor(kFG, PluginColors::NAM_1.WithOpacity(0.1f))));
-
- pParent->AddChildControl(new IVLabelControl(IRECT(), "Neural Amp Modeler", style
- .WithDrawFrame(false)
- .WithValueText({30, EAlign::Center, PluginColors::HELP_TEXT})));
-
- WDL_String versionStr {"Version "};
- versionStr.Append(PLUG_VERSION_STR);
- pParent->AddChildControl(new IVLabelControl(IRECT(), versionStr.Get(), style
- .WithDrawFrame(false)
- .WithValueText({DEFAULT_TEXT_SIZE, EAlign::Center, PluginColors::HELP_TEXT })));
- pParent->AddChildControl(new IVLabelControl(IRECT(), "By Steven Atkinson", style
- .WithDrawFrame(false)
- .WithValueText({DEFAULT_TEXT_SIZE, EAlign::Center, PluginColors::HELP_TEXT})));
- pParent->AddChildControl(new IURLControl(IRECT(),
- "Train your own model",
- "https://github.com/sdatkinson/neural-amp-modeler", {DEFAULT_TEXT_SIZE, PluginColors::HELP_TEXT }));
-
- },
- // ResizeFunc
- [](IContainerBase* pParent, const IRECT& r) {
- const IRECT mainArea = r.GetPadded(-20);
- const auto content = mainArea.GetPadded(-10);
- const auto titleLabel = content.GetFromTop(50);
- pParent->GetChild(0)->SetTargetAndDrawRECTs(r);
- pParent->GetChild(1)->SetTargetAndDrawRECTs(mainArea);
- pParent->GetChild(2)->SetTargetAndDrawRECTs(titleLabel);
- pParent->GetChild(3)->SetTargetAndDrawRECTs(titleLabel.GetVShifted(titleLabel.H()));
- pParent->GetChild(4)->SetTargetAndDrawRECTs(titleLabel.GetVShifted(titleLabel.H() + 20));
- pParent->GetChild(5)->SetTargetAndDrawRECTs(titleLabel.GetVShifted(titleLabel.H() + 40));
- },
- // Animation Time
- 0)
- , kCtrlTagAboutBox)->Hide(true);
+ pGraphics
+ ->AttachControl(
+ new IVPeakAvgMeterControl(
+ inputMeterArea, "",
+ style.WithWidgetFrac(0.5).WithShowValue(false).WithColor(
+ kFG, PluginColors::NAM_2),
+ EDirection::Vertical, {}, 0, meterMin, meterMax, {}),
+ kCtrlTagInputMeter)
+ ->As<IVPeakAvgMeterControl<>>()
+ ->SetPeakSize(2.0f);
+ pGraphics
+ ->AttachControl(
+ new IVPeakAvgMeterControl(
+ outputMeterArea, "",
+ style.WithWidgetFrac(0.5).WithShowValue(false).WithColor(
+ kFG, PluginColors::NAM_2),
+ EDirection::Vertical, {}, 0, meterMin, meterMax, {}),
+ kCtrlTagOutputMeter)
+ ->As<IVPeakAvgMeterControl<>>()
+ ->SetPeakSize(2.0f);
+
+ // Help/about box
+ pGraphics->AttachControl(new IRolloverCircleSVGButtonControl(
+ mainArea.GetFromTRHC(50, 50).GetCentredInside(20, 20),
+ [pGraphics](IControl *pCaller) {
+ pGraphics->GetControlWithTag(kCtrlTagAboutBox)
+ ->As<IAboutBoxControl>()
+ ->HideAnimated(false);
+ },
+ helpSVG));
+
+ pGraphics
+ ->AttachControl(
+ new IAboutBoxControl(
+ b, COLOR_GRAY,
+ // AttachFunc
+ [](IContainerBase *pParent, const IRECT &r) {
+ pParent->AddChildControl(new IPanelControl(
+ IRECT(), IPattern::CreateLinearGradient(
+ r, EDirection::Vertical,
+ {{PluginColors::NAM_3, 0.f},
+ {PluginColors::NAM_1, 1.f}})));
+
+ pParent->AddChildControl(new IVPanelControl(
+ IRECT(), "",
+ style
+ .WithColor(kFR, PluginColors::NAM_3.WithOpacity(0.1f))
+ .WithColor(kFG,
+ PluginColors::NAM_1.WithOpacity(0.1f))));
+
+ pParent->AddChildControl(new IVLabelControl(
+ IRECT(), "Neural Amp Modeler",
+ style.WithDrawFrame(false).WithValueText(
+ {30, EAlign::Center, PluginColors::HELP_TEXT})));
+
+ WDL_String versionStr{"Version "};
+ versionStr.Append(PLUG_VERSION_STR);
+ pParent->AddChildControl(new IVLabelControl(
+ IRECT(), versionStr.Get(),
+ style.WithDrawFrame(false).WithValueText(
+ {DEFAULT_TEXT_SIZE, EAlign::Center,
+ PluginColors::HELP_TEXT})));
+ pParent->AddChildControl(new IVLabelControl(
+ IRECT(), "By Steven Atkinson",
+ style.WithDrawFrame(false).WithValueText(
+ {DEFAULT_TEXT_SIZE, EAlign::Center,
+ PluginColors::HELP_TEXT})));
+ pParent->AddChildControl(new IURLControl(
+ IRECT(), "Train your own model",
+ "https://github.com/sdatkinson/neural-amp-modeler",
+ {DEFAULT_TEXT_SIZE, PluginColors::HELP_TEXT}));
+ },
+ // ResizeFunc
+ [](IContainerBase *pParent, const IRECT &r) {
+ const IRECT mainArea = r.GetPadded(-20);
+ const auto content = mainArea.GetPadded(-10);
+ const auto titleLabel = content.GetFromTop(50);
+ pParent->GetChild(0)->SetTargetAndDrawRECTs(r);
+ pParent->GetChild(1)->SetTargetAndDrawRECTs(mainArea);
+ pParent->GetChild(2)->SetTargetAndDrawRECTs(titleLabel);
+ pParent->GetChild(3)->SetTargetAndDrawRECTs(
+ titleLabel.GetVShifted(titleLabel.H()));
+ pParent->GetChild(4)->SetTargetAndDrawRECTs(
+ titleLabel.GetVShifted(titleLabel.H() + 20));
+ pParent->GetChild(5)->SetTargetAndDrawRECTs(
+ titleLabel.GetVShifted(titleLabel.H() + 40));
+ },
+ // Animation Time
+ 0),
+ kCtrlTagAboutBox)
+ ->Hide(true);
};
}
-NeuralAmpModeler::~NeuralAmpModeler()
-{
- this->_DeallocateIOPointers();
-}
+NeuralAmpModeler::~NeuralAmpModeler() { this->_DeallocateIOPointers(); }
-void NeuralAmpModeler::ProcessBlock(iplug::sample** inputs, iplug::sample** outputs, int nFrames)
-{
- const size_t numChannelsExternalIn = (size_t) this->NInChansConnected();
- const size_t numChannelsExternalOut = (size_t) this->NOutChansConnected();
+void NeuralAmpModeler::ProcessBlock(iplug::sample **inputs,
+ iplug::sample **outputs, int nFrames) {
+ const size_t numChannelsExternalIn = (size_t)this->NInChansConnected();
+ const size_t numChannelsExternalOut = (size_t)this->NOutChansConnected();
const size_t numChannelsInternal = this->mNUM_INTERNAL_CHANNELS;
const size_t numFrames = (size_t)nFrames;
this->_PrepareBuffers(numChannelsInternal, numFrames);
// Input is collapsed to mono in preparation for the NAM.
- this->_ProcessInput(inputs, numFrames, numChannelsExternalIn, numChannelsInternal);
+ this->_ProcessInput(inputs, numFrames, numChannelsExternalIn,
+ numChannelsInternal);
this->_ApplyDSPStaging();
const bool toneStackActive = this->GetParam(kEQActive)->Value();
- if (mNAM != nullptr)
- {
+ if (mNAM != nullptr) {
// TODO remove input / output gains from here.
const double inputGain = 1.0;
const double outputGain = 1.0;
- const int nChans = (int) numChannelsInternal;
- mNAM->process(this->mInputPointers, this->mOutputPointers, nChans, nFrames, inputGain, outputGain, mNAMParams);
+ const int nChans = (int)numChannelsInternal;
+ mNAM->process(this->mInputPointers, this->mOutputPointers, nChans, nFrames,
+ inputGain, outputGain, mNAMParams);
mNAM->finalize_(nFrames);
- }
- else {
+ } else {
this->_FallbackDSP(nFrames);
}
-
- sample** toneStackOutPointers = this->mOutputPointers;
+
+ sample **toneStackOutPointers = this->mOutputPointers;
if (toneStackActive) {
- // Tone stack
- const double sampleRate = this->GetSampleRate();
- // Translate params from knob 0-10 to dB.
- // Tuned ranges based on my ear. E.g. seems treble doesn't need nearly as
- // much swing as bass can use.
- const double bassGainDB = 4.0 * (this->GetParam(kToneBass)->Value() - 5.0); // +/- 20
- const double midGainDB = 3.0 * (this->GetParam(kToneMid)->Value() - 5.0); // +/- 15
- const double trebleGainDB = 2.0 * (this->GetParam(kToneTreble)->Value() - 5.0); // +/- 10
-
- const double bassFrequency = 150.0;
- const double midFrequency = 425.0;
- const double trebleFrequency = 1800.0;
- const double bassQuality = 0.707;
- // Wider EQ on mid bump up to sound less honky.
- const double midQuality = midGainDB < 0.0 ? 1.5 : 0.7;
- const double trebleQuality = 0.707;
-
-
- // Define filter parameters
- recursive_linear_filter::BiquadParams bassParams(sampleRate, bassFrequency, bassQuality, bassGainDB);
- recursive_linear_filter::BiquadParams midParams(sampleRate, midFrequency, midQuality, midGainDB);
- recursive_linear_filter::BiquadParams trebleParams(sampleRate, trebleFrequency, trebleQuality, trebleGainDB);
- // Apply tone stack
- // Set parameters
- this->mToneBass.SetParams(bassParams);
- this->mToneMid.SetParams(midParams);
- this->mToneTreble.SetParams(trebleParams);
- sample** bassPointers = this->mToneBass.Process(this->mOutputPointers, numChannelsInternal, numFrames);
- sample** midPointers = this->mToneMid.Process(bassPointers, numChannelsInternal, numFrames);
- sample** treblePointers = this->mToneTreble.Process(midPointers, numChannelsInternal, numFrames);
- toneStackOutPointers = treblePointers;
+ // Tone stack
+ const double sampleRate = this->GetSampleRate();
+ // Translate params from knob 0-10 to dB.
+ // Tuned ranges based on my ear. E.g. seems treble doesn't need nearly as
+ // much swing as bass can use.
+ const double bassGainDB =
+ 4.0 * (this->GetParam(kToneBass)->Value() - 5.0); // +/- 20
+ const double midGainDB =
+ 3.0 * (this->GetParam(kToneMid)->Value() - 5.0); // +/- 15
+ const double trebleGainDB =
+ 2.0 * (this->GetParam(kToneTreble)->Value() - 5.0); // +/- 10
+
+ const double bassFrequency = 150.0;
+ const double midFrequency = 425.0;
+ const double trebleFrequency = 1800.0;
+ const double bassQuality = 0.707;
+ // Wider EQ on mid bump up to sound less honky.
+ const double midQuality = midGainDB < 0.0 ? 1.5 : 0.7;
+ const double trebleQuality = 0.707;
+
+ // Define filter parameters
+ recursive_linear_filter::BiquadParams bassParams(sampleRate, bassFrequency,
+ bassQuality, bassGainDB);
+ recursive_linear_filter::BiquadParams midParams(sampleRate, midFrequency,
+ midQuality, midGainDB);
+ recursive_linear_filter::BiquadParams trebleParams(
+ sampleRate, trebleFrequency, trebleQuality, trebleGainDB);
+ // Apply tone stack
+ // Set parameters
+ this->mToneBass.SetParams(bassParams);
+ this->mToneMid.SetParams(midParams);
+ this->mToneTreble.SetParams(trebleParams);
+ sample **bassPointers = this->mToneBass.Process(
+ this->mOutputPointers, numChannelsInternal, numFrames);
+ sample **midPointers =
+ this->mToneMid.Process(bassPointers, numChannelsInternal, numFrames);
+ sample **treblePointers =
+ this->mToneTreble.Process(midPointers, numChannelsInternal, numFrames);
+ toneStackOutPointers = treblePointers;
}
-
- sample** irPointers = toneStackOutPointers;
+
+ sample **irPointers = toneStackOutPointers;
if (this->mIR != nullptr)
- irPointers = this->mIR->Process(toneStackOutPointers, numChannelsInternal, numFrames);
-
+ irPointers = this->mIR->Process(toneStackOutPointers, numChannelsInternal,
+ numFrames);
+
// Let's get outta here
// This is where we exit mono for whatever the output requires.
- this->_ProcessOutput(irPointers, outputs, numFrames, numChannelsInternal, numChannelsExternalOut);
+ this->_ProcessOutput(irPointers, outputs, numFrames, numChannelsInternal,
+ numChannelsExternalOut);
// * Output of input leveling (inputs -> mInputPointers),
// * Output of output leveling (mOutputPointers -> outputs)
- this->_UpdateMeters(this->mInputPointers, outputs, numFrames, numChannelsInternal, numChannelsExternalOut);
+ this->_UpdateMeters(this->mInputPointers, outputs, numFrames,
+ numChannelsInternal, numChannelsExternalOut);
}
-bool NeuralAmpModeler::SerializeState(IByteChunk& chunk) const
-{
- // Model directory (don't serialize the model itself; we'll just load it again when we unserialize)
+bool NeuralAmpModeler::SerializeState(IByteChunk &chunk) const {
+ // Model directory (don't serialize the model itself; we'll just load it again
+ // when we unserialize)
chunk.PutStr(this->mNAMPath.Get());
chunk.PutStr(this->mNAMLegacyPath.Get());
chunk.PutStr(this->mIRPath.Get());
return SerializeParams(chunk);
}
-int NeuralAmpModeler::UnserializeState(const IByteChunk& chunk, int startPos)
-{
+int NeuralAmpModeler::UnserializeState(const IByteChunk &chunk, int startPos) {
WDL_String dir;
startPos = chunk.GetStr(this->mNAMPath, startPos);
startPos = chunk.GetStr(this->mNAMLegacyPath, startPos);
@@ -505,8 +591,7 @@ int NeuralAmpModeler::UnserializeState(const IByteChunk& chunk, int startPos)
return retcode;
}
-void NeuralAmpModeler::OnUIOpen()
-{
+void NeuralAmpModeler::OnUIOpen() {
Plugin::OnUIOpen();
if (this->mNAMLegacyPath.GetLength())
this->_SetModelMsg(this->mNAMLegacyPath);
@@ -518,25 +603,24 @@ void NeuralAmpModeler::OnUIOpen()
// Private methods ============================================================
-void NeuralAmpModeler::_AllocateIOPointers(const size_t nChans)
-{
+void NeuralAmpModeler::_AllocateIOPointers(const size_t nChans) {
if (this->mInputPointers != nullptr)
- throw std::runtime_error("Tried to re-allocate mInputPointers without freeing");
- this->mInputPointers = new sample*[nChans];
+ throw std::runtime_error(
+ "Tried to re-allocate mInputPointers without freeing");
+ this->mInputPointers = new sample *[nChans];
if (this->mInputPointers == nullptr)
throw std::runtime_error("Failed to allocate pointer to input buffer!\n");
if (this->mOutputPointers != nullptr)
- throw std::runtime_error("Tried to re-allocate mOutputPointers without freeing");
- this->mOutputPointers = new sample*[nChans];
+ throw std::runtime_error(
+ "Tried to re-allocate mOutputPointers without freeing");
+ this->mOutputPointers = new sample *[nChans];
if (this->mOutputPointers == nullptr)
throw std::runtime_error("Failed to allocate pointer to output buffer!\n");
}
-void NeuralAmpModeler::_ApplyDSPStaging()
-{
+void NeuralAmpModeler::_ApplyDSPStaging() {
// Move things from staged to live
- if (this->mStagedNAM != nullptr)
- {
+ if (this->mStagedNAM != nullptr) {
// Move from staged to active DSP
this->mNAM = std::move(this->mStagedNAM);
this->mStagedNAM = nullptr;
@@ -561,8 +645,7 @@ void NeuralAmpModeler::_ApplyDSPStaging()
}
}
-void NeuralAmpModeler::_DeallocateIOPointers()
-{
+void NeuralAmpModeler::_DeallocateIOPointers() {
if (this->mInputPointers != nullptr) {
delete[] this->mInputPointers;
this->mInputPointers = nullptr;
@@ -574,19 +657,18 @@ void NeuralAmpModeler::_DeallocateIOPointers()
this->mOutputPointers = nullptr;
}
if (this->mOutputPointers != nullptr)
- throw std::runtime_error("Failed to deallocate pointer to output buffer!\n");
+ throw std::runtime_error(
+ "Failed to deallocate pointer to output buffer!\n");
}
-void NeuralAmpModeler::_FallbackDSP(const int nFrames)
-{
+void NeuralAmpModeler::_FallbackDSP(const int nFrames) {
const size_t nChans = this->mNUM_INTERNAL_CHANNELS;
- for (auto c=0; c<nChans; c++)
- for (auto s=0; s<nFrames; s++)
+ for (auto c = 0; c < nChans; c++)
+ for (auto s = 0; s < nFrames; s++)
this->mOutputArray[c][s] = this->mInputArray[c][s];
}
-bool NeuralAmpModeler::_GetNAM(const WDL_String& modelPath)
-{
+bool NeuralAmpModeler::_GetNAM(const WDL_String &modelPath) {
WDL_String previousNAMPath = this->mNAMPath;
WDL_String previousNAMLegacyPath = this->mNAMLegacyPath;
try {
@@ -595,11 +677,11 @@ bool NeuralAmpModeler::_GetNAM(const WDL_String& modelPath)
this->_SetModelMsg(modelPath);
this->mNAMPath = modelPath;
this->mNAMLegacyPath.Set("");
- }
- catch (std::exception& e) {
+ } catch (std::exception &e) {
std::stringstream ss;
ss << "FAILED to load model";
- SendControlMsgFromDelegate(kCtrlTagModelName, 0, int(strlen(ss.str().c_str())), ss.str().c_str());
+ SendControlMsgFromDelegate(kCtrlTagModelName, 0,
+ int(strlen(ss.str().c_str())), ss.str().c_str());
if (this->mStagedNAM != nullptr) {
this->mStagedNAM = nullptr;
}
@@ -612,8 +694,7 @@ bool NeuralAmpModeler::_GetNAM(const WDL_String& modelPath)
return true;
}
-bool NeuralAmpModeler::_GetNAMLegacy(const WDL_String& modelDir)
-{
+bool NeuralAmpModeler::_GetNAMLegacy(const WDL_String &modelDir) {
WDL_String previousNAMLegacyPath = this->mNAMLegacyPath;
WDL_String previousNAMPath = this->mNAMPath;
try {
@@ -622,11 +703,11 @@ bool NeuralAmpModeler::_GetNAMLegacy(const WDL_String& modelDir)
this->_SetModelMsg(modelDir);
this->mNAMLegacyPath = modelDir;
this->mNAMPath.Set("");
- }
- catch (std::exception& e) {
+ } catch (std::exception &e) {
std::stringstream ss;
ss << "FAILED to load legacy model";
- SendControlMsgFromDelegate(kCtrlTagModelName, 0, int(strlen(ss.str().c_str())), ss.str().c_str());
+ SendControlMsgFromDelegate(kCtrlTagModelName, 0,
+ int(strlen(ss.str().c_str())), ss.str().c_str());
if (mStagedNAM != nullptr) {
mStagedNAM = nullptr;
}
@@ -639,84 +720,83 @@ bool NeuralAmpModeler::_GetNAMLegacy(const WDL_String& modelDir)
return true;
}
-dsp::wav::LoadReturnCode NeuralAmpModeler::_GetIR(const WDL_String& irPath)
-{
+dsp::wav::LoadReturnCode NeuralAmpModeler::_GetIR(const WDL_String &irPath) {
// FIXME it'd be better for the path to be "staged" as well. Just in case the
// path and the model got caught on opposite sides of the fence...
WDL_String previousIRPath = this->mIRPath;
const double sampleRate = this->GetSampleRate();
dsp::wav::LoadReturnCode wavState = dsp::wav::LoadReturnCode::ERROR_OTHER;
try {
- this->mStagedIR = std::make_unique<dsp::ImpulseResponse>(irPath, sampleRate);
+ this->mStagedIR =
+ std::make_unique<dsp::ImpulseResponse>(irPath, sampleRate);
wavState = this->mStagedIR->GetWavState();
- }
- catch (std::exception& e) {
+ } catch (std::exception &e) {
wavState = dsp::wav::LoadReturnCode::ERROR_OTHER;
- std::cerr << "Caught unhandled exception while attempting to load IR:" << std::endl;
+ std::cerr << "Caught unhandled exception while attempting to load IR:"
+ << std::endl;
std::cerr << e.what() << std::endl;
}
if (wavState == dsp::wav::LoadReturnCode::SUCCESS) {
- this->_SetIRMsg(irPath);
- this->mIRPath = irPath;
- }
- else {
- if (this->mStagedIR != nullptr) {
- this->mStagedIR = nullptr;
- }
- this->mIRPath = previousIRPath;
- std::stringstream ss;
- ss << "FAILED to load IR";
- SendControlMsgFromDelegate(kCtrlTagIRName, 0, int(strlen(ss.str().c_str())), ss.str().c_str());
+ this->_SetIRMsg(irPath);
+ this->mIRPath = irPath;
+ } else {
+ if (this->mStagedIR != nullptr) {
+ this->mStagedIR = nullptr;
+ }
+ this->mIRPath = previousIRPath;
+ std::stringstream ss;
+ ss << "FAILED to load IR";
+ SendControlMsgFromDelegate(kCtrlTagIRName, 0, int(strlen(ss.str().c_str())),
+ ss.str().c_str());
}
return wavState;
}
-size_t NeuralAmpModeler::_GetBufferNumChannels() const
-{
+size_t NeuralAmpModeler::_GetBufferNumChannels() const {
// Assumes input=output (no mono->stereo effects)
return this->mInputArray.size();
}
-size_t NeuralAmpModeler::_GetBufferNumFrames() const
-{
+size_t NeuralAmpModeler::_GetBufferNumFrames() const {
if (this->_GetBufferNumChannels() == 0)
return 0;
return this->mInputArray[0].size();
}
-void NeuralAmpModeler::_PrepareBuffers(const size_t numChannels, const size_t numFrames)
-{
+void NeuralAmpModeler::_PrepareBuffers(const size_t numChannels,
+ const size_t numFrames) {
const bool updateChannels = numChannels != this->_GetBufferNumChannels();
- const bool updateFrames = updateChannels || (this->_GetBufferNumFrames() != numFrames);
-// if (!updateChannels && !updateFrames) // Could we do this?
-// return;
-
+ const bool updateFrames =
+ updateChannels || (this->_GetBufferNumFrames() != numFrames);
+ // if (!updateChannels && !updateFrames) // Could we do this?
+ // return;
+
if (updateChannels) {
this->_PrepareIOPointers(numChannels);
this->mInputArray.resize(numChannels);
this->mOutputArray.resize(numChannels);
}
if (updateFrames) {
- for (auto c=0; c<this->mInputArray.size(); c++) {
+ for (auto c = 0; c < this->mInputArray.size(); c++) {
this->mInputArray[c].resize(numFrames);
std::fill(this->mInputArray[c].begin(), this->mInputArray[c].end(), 0.0);
}
- for (auto c=0; c<this->mOutputArray.size(); c++) {
+ for (auto c = 0; c < this->mOutputArray.size(); c++) {
this->mOutputArray[c].resize(numFrames);
- std::fill(this->mOutputArray[c].begin(), this->mOutputArray[c].end(), 0.0);
+ std::fill(this->mOutputArray[c].begin(), this->mOutputArray[c].end(),
+ 0.0);
}
}
// Would these ever get changed by something?
- for (auto c=0; c<this->mInputArray.size(); c++)
+ for (auto c = 0; c < this->mInputArray.size(); c++)
this->mInputPointers[c] = this->mInputArray[c].data();
- for (auto c=0; c<this->mOutputArray.size(); c++)
+ for (auto c = 0; c < this->mOutputArray.size(); c++)
this->mOutputPointers[c] = this->mOutputArray[c].data();
}
-void NeuralAmpModeler::_PrepareIOPointers(const size_t numChannels)
-{
+void NeuralAmpModeler::_PrepareIOPointers(const size_t numChannels) {
this->_DeallocateIOPointers();
this->_AllocateIOPointers(numChannels);
}
@@ -724,88 +804,80 @@ void NeuralAmpModeler::_PrepareIOPointers(const size_t numChannels)
void NeuralAmpModeler::_ProcessInput(iplug::sample **inputs,
const size_t nFrames,
const size_t nChansIn,
- const size_t nChansOut)
-{
+ const size_t nChansOut) {
// Assume _PrepareBuffers() was already called
const double gain = pow(10.0, GetParam(kInputLevel)->Value() / 20.0);
- if (nChansOut <= nChansIn) // Many->few: Drop additional channels
- for (size_t c=0; c<nChansOut; c++)
- for (size_t s=0; s<nFrames; s++)
+ if (nChansOut <= nChansIn) // Many->few: Drop additional channels
+ for (size_t c = 0; c < nChansOut; c++)
+ for (size_t s = 0; s < nFrames; s++)
this->mInputArray[c][s] = gain * inputs[c][s];
else {
// Something is wrong--this is a mono plugin. How could there be fewer
// incoming channels?
- throw std::runtime_error("Unexpected input processing--sees fewer than 1 incoming channel?");
+ throw std::runtime_error(
+ "Unexpected input processing--sees fewer than 1 incoming channel?");
}
}
-void NeuralAmpModeler::_ProcessOutput(iplug::sample** inputs,
+void NeuralAmpModeler::_ProcessOutput(iplug::sample **inputs,
iplug::sample **outputs,
const size_t nFrames,
const size_t nChansIn,
- const size_t nChansOut)
-{
+ const size_t nChansOut) {
const double gain = pow(10.0, GetParam(kOutputLevel)->Value() / 20.0);
// Assume _PrepareBuffers() was already called
if (nChansIn != 1)
throw std::runtime_error("Plugin is supposed to process in mono.");
// Broadcast the internal mono stream to all output channels.
const size_t cin = 0;
- for (auto cout=0; cout<nChansOut; cout++)
- for (auto s=0; s<nFrames; s++)
+ for (auto cout = 0; cout < nChansOut; cout++)
+ for (auto s = 0; s < nFrames; s++)
outputs[cout][s] = std::clamp(gain * inputs[cin][s], -1.0, 1.0);
}
-void NeuralAmpModeler::_SetModelMsg(const WDL_String& modelPath)
-{
+void NeuralAmpModeler::_SetModelMsg(const WDL_String &modelPath) {
auto dspPath = std::filesystem::path(modelPath.Get());
std::stringstream ss;
ss << "Loaded ";
if (dspPath.has_filename())
- ss << dspPath.filename().stem(); // /path/to/model.nam -> "model"
+ ss << dspPath.filename().stem(); // /path/to/model.nam -> "model"
else
ss << dspPath.parent_path().filename(); // /path/to/model/ -> "model"
- SendControlMsgFromDelegate(kCtrlTagModelName, 0, int(strlen(ss.str().c_str())), ss.str().c_str());
+ SendControlMsgFromDelegate(kCtrlTagModelName, 0,
+ int(strlen(ss.str().c_str())), ss.str().c_str());
}
-void NeuralAmpModeler::_SetIRMsg(const WDL_String& irPath)
-{
- this->mIRPath = irPath; // This might already be done elsewhere...need to dedup.
+void NeuralAmpModeler::_SetIRMsg(const WDL_String &irPath) {
+ this->mIRPath =
+ irPath; // This might already be done elsewhere...need to dedup.
auto dspPath = std::filesystem::path(irPath.Get());
std::stringstream ss;
ss << "Loaded " << dspPath.filename().stem();
- SendControlMsgFromDelegate(kCtrlTagIRName, 0, int(strlen(ss.str().c_str())), ss.str().c_str());
+ SendControlMsgFromDelegate(kCtrlTagIRName, 0, int(strlen(ss.str().c_str())),
+ ss.str().c_str());
}
-void NeuralAmpModeler::_UnsetModelMsg()
-{
+void NeuralAmpModeler::_UnsetModelMsg() {
this->_UnsetMsg(kCtrlTagModelName, this->mDefaultNAMString);
}
-void NeuralAmpModeler::_UnsetIRMsg()
-{
+void NeuralAmpModeler::_UnsetIRMsg() {
this->_UnsetMsg(kCtrlTagIRName, this->mDefaultIRString);
}
-void NeuralAmpModeler::_UnsetMsg(const int tag, const WDL_String &msg)
-{
+void NeuralAmpModeler::_UnsetMsg(const int tag, const WDL_String &msg) {
SendControlMsgFromDelegate(tag, 0, int(strlen(msg.Get())), msg.Get());
}
-void NeuralAmpModeler::_UpdateMeters(sample** inputPointer,
- sample** outputPointer,
+void NeuralAmpModeler::_UpdateMeters(sample **inputPointer,
+ sample **outputPointer,
const size_t nFrames,
const size_t nChansIn,
- const size_t nChansOut)
-{
+ const size_t nChansOut) {
// Right now, we didn't specify MAXNC when we initialized these, so it's 1.
const int nChansHack = 1;
- this->mInputSender.ProcessBlock(inputPointer,
- (int) nFrames,
- kCtrlTagInputMeter,
- nChansHack);
- this->mOutputSender.ProcessBlock(outputPointer,
- (int) nFrames,
- kCtrlTagOutputMeter,
- nChansHack);
+ this->mInputSender.ProcessBlock(inputPointer, (int)nFrames,
+ kCtrlTagInputMeter, nChansHack);
+ this->mOutputSender.ProcessBlock(outputPointer, (int)nFrames,
+ kCtrlTagOutputMeter, nChansHack);
}
diff --git a/NeuralAmpModeler/NeuralAmpModeler.h b/NeuralAmpModeler/NeuralAmpModeler.h
@@ -1,10 +1,10 @@
#pragma once
#include "choc_DisableAllWarnings.h"
-#include "dsp.h"
#include "choc_ReenableAllWarnings.h"
-#include "dsp/RecursiveLinearFilter.h"
+#include "dsp.h"
#include "dsp/ImpulseResponse.h"
+#include "dsp/RecursiveLinearFilter.h"
#include "IPlug_include_in_plug_hdr.h"
@@ -14,8 +14,7 @@
const int kNumPresets = 1;
-enum EParams
-{
+enum EParams {
kInputLevel = 0,
kToneBass,
kToneMid,
@@ -27,8 +26,7 @@ enum EParams
const int numKnobs = 5;
-enum ECtrlTags
-{
+enum ECtrlTags {
kCtrlTagModelName = 0,
kCtrlTagIRName,
kCtrlTagInputMeter,
@@ -37,13 +35,13 @@ enum ECtrlTags
kNumCtrlTags
};
-class NeuralAmpModeler final : public iplug::Plugin
-{
+class NeuralAmpModeler final : public iplug::Plugin {
public:
- NeuralAmpModeler(const iplug::InstanceInfo& info);
+ NeuralAmpModeler(const iplug::InstanceInfo &info);
~NeuralAmpModeler();
- void ProcessBlock(iplug::sample** inputs, iplug::sample** outputs, int nFrames) override;
+ void ProcessBlock(iplug::sample **inputs, iplug::sample **outputs,
+ int nFrames) override;
void OnReset() override {
const auto sampleRate = this->GetSampleRate();
this->mInputSender.Reset(sampleRate);
@@ -53,11 +51,11 @@ public:
this->mInputSender.TransmitData(*this);
this->mOutputSender.TransmitData(*this);
}
-
- bool SerializeState(iplug::IByteChunk& chunk) const override;
- int UnserializeState(const iplug::IByteChunk& chunk, int startPos) override;
+
+ bool SerializeState(iplug::IByteChunk &chunk) const override;
+ int UnserializeState(const iplug::IByteChunk &chunk, int startPos) override;
void OnUIOpen() override;
-
+
private:
// Allocates mInputPointers and mOutputPointers
void _AllocateIOPointers(const size_t nChans);
@@ -75,18 +73,16 @@ private:
size_t _GetBufferNumFrames() const;
// Gets a new Neural Amp Model object and stores it to mStagedNAM
// Returns a bool for whether the operation was successful.
- bool _GetNAM(const WDL_String& dspFile);
+ bool _GetNAM(const WDL_String &dspFile);
// Legacy load from directory containing "config.json" and "weights.npy"
- bool _GetNAMLegacy(const WDL_String& dspDirectory);
+ bool _GetNAMLegacy(const WDL_String &dspDirectory);
// Gets the IR and stores to mStagedIR.
// Return status code so that error messages can be relayed if
// it wasn't successful.
- dsp::wav::LoadReturnCode _GetIR(const WDL_String& irPath);
+ dsp::wav::LoadReturnCode _GetIR(const WDL_String &irPath);
// Update the message about which model is loaded.
- void _SetModelMsg(const WDL_String& dspPath);
- bool _HaveModel() const {
- return this->mNAM != nullptr;
- };
+ void _SetModelMsg(const WDL_String &dspPath);
+ bool _HaveModel() const { return this->mNAM != nullptr; };
// Prepare the input & output buffers
void _PrepareBuffers(const size_t numChannels, const size_t numFrames);
// Manage pointers
@@ -94,45 +90,39 @@ private:
// Copy the input buffer to the object, applying input level.
// :param nChansIn: In from external
// :param nChansOut: Out to the internal of the DSP routine
- void _ProcessInput(iplug::sample** inputs,
- const size_t nFrames,
- const size_t nChansIn,
- const size_t nChansOut);
+ void _ProcessInput(iplug::sample **inputs, const size_t nFrames,
+ const size_t nChansIn, const size_t nChansOut);
// Copy the output to the output buffer, applying output level.
// :param nChansIn: In from internal
// :param nChansOut: Out to external
- void _ProcessOutput(iplug::sample** inputs,
- iplug::sample** outputs,
- const size_t nFrames,
- const size_t nChansIn,
+ void _ProcessOutput(iplug::sample **inputs, iplug::sample **outputs,
+ const size_t nFrames, const size_t nChansIn,
const size_t nChansOut);
// Update the text in the IR area to say what's loaded.
- void _SetIRMsg(const WDL_String& irPath);
+ void _SetIRMsg(const WDL_String &irPath);
void _UnsetModelMsg();
void _UnsetIRMsg();
- void _UnsetMsg(const int tag, const WDL_String& msg);
+ void _UnsetMsg(const int tag, const WDL_String &msg);
// Update level meters
// Called within ProcessBlock().
// Assume _ProcessInput() and _ProcessOutput() were run immediately before.
- void _UpdateMeters(iplug::sample** inputPointer,
- iplug::sample** outputPointer,
- const size_t nFrames,
- const size_t nChansIn,
- const size_t nChansOut);
+ void _UpdateMeters(iplug::sample **inputPointer,
+ iplug::sample **outputPointer, const size_t nFrames,
+ const size_t nChansIn, const size_t nChansOut);
// Member data
-
+
// The plugin is mono inside
const size_t mNUM_INTERNAL_CHANNELS = 1;
-
+
// Input arrays to NAM
std::vector<std::vector<iplug::sample>> mInputArray;
// Output from NAM
std::vector<std::vector<iplug::sample>> mOutputArray;
// Pointer versions
- iplug::sample** mInputPointers;
- iplug::sample** mOutputPointers;
-
+ iplug::sample **mInputPointers;
+ iplug::sample **mOutputPointers;
+
// The Neural Amp Model (NAM) actually being used:
std::unique_ptr<DSP> mNAM;
// And the IR
@@ -145,24 +135,22 @@ private:
bool mFlagRemoveIR;
const WDL_String mDefaultNAMString;
const WDL_String mDefaultIRString;
-
+
// Tone stack modules
recursive_linear_filter::LowShelf mToneBass;
recursive_linear_filter::Peaking mToneMid;
recursive_linear_filter::HighShelf mToneTreble;
-
+
// Path to model's config.json or model.nam
WDL_String mNAMPath;
// Legacy
WDL_String mNAMLegacyPath;
// Path to IR (.wav file)
WDL_String mIRPath;
-
- std::unordered_map<std::string, double> mNAMParams = {
- { "Input", 0.0 },
- { "Output", 0.0 }
- };
-
+
+ std::unordered_map<std::string, double> mNAMParams = {{"Input", 0.0},
+ {"Output", 0.0}};
+
iplug::IPeakAvgSender<> mInputSender;
iplug::IPeakAvgSender<> mOutputSender;
};
diff --git a/NeuralAmpModeler/choc_DisableAllWarnings.h b/NeuralAmpModeler/choc_DisableAllWarnings.h
@@ -5,71 +5,74 @@
// ██ ██ ██ ██ ██ ██ https://github.com/Tracktion/choc
// ██████ ██ ██ ██████ ██████
//
-// CHOC is (C)2022 Tracktion Corporation, and is offered under the terms of the ISC license:
+// CHOC is (C)2022 Tracktion Corporation, and is offered under the terms of
+// the ISC license:
//
-// Permission to use, copy, modify, and/or distribute this software for any purpose with or
-// without fee is hereby granted, provided that the above copyright notice and this permission
-// notice appear in all copies. THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL
-// WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
-// AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR
-// CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
-// WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN
+// Permission to use, copy, modify, and/or distribute this software for any
+// purpose with or without fee is hereby granted, provided that the above
+// copyright notice and this permission notice appear in all copies. THE
+// SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
+// REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
+// AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL,
+// DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER
+// RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF
+// CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN
// CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
-
/*
- Sometimes you inevitably have to include some 3rd-party headers in your code, and it's
- depressing how often even the most widely-used libraries are full of poorly-written
- code that triggers all kinds of compiler warnings.
+ Sometimes you inevitably have to include some 3rd-party headers in your
+ code, and it's depressing how often even the most widely-used libraries are
+ full of poorly-written code that triggers all kinds of compiler warnings.
- Obviously you're a proper programmer who always has warnings turned up to full, and "-Werror"
- enabled, so rather than having to compromise your own standards to work around other people's
- laziness, this header provides an easy way to locally disable warnings by sandwiching your
- 3rd-party headers between includes of these two files, e.g:
+ Obviously you're a proper programmer who always has warnings turned up to
+ full, and "-Werror" enabled, so rather than having to compromise your own
+ standards to work around other people's laziness, this header provides an
+ easy way to locally disable warnings by sandwiching your 3rd-party headers
+ between includes of these two files, e.g:
- #include "choc_DisableAllWarnings.h"
#include "SloppilyWrittenButEssentialLibraryCode.h"
+ #include "choc_DisableAllWarnings.h"
#include "choc_ReenableAllWarnings.h"
*/
#if __clang__
- #pragma clang diagnostic push
- #pragma clang diagnostic ignored "-Weverything"
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Weverything"
#elif __GNUC__
- #pragma GCC diagnostic push
- #pragma GCC diagnostic ignored "-Wall"
- #pragma GCC diagnostic ignored "-Wpragmas"
- #pragma GCC diagnostic ignored "-Wextra"
- #pragma GCC diagnostic ignored "-Wshadow"
- #pragma GCC diagnostic ignored "-Wunused-parameter"
- #pragma GCC diagnostic ignored "-Wconversion"
- #pragma GCC diagnostic ignored "-Wsign-conversion"
- #pragma GCC diagnostic ignored "-Wsign-compare"
- #pragma GCC diagnostic ignored "-Wfloat-conversion"
- #pragma GCC diagnostic ignored "-Wswitch-enum"
- #pragma GCC diagnostic ignored "-Wswitch"
- #pragma GCC diagnostic ignored "-Wzero-as-null-pointer-constant"
- #pragma GCC diagnostic ignored "-Wunused-variable"
- #pragma GCC diagnostic ignored "-Wredundant-decls"
- #pragma GCC diagnostic ignored "-Wsubobject-linkage"
- #pragma GCC diagnostic ignored "-Wunused-but-set-variable"
- #pragma GCC diagnostic ignored "-Wredundant-move"
- #pragma GCC diagnostic ignored "-Wstrict-aliasing"
- #pragma GCC diagnostic ignored "-Woverloaded-virtual"
- #pragma GCC diagnostic ignored "-Wc99-extensions"
- #pragma GCC diagnostic ignored "-Wmisleading-indentation"
- #pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
- #pragma GCC diagnostic ignored "-Wimplicit-fallthrough"
- #pragma GCC diagnostic ignored "-Wcast-function-type"
- #pragma GCC diagnostic ignored "-Wunused-label"
- #pragma GCC diagnostic ignored "-Wnarrowing"
- #pragma GCC diagnostic ignored "-Wparentheses"
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wall"
+#pragma GCC diagnostic ignored "-Wpragmas"
+#pragma GCC diagnostic ignored "-Wextra"
+#pragma GCC diagnostic ignored "-Wshadow"
+#pragma GCC diagnostic ignored "-Wunused-parameter"
+#pragma GCC diagnostic ignored "-Wconversion"
+#pragma GCC diagnostic ignored "-Wsign-conversion"
+#pragma GCC diagnostic ignored "-Wsign-compare"
+#pragma GCC diagnostic ignored "-Wfloat-conversion"
+#pragma GCC diagnostic ignored "-Wswitch-enum"
+#pragma GCC diagnostic ignored "-Wswitch"
+#pragma GCC diagnostic ignored "-Wzero-as-null-pointer-constant"
+#pragma GCC diagnostic ignored "-Wunused-variable"
+#pragma GCC diagnostic ignored "-Wredundant-decls"
+#pragma GCC diagnostic ignored "-Wsubobject-linkage"
+#pragma GCC diagnostic ignored "-Wunused-but-set-variable"
+#pragma GCC diagnostic ignored "-Wredundant-move"
+#pragma GCC diagnostic ignored "-Wstrict-aliasing"
+#pragma GCC diagnostic ignored "-Woverloaded-virtual"
+#pragma GCC diagnostic ignored "-Wc99-extensions"
+#pragma GCC diagnostic ignored "-Wmisleading-indentation"
+#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
+#pragma GCC diagnostic ignored "-Wimplicit-fallthrough"
+#pragma GCC diagnostic ignored "-Wcast-function-type"
+#pragma GCC diagnostic ignored "-Wunused-label"
+#pragma GCC diagnostic ignored "-Wnarrowing"
+#pragma GCC diagnostic ignored "-Wparentheses"
- #ifndef __MINGW32__
- #pragma GCC diagnostic ignored "-Wredundant-move"
- #endif
+#ifndef __MINGW32__
+#pragma GCC diagnostic ignored "-Wredundant-move"
+#endif
#else
- #pragma warning (push, 0)
- #pragma warning (disable: 4702)
- #pragma warning (disable: 4706)
+#pragma warning(push, 0)
+#pragma warning(disable : 4702)
+#pragma warning(disable : 4706)
#endif
diff --git a/NeuralAmpModeler/choc_ReenableAllWarnings.h b/NeuralAmpModeler/choc_ReenableAllWarnings.h
@@ -5,26 +5,29 @@
// ██ ██ ██ ██ ██ ██ https://github.com/Tracktion/choc
// ██████ ██ ██ ██████ ██████
//
-// CHOC is (C)2022 Tracktion Corporation, and is offered under the terms of the ISC license:
+// CHOC is (C)2022 Tracktion Corporation, and is offered under the terms of
+// the ISC license:
//
-// Permission to use, copy, modify, and/or distribute this software for any purpose with or
-// without fee is hereby granted, provided that the above copyright notice and this permission
-// notice appear in all copies. THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL
-// WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
-// AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR
-// CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
-// WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN
+// Permission to use, copy, modify, and/or distribute this software for any
+// purpose with or without fee is hereby granted, provided that the above
+// copyright notice and this permission notice appear in all copies. THE
+// SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
+// REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
+// AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL,
+// DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER
+// RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF
+// CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN
// CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
-
-// This file re-enables the warnings that were turned off by choc_DisableAllWarnings.h
-// So when you have to include some crappy 3rd-party code which is full of warnings, you
-// can sandwich it between includes of choc_DisableAllWarnings.h and choc_ReenableAllWarnings.h
+// This file re-enables the warnings that were turned off by
+// choc_DisableAllWarnings.h So when you have to include some crappy 3rd-party
+// code which is full of warnings, you can sandwich it between includes of
+// choc_DisableAllWarnings.h and choc_ReenableAllWarnings.h
#if __clang__
- #pragma clang diagnostic pop
+#pragma clang diagnostic pop
#elif __GNUC__
- #pragma GCC diagnostic pop
+#pragma GCC diagnostic pop
#else
- #pragma warning (pop)
+#pragma warning(pop)
#endif
diff --git a/NeuralAmpModeler/dsp/HardCodedModel.h b/NeuralAmpModeler/dsp/HardCodedModel.h
@@ -9,35 +9,4064 @@
// #define PYTHON_MODEL_VERSION "0.2.0"
// const int CHANNELS = 16;
// const bool BATCHNORM = true;
-// std::vector<int> DILATIONS{ 1,2,4,8,16,32,64,128,256,512,1024,2048,1,2,4,8,16,32,64,128,256,512,1024,2048 };
-// const std::string ACTIVATION = "Tanh";
-// std::vector<float> PARAMS{ 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};
+// std::vector<int> DILATIONS{
+// 1,2,4,8,16,32,64,128,256,512,1024,2048,1,2,4,8,16,32,64,128,256,512,1024,2048
+// }; const std::string ACTIVATION = "Tanh"; std::vector<float> PARAMS{
+// 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+// };
// DR + T-Fuzz (ConvNet)
// Used on https://youtu.be/APd-GyMxjBY
-//#pragma once
+// #pragma once
//// Automatically-generated model file
-//#include <vector>
-//#define PYTHON_MODEL_VERSION "0.2.0"
-//const int CHANNELS = 16;
-//const bool BATCHNORM = true;
-//std::vector<int> DILATIONS{ 1,2,4,8,16,32,64,128,256,512,1024,2048,1,2,4,8,16,32,64,128,256,512,1024,2048 };
-//const std::string ACTIVATION = "Tanh";
-//std::vector<float> PARAMS{ 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};
+// #include <vector>
+// #define PYTHON_MODEL_VERSION "0.2.0"
+// const int CHANNELS = 16;
+// const bool BATCHNORM = true;
+// std::vector<int> DILATIONS{
+// 1,2,4,8,16,32,64,128,256,512,1024,2048,1,2,4,8,16,32,64,128,256,512,1024,2048
+// }; const std::string ACTIVATION = "Tanh"; std::vector<float> PARAMS{
+// 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+// };
// Deluxe Reverb; Vibrato channel
// (LSTM)
#pragma once
// Automatically-generated model file
-#include <vector>
#include "json.hpp"
#include "lstm.h"
+#include <vector>
#define PYTHON_MODEL_VERSION "0.4.0"
const int NUM_LAYERS = 3;
const int INPUT_SIZE = 1;
const int HIDDEN_SIZE = 24;
nlohmann::json PARAMETRIC{};
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+std::vector<float> PARAMS{
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+ -0.1654383838176727f, -0.6908612847328186f, 0.6639771461486816f,
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// My Axe FX II basss tone (Darkglass B7K into an Ampeg SVT)
// (WaveNet)
@@ -48,10 +4077,4618 @@ std::vector<float> PARAMS{ 2.0489573478698730f, 0.1933414638042450f, 0.147690847
// #include "wavenet.h"
// #define PYTHON_MODEL_VERSION "0.4.0"
// const std::vector<wavenet::LayerArrayParams> LAYER_ARRAY_PARAMS{
-// wavenet::LayerArrayParams(1, 1, 8, 16, 3, std::vector<int> {1, 2, 4, 8, 16, 32, 64, 128, 256, 512}, "Tanh", false, false),
-// wavenet::LayerArrayParams(16, 1, 1, 8, 3, std::vector<int> {1, 2, 4, 8, 16, 32, 64, 128, 256, 512}, "Tanh", false, true)
+// wavenet::LayerArrayParams(1, 1, 8, 16, 3, std::vector<int> {1, 2, 4, 8, 16,
+// 32, 64, 128, 256, 512}, "Tanh", false, false),
+// wavenet::LayerArrayParams(16, 1, 1, 8, 3, std::vector<int> {1, 2, 4, 8, 16,
+// 32, 64, 128, 256, 512}, "Tanh", false, true)
// };
// const float HEAD_SCALE = 1.0;
// const bool WITH_HEAD = false;
// nlohmann::json PARAMETRIC {};
-// std::vector<float> PARAMS{0.3835485577583313f, 0.5359688997268677f, -0.9955689311027527f, -0.7553601264953613f, -0.1494733691215515f, 1.2345675230026245f, -0.1786766350269318f, 1.0769165754318237f, -0.9440643191337585f, 1.1597353219985962f, -1.2624912261962891f, -0.4461484253406525f, -0.6159268617630005f, -1.2956296205520630f, -0.8408089280128479f, 1.2146446704864502f, 0.1296682208776474f, -0.0277807340025902f, -0.4071600437164307f, 0.0822563767433167f, 0.0648131594061852f, 0.0528585948050022f, -0.1753178089857101f, 0.0956070274114609f, 0.0528422854840755f, -0.1341764926910400f, 0.1146047562360764f, -0.0721464604139328f, -0.1895050406455994f, -0.0151604283601046f, 0.0599605888128281f, 0.2469886243343353f, -0.1048045530915260f, -0.1958756148815155f, -0.1983633339405060f, -0.0829553380608559f, 0.1319145262241364f, 0.2669599950313568f, 0.0711239054799080f, -0.0220919530838728f, -0.0615119673311710f, 0.0306550096720457f, 0.2941007018089294f, -0.0264443457126617f, -0.1558667570352554f, 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-0.1200385093688965f, 0.1161482706665993f, -0.0993445664644241f, 0.1035206690430641f, 0.2043389976024628f, 0.0066380770877004f, 0.1182640567421913f, 0.1494064182043076f, 0.3085750341415405f, 0.2310723662376404f, -0.1379791349172592f, -0.1877056658267975f, 0.1587389260530472f, 0.1117305234074593f, -0.1185799688100815f, 0.1709762960672379f, 0.0457643084228039f, -0.2255200892686844f, -0.1225367113947868f, -0.1887516528367996f, -0.0411749407649040f, -0.1572306156158447f, -0.0373850725591183f, -0.0516659021377563f, -0.0028457029256970f, 0.1696260273456573f, 0.1106372922658920f, -0.2047734856605530f, 0.0053880028426647f, -0.1328373700380325f, -0.0649224147200584f, -0.0101982131600380f, 0.0770838484168053f, -0.0951460748910904f, -0.2241573780775070f, -0.1490227133035660f, -0.0707198753952980f, -0.2232327610254288f, 0.0298546496778727f, -0.1661320179700851f, -0.0932367295026779f, 0.1693368554115295f, 0.1590259373188019f, 0.0193731356412172f, -0.0657057464122772f, 0.1089156717061996f, 0.1032359302043915f, 0.1619964241981506f, 0.0000137926263051f, 0.0823598131537437f, -0.0912312939763069f, 0.1062601804733276f, 0.0756709203124046f, -0.0121430503204465f, 0.0763056576251984f, -0.0054127606563270f, -0.3388555645942688f, -0.0430928319692612f, -0.0541323386132717f, 0.0204487442970276f, -0.2136927396059036f, 0.0257074441760778f, -0.2725523710250854f, 0.0085609285160899f, -0.0743933543562889f, 0.0447168461978436f, 0.1216988414525986f, -0.0936483293771744f, -0.0364801958203316f, -0.1163876578211784f, -0.1144527718424797f, 0.0996754318475723f, 0.1016776189208031f, -0.0802735090255737f, 0.0420583747327328f, 0.1409213691949844f, 0.1143178790807724f, 0.1809004843235016f, 0.1841068416833878f, -0.0173659548163414f, -0.1322118341922760f, -0.1313337981700897f, 0.0959200412034988f, 0.2102988213300705f, 0.2287792414426804f, 0.3155713379383087f, 0.1476121395826340f, 0.2918182015419006f, -0.1163526400923729f, 0.1988018453121185f, 0.1008848473429680f, -0.2047589570283890f, -0.0620911046862602f, 0.1552779227495193f, -0.1100812256336212f, -0.1536879539489746f, 1.0569953918457031f, 0.3136036694049835f, 0.0432358235120773f, -0.0242086052894592f, 0.8666443824768066f, 0.2703282535076141f, -0.1575263887643814f, -0.6900277733802795f, 0.3240924775600433f, -0.2684019505977631f, 0.1021989881992340f, -0.1503699272871017f, 0.2512529194355011f, 0.2426625192165375f, 0.1820336878299713f, -0.0936641991138458f, 0.2864372432231903f, -0.0844886600971222f, 0.2345096170902252f, 0.1671409904956818f, -0.2909255027770996f, -0.2231021076440811f, -0.0285452902317047f, -0.2902416884899139f, -0.0911809206008911f, 0.1914344131946564f, 0.3196655809879303f, -0.0279632806777954f, -0.0846583843231201f, -0.2666132152080536f, 0.1073178350925446f, 0.0505908429622650f, 0.1508843600749969f, -0.2990425527095795f, 0.0172648727893829f, -0.1562631875276566f, -0.1995172798633575f, 0.1757102906703949f, -0.2895315289497375f, -0.2112935334444046f, 0.2603401839733124f, -0.2312087565660477f, 0.2381831705570221f, -0.1290394067764282f, -0.2417178153991699f, -0.0228334367275238f, -0.2175087481737137f, 0.0927365422248840f, 0.2515943944454193f, -0.2678905427455902f, -0.2392645329236984f, -0.0614089965820312f, 0.0116340816020966f, 0.3061031401157379f, 0.2777076661586761f, -0.1913124620914459f, 0.2306869328022003f, 0.2046033442020416f, -0.2708279490470886f, 0.2188521325588226f, 0.3408154547214508f, -0.0827629566192627f, 0.3052035272121429f, 0.3354517519474030f, 0.0888060927391052f, 0.0076411962509155f, 0.2934277951717377f, 0.2444260418415070f, 0.3364352881908417f, -0.2267208397388458f, 0.1205825805664062f, 0.2158147394657135f, -0.2301437556743622f, 0.0601432025432587f, -0.1920311152935028f, -0.2548098862171173f, 0.3473303616046906f, -0.2866051793098450f, -0.3235993683338165f, 0.2944277822971344f, 0.0385968759655952f, 0.0506347008049488f, 0.0809904187917709f, -0.0053636352531612f, -0.0067958584986627f, -0.0324983447790146f, 0.0305824782699347f, -0.1963013857603073f, -0.2978549301624298f, 1.0000000000000000f};
+// std::vector<float> PARAMS{0.3835485577583313f, 0.5359688997268677f,
+// -0.9955689311027527f, -0.7553601264953613f,
+// -0.1494733691215515f, 1.2345675230026245f,
+// -0.1786766350269318f, 1.0769165754318237f,
+// -0.9440643191337585f, 1.1597353219985962f, -1.2624912261962891f,
+// -0.4461484253406525f, -0.6159268617630005f, -1.2956296205520630f,
+// -0.8408089280128479f, 1.2146446704864502f, 0.1296682208776474f,
+// -0.0277807340025902f, -0.4071600437164307f, 0.0822563767433167f,
+// 0.0648131594061852f, 0.0528585948050022f, -0.1753178089857101f,
+// 0.0956070274114609f, 0.0528422854840755f, -0.1341764926910400f,
+// 0.1146047562360764f, -0.0721464604139328f, -0.1895050406455994f,
+// -0.0151604283601046f, 0.0599605888128281f, 0.2469886243343353f,
+// -0.1048045530915260f, -0.1958756148815155f, -0.1983633339405060f,
+// -0.0829553380608559f, 0.1319145262241364f, 0.2669599950313568f,
+// 0.0711239054799080f, -0.0220919530838728f, -0.0615119673311710f,
+// 0.0306550096720457f, 0.2941007018089294f, -0.0264443457126617f,
+// -0.1558667570352554f, -0.2699396610260010f, -0.0466555096209049f,
+// 0.0870699733495712f, 0.0594101957976818f, -0.1440277993679047f,
+// 0.0823401063680649f, 0.2327432185411453f, -0.0799996107816696f,
+// 0.0160392522811890f, 0.1652154475450516f, -0.2258044481277466f,
+// 0.0234798286110163f, -0.0188831593841314f, -0.2255857735872269f,
+// -0.0616229213774204f, 0.1857846230268478f, 0.1055725663900375f,
+// -0.1839340925216675f, -0.2114940434694290f, 0.1212260797619820f,
+// -0.0994124040007591f, -0.3088673949241638f, 0.0806258544325829f,
+// 0.1310831457376480f, 0.0919791162014008f, -0.1434854567050934f,
+// -0.0847446992993355f, 0.1181433200836182f, 0.0780468732118607f,
+// 0.0893510431051254f, 0.1765092611312866f, 0.0160327851772308f,
+// -0.1390814781188965f, 0.0962059348821640f, -0.0769020691514015f,
+// -0.0928046256303787f, 0.0546453483402729f, 0.0201090965420008f,
+// -0.1635543256998062f, 0.1999717652797699f, 0.0061834929510951f,
+// 0.0026925033889711f, -0.1427928805351257f, -0.0062427846714854f,
+// -0.0561937093734741f, 0.2791958153247833f, 0.1182280033826828f,
+// 0.0917589813470840f, -0.1214380413293839f, -0.1693758815526962f,
+// -0.1247381791472435f, 0.1642871201038361f, -0.0018485406180844f,
+// -0.1607224196195602f, -0.0311561990529299f, 0.0925975888967514f,
+// 0.0663369596004486f, -0.0112689128145576f, -0.0697173625230789f,
+// -0.1696640849113464f, 0.0672958195209503f, -0.1381272375583649f,
+// -0.1396837234497070f, 0.0765482559800148f, 0.0808947235345840f,
+// -0.0396494530141354f, -0.0828066915273666f, -0.7091677784919739f,
+// -0.0946900472044945f, 2.0658030509948730f, -0.4384669661521912f,
+// -0.3920795619487762f, 0.7910001277923584f, 0.4106825292110443f,
+// 0.4967099726200104f, -0.7356845736503601f, 0.3281491696834564f,
+// 0.3102262020111084f, -0.6735978722572327f, 0.3348606228828430f,
+// 0.3791383206844330f, -0.9260874986648560f, -1.0537509918212891f,
+// -1.1244480609893799f, 0.8468663096427917f, 0.6440409421920776f,
+// 0.3873966932296753f, -1.9147459268569946f, -0.4581663012504578f,
+// -0.3685331046581268f, 0.8802012801170349f, 0.4796718657016754f,
+// 0.1122903153300285f, -1.7525925636291504f, -0.4159922301769257f,
+// -0.1234852448105812f, 1.5773060321807861f, 0.8606653809547424f,
+// 0.7369998693466187f, -1.1790728569030762f, 0.5124739408493042f,
+// 0.7945433855056763f, -0.8411487340927124f, 0.2201288938522339f,
+// 0.1891912668943405f, -0.8937372565269470f, 0.3767694830894470f,
+// 0.4880002737045288f, -0.8206704258918762f, 0.6735700964927673f,
+// 0.4418495893478394f, -0.9129898548126221f, -0.9786708354949951f,
+// -0.7418314814567566f, 1.7252787351608276f, 0.1879804581403732f,
+// -0.0835965946316719f, -0.5365368127822876f, -0.0035692155361176f,
+// -0.0207565706223249f, -0.1090660095214844f, -0.1887642443180084f,
+// 0.0419892296195030f, -0.0149951437488198f, -0.1276530325412750f,
+// 0.1249947845935822f, 0.0467409342527390f, -0.0010692375944927f,
+// 0.0350797064602375f, 0.0079275807365775f, 0.2335309833288193f,
+// 0.0681525543332100f, -0.1682576239109039f, -0.1190695464611053f,
+// -0.1409078985452652f, 0.3048306107521057f, 0.1046163216233253f,
+// 0.1147358641028404f, -0.0988144427537918f, -0.1387477517127991f,
+// 0.1157697141170502f, 0.3484512865543365f, 0.1520982384681702f,
+// -0.1596708893775940f, -0.2265224307775497f, -0.0285864602774382f,
+// 0.0630714297294617f, 0.0554641634225845f, -0.1164911910891533f,
+// -0.1445630937814713f, 0.0242413394153118f, -0.2101331949234009f,
+// 0.0522399395704269f, 0.0226299557834864f, -0.1375105679035187f,
+// -0.0095624877139926f, 0.2255221009254456f, -0.2520672380924225f,
+// -0.1178971007466316f, 0.0738684087991714f, 0.3418537676334381f,
+// 0.0054704467765987f, -0.1624043285846710f, 0.4573345780372620f,
+// 0.0782751739025116f, -0.4820468723773956f, 0.1850459575653076f,
+// 0.0791331678628922f, -0.2517721056938171f, -0.2344481796026230f,
+// -0.0532403141260147f, 0.1076360046863556f, -0.2888205349445343f,
+// 0.0551327988505363f, 0.0989247113466263f, -0.2539763152599335f,
+// 0.0646820813417435f, 0.2702504396438599f, 0.2781206071376801f,
+// -0.0221281386911869f, -0.1543378531932831f, -0.5210901498794556f,
+// -0.1635621190071106f, 0.3167267143726349f, 0.2340520322322845f,
+// 0.0842395424842834f, -0.1078023761510849f, -0.4002801775932312f,
+// 0.0054281568154693f, 0.4456237256526947f, 0.2772706151008606f,
+// 0.1789450794458389f, -0.4123204946517944f, -0.3515256047248840f,
+// -0.0506022498011589f, 0.3057927489280701f, -0.1273935884237289f,
+// -0.1181593090295792f, 0.2317020446062088f, -0.1301273554563522f,
+// -0.1996995657682419f, 0.3121384978294373f, -0.3685532808303833f,
+// -0.0764643028378487f, 0.2080480307340622f, -0.3437846302986145f,
+// -0.0673226863145828f, 0.3604329526424408f, 0.3712747097015381f,
+// 0.0774449110031128f, -0.3520209491252899f, -0.3603218495845795f,
+// 0.0832555964589119f, 0.6977984905242920f, -0.2196862697601318f,
+// -0.2348747402429581f, 0.2560168206691742f, 0.2106485962867737f,
+// 0.2816737890243530f, -0.1318713128566742f, 0.0736185982823372f,
+// 0.1137855201959610f, -0.1177031621336937f, 0.2515149712562561f,
+// 0.1938474327325821f, -0.3113115131855011f, -0.3095616698265076f,
+// -0.4169439673423767f, 0.2904133498668671f, 0.2463551163673401f,
+// 0.0501491986215115f, -0.3931232094764709f, -0.2487120181322098f,
+// -0.1934022754430771f, 0.2598019540309906f, 0.2164300680160522f,
+// -0.0674264281988144f, -0.7437754869461060f, -0.0950855463743210f,
+// -0.0835002362728119f, 0.5874764919281006f, 0.1597914695739746f,
+// 0.2644749581813812f, -0.3180186152458191f, 0.1573039144277573f,
+// 0.1264152675867081f, -0.1563924252986908f, 0.1615686714649200f,
+// 0.1307362318038940f, -0.1984806805849075f, 0.0724882185459137f,
+// 0.2828727960586548f, -0.3276949822902679f, 0.2351306229829788f,
+// 0.1360947787761688f, -0.3430641591548920f, -0.3350097835063934f,
+// -0.3037174940109253f, 0.5648471117019653f, -1.1206485033035278f,
+// -0.2710267007350922f, 2.1717724800109863f, -0.5460085868835449f,
+// -0.4047183990478516f, 0.8527598381042480f, 0.5444395542144775f,
+// 0.4771609008312225f, -0.8826536536216736f, 0.5367618799209595f,
+// 0.5158080458641052f, -0.7613511681556702f, 0.6672366261482239f,
+// 0.5175638198852539f, -0.9383198618888855f, -1.0655921697616577f,
+// -0.7533731460571289f, 1.1883540153503418f, 1.2006424665451050f,
+// 0.4698196053504944f, -1.7262845039367676f, -0.6137087345123291f,
+// -0.4268763661384583f, 1.0405226945877075f, 1.1856163740158081f,
+// 0.2001822590827942f, -1.9437428712844849f, -1.1729369163513184f,
+// -0.2403890788555145f, 1.6573206186294556f, 0.8778624534606934f,
+// 0.6750581264495850f, -1.1270393133163452f, 0.9290090203285217f,
+// 0.7223676443099976f, -0.8965227603912354f, 0.5319220423698425f,
+// 0.3813888132572174f, -0.7079824209213257f, 0.8585599660873413f,
+// 0.4507257342338562f, -0.8998194932937622f, 0.9452975392341614f,
+// 0.6439204216003418f, -1.2247362136840820f, -1.4261493682861328f,
+// -0.6812862157821655f, 1.9406217336654663f, 0.2594836950302124f,
+// 0.0245255641639233f, 0.0694512948393822f, 0.2374039590358734f,
+// -0.0970196947455406f, 0.0086472555994987f, -0.2896052300930023f,
+// 0.0979810580611229f, -0.0346520729362965f, -0.3170170187950134f,
+// -0.0647750645875931f, 0.1811313331127167f, -0.1145716980099678f,
+// 0.1951909661293030f, 0.1555383056402206f, 0.0605108663439751f,
+// -0.2593950033187866f, -0.0645651742815971f, -0.3953244686126709f,
+// 0.1167314201593399f, -0.1783294677734375f, 0.1315362453460693f,
+// -0.2050934582948685f, -0.1311579197645187f, -0.2267016023397446f,
+// 0.0759766027331352f, 0.0126863503828645f, 0.4028666913509369f,
+// 0.1175964921712875f, -0.0060608885250986f, -0.1525719612836838f,
+// 0.2440186142921448f, 0.0883673056960106f, -0.0427154265344143f,
+// 0.1870790868997574f, 0.1568736881017685f, -0.2176408469676971f,
+// 0.1023798510432243f, 0.0736447498202324f, -0.2303591668605804f,
+// -0.0083245383575559f, -0.0287871621549129f, -0.3173414766788483f,
+// 0.1805833578109741f, 0.1410282105207443f, 0.2826967835426331f,
+// -0.1452051848173141f, 0.1947334855794907f, -0.0943694561719894f,
+// 0.0628618225455284f, 1.3020647764205933f, -0.0108456574380398f,
+// -0.1888330131769180f, 0.1634834259748459f, 0.2943543791770935f,
+// 0.3913155198097229f, -0.3518658876419067f, 0.2196010053157806f,
+// 0.1652868986129761f, -0.2876240313053131f, 0.2990699112415314f,
+// 0.2923117578029633f, -0.4344880580902100f, -0.4115230739116669f,
+// -0.5841859579086304f, 0.3508805632591248f, 0.3951162397861481f,
+// 0.3552975058555603f, -1.0393805503845215f, -0.2683453857898712f,
+// -0.2928456664085388f, 0.4152113497257233f, 0.3653745949268341f,
+// 0.0290005262941122f, -1.0046013593673706f, -0.3722553253173828f,
+// -0.3074940443038940f, 0.7989940047264099f, 0.1711410284042358f,
+// 0.4647922217845917f, -0.3451218307018280f, 0.2167951762676239f,
+// 0.2726981639862061f, -0.3769807219505310f, 0.1679786890745163f,
+// 0.1139769777655602f, -0.1764669269323349f, 0.0658018514513969f,
+// 0.1811755001544952f, -0.4859268367290497f, 0.2031539976596832f,
+// 0.4523976445198059f, -0.5353071689605713f, -0.4658588171005249f,
+// -0.5454562306404114f, 0.9503879547119141f, -0.2826316058635712f,
+// -0.2138970196247101f, 0.3962569832801819f, -0.0470762327313423f,
+// 0.0907242894172668f, 0.1944733709096909f, 0.0459418445825577f,
+// 0.1855217218399048f, -0.1097331419587135f, 0.1967014670372009f,
+// -0.0594666860997677f, -0.1589276939630508f, -0.0128874126821756f,
+// -0.0035411673597991f, -0.0975538566708565f, -0.2679572403430939f,
+// -0.0353154800832272f, 0.1953826099634171f, 0.2787609100341797f,
+// 0.0098278522491455f, -0.3107512593269348f, -0.1999863386154175f,
+// -0.0100540863350034f, 0.2618116438388824f, 0.3237391710281372f,
+// 0.0593304224312305f, -0.1853213608264923f, -0.3643108904361725f,
+// -0.2120517641305923f, 0.2486929446458817f, 0.0959474146366119f,
+// 0.1556572467088699f, -0.2327238023281097f, 0.0696782618761063f,
+// -0.0519720539450645f, -0.0453898832201958f, 0.0997926220297813f,
+// 0.1565207093954086f, -0.0319520086050034f, 0.2284449189901352f,
+// 0.0734813883900642f, -0.1686859875917435f, 0.1207970306277275f,
+// 0.0867816060781479f, -0.0630694478750229f, -0.3239029645919800f,
+// 0.0230684969574213f, 0.1756431013345718f, -0.1095235422253609f,
+// 0.0606760419905186f, 0.4085251688957214f, 0.1138619631528854f,
+// -0.0959931984543800f, 0.1258117258548737f, 0.0815782696008682f,
+// 0.0416563488543034f, 0.0887087658047676f, -0.0623348914086819f,
+// 0.0050907428376377f, 0.0362667739391327f, -0.0395419895648956f,
+// 0.0017235354753211f, -0.0962268486618996f, 0.0778556391596794f,
+// -0.0356663838028908f, -0.0476076304912567f, 0.1106588542461395f,
+// 0.0217915121465921f, -0.2232363820075989f, -0.0039226259104908f,
+// 0.1237085685133934f, 0.0279322508722544f, 0.0713241621851921f,
+// -0.1292881369590759f, -0.1565169245004654f, -0.1262233406305313f,
+// -0.0027695342432708f, 0.0876644626259804f, 0.1504435688257217f,
+// -0.0694153010845184f, -0.0488925240933895f, -0.0526544414460659f,
+// 0.1271196752786636f, 0.1342358589172363f, -0.0905986875295639f,
+// -0.1577730625867844f, -0.1343314051628113f, 0.0126047320663929f,
+// -0.0763369053602219f, -0.1325558274984360f, -0.0407603122293949f,
+// -0.0147403888404369f, -0.1304033398628235f, -0.0044838362373412f,
+// 0.0019905713852495f, 0.0712297782301903f, -0.1693610548973083f,
+// 0.1066210195422173f, 0.0453766323626041f, -0.0961173102259636f,
+// -0.0388633422553539f, 0.2943672835826874f, -0.0182528980076313f,
+// -0.1504843980073929f, -0.0075319358147681f, 0.0106137730181217f,
+// 0.0132826017215848f, -0.1650476753711700f, 0.0995308980345726f,
+// -0.0349338501691818f, -0.0398641377687454f, -0.1677098274230957f,
+// -0.1328675597906113f, 0.0486261472105980f, 0.1474831402301788f,
+// 0.0934888795018196f, -0.2167856693267822f, 0.0085571501404047f,
+// -0.0224576033651829f, 0.1212888434529305f, 0.2867642343044281f,
+// 0.0816287845373154f, -0.0261730570346117f, -0.0876617059111595f,
+// -0.0588066950440407f, 0.0387821495532990f, 0.1540341228246689f,
+// 0.1151980385184288f, -0.1888328045606613f, 0.0057006855495274f,
+// 0.0431387685239315f, -0.0101277641952038f, 0.0482725873589516f,
+// -0.1345191299915314f, -0.2818538248538971f, 0.1672190874814987f,
+// -0.0186445750296116f, -0.2203189432621002f, 0.1741350591182709f,
+// 0.0501426234841347f, -0.0265687089413404f, -0.1156954318284988f,
+// -0.0397054441273212f, 0.0023603737354279f, -0.2110000401735306f,
+// 0.1600479185581207f, 0.2712180018424988f, 0.0283397603780031f,
+// -0.1106328442692757f, 0.1585426628589630f, 0.1607926636934280f,
+// 0.1067421659827232f, -0.1628948450088501f, -0.0288927126675844f,
+// -0.1232138872146606f, 0.1087989658117294f, -0.0420227982103825f,
+// -0.0883590057492256f, 0.0090882303193212f, -0.1483080983161926f,
+// -0.1190334632992744f, 0.0076286005787551f, 0.0746160522103310f,
+// -0.1039879396557808f, -0.0355579145252705f, -0.1026227325201035f,
+// 0.0633763968944550f, 0.1717687249183655f, 0.1379437148571014f,
+// -0.0216830801218748f, -0.0719579607248306f, -0.0251045767217875f,
+// -0.0238685589283705f, 0.2921740412712097f, 0.0907428637146950f,
+// -0.1336200833320618f, -0.0969421193003654f, -0.0482653304934502f,
+// 0.1384911388158798f, -0.0455801934003830f, -0.1043045222759247f,
+// -0.0344574116170406f, 0.0608370304107666f, 0.0768014043569565f,
+// 0.0347110740840435f, -0.0292194597423077f, 0.0966293439269066f,
+// -0.0441352240741253f, -0.1196748465299606f, -0.1919686794281006f,
+// -0.0959874093532562f, 0.2464220970869064f, -0.2049008607864380f,
+// -0.1100302711129189f, -0.3535399436950684f, 0.0290851686149836f,
+// 0.0407179035246372f, 0.1469351053237915f, -0.0978331416845322f,
+// -0.0213740020990372f, -0.1170124411582947f, -0.0503737479448318f,
+// -0.0542001612484455f, -0.0707536786794662f, 0.1150614693760872f,
+// -0.2197795361280441f, -0.0920485556125641f, -0.0206799861043692f,
+// 0.2041277587413788f, 0.0917055010795593f, -0.0198795646429062f,
+// 0.0712767094373703f, 0.2390198260545731f, -0.0204122383147478f,
+// 0.2417009472846985f, -0.1296899616718292f, 0.0424955710768700f,
+// 0.1334753036499023f, 0.2225069105625153f, 0.0785798206925392f,
+// -0.0013251088093966f, -0.0575324483215809f, -0.1486231088638306f,
+// -0.1609854400157928f, 0.0372985415160656f, 0.0243615731596947f,
+// -0.1023856624960899f, 0.1200772076845169f, -0.0400745756924152f,
+// -0.1281910985708237f, 0.0885516405105591f, -0.0558497309684753f,
+// -0.0141376061365008f, -0.0788387134671211f, -0.0310146380215883f,
+// -0.1453843563795090f, 0.1056148186326027f, 0.1186396554112434f,
+// 0.0310862772166729f, -0.3638842701911926f, 0.5460391640663147f,
+// 0.3045035004615784f, -0.3203968107700348f, 0.0275539811700583f,
+// 0.1579933464527130f, -0.0319667905569077f, -0.1176021248102188f,
+// -0.2175629287958145f, 0.2764100432395935f, -0.2294190078973770f,
+// -0.0366404615342617f, 0.1794108450412750f, -0.1753805130720139f,
+// -0.0152878724038601f, 0.0878001302480698f, 0.1474531292915344f,
+// 0.0180700328201056f, -0.2647612094879150f, -0.2186463326215744f,
+// 0.0440450906753540f, 0.4345470964908600f, 0.2392152100801468f,
+// 0.0767188146710396f, -0.2611866295337677f, -0.4010565280914307f,
+// -0.2487067878246307f, 0.5535606145858765f, 0.1945858299732208f,
+// 0.1117445975542068f, -0.3153550624847412f, -0.0605762340128422f,
+// 0.0121782366186380f, 0.3770616948604584f, -0.2237350642681122f,
+// -0.1153680309653282f, 0.1118452027440071f, -0.1973316967487335f,
+// -0.0230757556855679f, 0.2907045781612396f, -0.2510453462600708f,
+// 0.0005231340182945f, 0.1270689815282822f, -0.1643870770931244f,
+// 0.0269636865705252f, 0.2062817215919495f, 0.1634417176246643f,
+// -0.0393679402768612f, -0.3811047971248627f, -0.3179153800010681f,
+// -0.2177615463733673f, 0.1017280668020248f, -0.2174061536788940f,
+// -0.1082449406385422f, 0.1400422751903534f, 0.2399765402078629f,
+// -0.0464170686900616f, -0.0612579174339771f, 0.2353603541851044f,
+// 0.0866287350654602f, -0.2092525064945221f, 0.1209143698215485f,
+// -0.0409992448985577f, -0.2294186800718307f, -0.1686474233865738f,
+// 0.0979322716593742f, 0.2173075675964355f, 0.2806709110736847f,
+// 0.1269717216491699f, -0.1181488409638405f, -0.0332166589796543f,
+// -0.0651700422167778f, 0.0193661842495203f, 0.2815992534160614f,
+// 0.1724808216094971f, -0.2090763598680496f, -0.0973314344882965f,
+// -0.0133622689172626f, -0.0163878314197063f, 0.1412088274955750f,
+// 0.1396625041961670f, -0.2183370590209961f, 0.0929850339889526f,
+// 0.0367710031569004f, -0.2549623548984528f, 0.1834830939769745f,
+// 0.0680209994316101f, -0.0412221550941467f, 0.0503272451460361f,
+// 0.1488639265298843f, -0.2060079574584961f, 0.3009979724884033f,
+// -0.1269034743309021f, -0.2408943027257919f, -0.1965362429618835f,
+// -0.0852384269237518f, 0.0529016554355621f, 0.0053336909040809f,
+// -0.0914399623870850f, -0.0435058549046516f, -0.1218552887439728f,
+// 0.0116267930716276f, 0.1026470288634300f, 0.0098517388105392f,
+// -0.0038907711859792f, 0.0822582393884659f, 0.0653708428144455f,
+// -0.0306853558868170f, -0.0238057281821966f, -0.0330817773938179f,
+// 0.0033014309592545f, -0.0547053329646587f, -0.0010501117212698f,
+// 0.3960256278514862f, -0.4785180687904358f, 1.4786890745162964f,
+// -0.8028815984725952f,
+// -0.1977266669273376f, 1.0339705944061279f, 1.7679344415664673f,
+// -0.6415666937828064f, 0.4047720432281494f, 0.2296413332223892f,
+// -0.4389397203922272f, -0.1906062662601471f, 0.3005854189395905f,
+// -0.6683999896049500f, 0.0386615507304668f, 0.5658690333366394f,
+// 0.0063076764345169f, 0.1999761611223221f, -0.0512533299624920f,
+// 0.1541350185871124f, 0.1804767102003098f, -0.1102965325117111f,
+// 0.6277126073837280f, 0.0558543317019939f, -0.0837401002645493f,
+// -0.0502322427928448f, 0.0215842742472887f, -0.0798394009470940f,
+// 0.0523882210254669f, 0.0285793803632259f, 0.2517132163047791f,
+// -0.0675152540206909f, -0.0705629661679268f, -0.1179531142115593f,
+// -0.2212570011615753f, 0.0237996242940426f, 0.0072028115391731f,
+// -0.0400596708059311f, -0.1241938993334770f, -0.1137971803545952f,
+// 0.1113184913992882f, 0.1830842941999435f, -0.0645998418331146f,
+// 0.0975617393851280f, 0.0059587680734694f, -0.1140224486589432f,
+// -0.0109576340764761f, 0.2991776168346405f, -0.0693376958370209f,
+// 0.1521652936935425f, 0.1948499381542206f, 0.2599588632583618f,
+// 0.0874628573656082f, -0.2737416923046112f, -0.3340214192867279f,
+// -0.1726134270429611f, -0.0314203910529613f, -0.3260804414749146f,
+// 0.2095710337162018f, -0.1899956464767456f, 0.1971395462751389f,
+// 0.0971470996737480f, 0.1734993606805801f, -0.0283534917980433f,
+// 0.0501609183847904f, -0.3068552315235138f, -0.0643936842679977f,
+// -0.2591196000576019f, 0.1827388703823090f, 0.1789114773273468f,
+// 0.0954087972640991f, 0.1115753799676895f, -0.1555776298046112f,
+// 0.0358403027057648f, -0.0596120841801167f, -0.1807097941637039f,
+// 0.0496819168329239f, 0.1203456744551659f, -0.1932424753904343f,
+// -0.2510500550270081f, -0.1794597059488297f, -0.3276180624961853f,
+// -0.1699865758419037f, 0.0663877725601196f, 0.3538720309734344f,
+// 0.4105246961116791f, 0.0115184728056192f, -0.0533995367586613f,
+// 0.2809431850910187f, 0.2379382103681564f, -0.1479794830083847f,
+// 0.0353702493011951f, 0.0751368999481201f, -0.0185358021408319f,
+// -0.3332819044589996f, -0.0402830317616463f, -0.2270411103963852f,
+// -0.0804551839828491f, -0.0977378487586975f, -0.0010506383841857f,
+// 0.3838693797588348f, 0.3678500950336456f, 0.5751628279685974f,
+// 0.1028663441538811f, 0.1935140788555145f, -0.0938084647059441f,
+// -0.0918707475066185f, -0.0771241560578346f, 0.0078038820065558f,
+// -0.1016881093382835f, -0.0604769587516785f, 0.0148315243422985f,
+// 0.1201854795217514f, 0.1591582596302032f, 0.2462825030088425f,
+// 0.1988690197467804f, -0.0947201177477837f, -0.2519393861293793f,
+// 0.4097942113876343f, 0.1850043386220932f, 0.0047847102396190f,
+// -0.2801516354084015f, -0.1657818406820297f, 0.1707142144441605f,
+// 0.1297177523374557f, -0.2238232493400574f, 0.3385968208312988f,
+// -0.2450539320707321f, 0.2673604786396027f, 0.0547685921192169f,
+// -0.0798216909170151f, -0.1318850964307785f, 0.1408963501453400f,
+// -0.0468843132257462f, 0.0827577561140060f, 0.2266398966312408f,
+// -0.0357681773602962f, -0.4199861884117126f, 0.1977754980325699f,
+// -0.2603513002395630f, 0.0463481582701206f, 0.0403754189610481f,
+// 0.0562467947602272f, -0.1506491899490356f, -0.1702726036310196f,
+// -0.0011086817830801f, -0.5383455157279968f, -0.1696404367685318f,
+// 0.5151602625846863f, -0.3070081472396851f, -1.3501046895980835f,
+// -0.1502226740121841f, -0.2496132403612137f, -0.3295072615146637f,
+// 0.1532854735851288f, 0.1562047004699707f, 0.0365388654172421f,
+// -0.1060307323932648f, 0.1278036683797836f, -0.0081796143203974f,
+// -0.1448884457349777f, -0.0154520515352488f, 0.2813165485858917f,
+// -0.3437614142894745f, -0.7582661509513855f,
+// 0.2514113187789917f, 1.2704509496688843f, -0.2292601913213730f,
+// 0.0626041591167450f, 0.3712230026721954f, 0.1092905253171921f,
+// 0.0605583563446999f, 0.1895946860313416f, 0.0668536573648453f,
+// -0.2511956095695496f, 0.1396786421537399f, 0.1793829947710037f,
+// 0.3100098073482513f, -0.1142855435609818f, 0.1815089136362076f,
+// -0.5644747614860535f, -0.3747499883174896f, -0.5951842665672302f,
+// -0.2368815839290619f, 0.0338751338422298f, 0.0293026044964790f,
+// -0.2369634062051773f, 0.0759808123111725f, -0.1194062754511833f,
+// 0.0419737659394741f, 0.1978740692138672f, 0.4509996175765991f,
+// 0.0651164278388023f, -0.0857935622334480f, 0.0638262331485748f,
+// 0.0490558557212353f, 0.1612573564052582f, -0.1332191079854965f,
+// -0.1583188474178314f, -0.0214333273470402f, -0.1135644689202309f,
+// -0.1386854052543640f, -0.1246583238244057f, -0.1744605898857117f,
+// -0.2063066512346268f, 0.0887999758124352f, -0.1249957308173180f,
+// -0.1814885586500168f, -0.0057866359129548f, 0.0063533703796566f,
+// 0.1182514950633049f, 0.0234791375696659f, 0.1125493273139000f,
+// -0.0704846233129501f, 0.2126097828149796f, 0.2231549620628357f,
+// 0.1203070953488350f, -0.1051856577396393f, 0.1217390447854996f,
+// 0.0134168546646833f, 0.3279149830341339f, -0.1392098665237427f,
+// -0.1235949024558067f, 0.0480157062411308f, -0.0264936089515686f,
+// -0.1907872557640076f, 0.1023858636617661f, 0.0883304551243782f,
+// -0.3108767569065094f, 0.1893735527992249f, 0.2802312374114990f,
+// 0.1575639247894287f, -0.0109246252104640f, -0.0133890025317669f,
+// 0.0535348318517208f, 0.0111949266865849f, -0.1243411749601364f,
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+// -0.1721346527338028f, 0.2249182313680649f, -0.0628623291850090f,
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+// 0.0297248531132936f, 0.0243430119007826f, -0.1538285166025162f,
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+// 0.0076348725706339f, -0.0717770382761955f, -0.1240352764725685f,
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+// 0.1737462431192398f, 0.0146679216995835f, -0.1152463182806969f,
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+// -0.1657188236713409f, -0.1331969946622849f, 0.2499409615993500f,
+// 0.1198557615280151f, 0.1792458593845367f, -0.1056910082697868f,
+// 0.1177701875567436f, 0.2587517499923706f, -0.0499034747481346f,
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+// 0.0661796629428864f, -0.0394094400107861f, 0.0434221737086773f,
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+// 0.1165523380041122f, -0.1312440335750580f, -0.0749584808945656f,
+// 0.3485709130764008f, -0.0909551233053207f, -0.1787046343088150f,
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+// -0.1012458130717278f, 0.1573468297719955f, -0.1628507673740387f,
+// 0.0601159222424030f, -0.0955733954906464f, -0.1479061841964722f,
+// -0.0031853148248047f, -0.1238449662923813f, -0.1780974417924881f,
+// 0.0627665296196938f, 0.1257301419973373f, 0.2760817706584930f,
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+// 0.1393495947122574f, 0.1759965121746063f, -0.1309165805578232f,
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+// 0.1447358131408691f, 0.1892404258251190f, 0.1373548656702042f,
+// 0.1637340635061264f, 0.1169472262263298f, 0.0515772663056850f,
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+// 0.0629809945821762f, -0.0835471972823143f, -0.1557926088571548f,
+// 0.0713412314653397f, 0.1043599396944046f, -0.0929564833641052f,
+// 0.0297129359096289f, -0.1671593785285950f, -0.0322603844106197f,
+// 0.0742662325501442f, 0.0120167564600706f, 0.1663252413272858f,
+// 0.1102603524923325f, 0.0078095211647451f, -0.0266669671982527f,
+// 0.0254246015101671f, 0.1061996147036552f, 0.1450502872467041f,
+// 0.1438043862581253f, 0.1233898475766182f, 0.1934651285409927f,
+// -0.2739497721195221f, -0.0946659371256828f, -0.1389613598585129f,
+// 0.1460589468479156f, 0.0173697434365749f, 0.1614376902580261f,
+// 0.1635937541723251f, 0.1900241374969482f, -0.0316323451697826f,
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+// 0.0488557927310467f, 0.2628810703754425f, -0.0141080608591437f,
+// 0.1467439383268356f, 0.1033169329166412f, 0.0239835437387228f,
+// -0.0560682602226734f, 0.0541454479098320f, 0.0899526923894882f,
+// 0.0308641586452723f, -0.1439017802476883f, -0.0466968864202499f,
+// -0.0210954882204533f, 0.0200143996626139f, 0.0529208853840828f,
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+// -0.2659919857978821f, 0.1503084599971771f, -0.1422491371631622f,
+// 0.0647155642509460f, -0.0570775270462036f, -0.0583105795085430f,
+// 0.0185720212757587f, -0.1473061740398407f, 0.0609430223703384f,
+// 0.1812216341495514f, -0.1350992172956467f, 0.0783604755997658f,
+// -0.0351044498383999f, -0.1050428226590157f, -0.0659144446253777f,
+// 0.0993853956460953f, 0.2423761785030365f, 0.0462224967777729f,
+// -0.1890792697668076f, -0.0413890704512596f, -0.0929801166057587f,
+// 0.0008010407909751f, -0.2027589082717896f, -0.0197576563805342f,
+// -0.0870766714215279f, -0.0634076818823814f, -0.0285393707454205f,
+// 0.1020642593502998f, 0.0913494527339935f, -0.1330678761005402f,
+// -0.0165407061576843f, 0.0733228400349617f, 0.0705429986119270f,
+// 0.0096256444230676f, 0.0746690183877945f, 0.1901417970657349f,
+// 0.0148927057161927f, 0.0503044724464417f, 0.0414573401212692f,
+// 0.0529941990971565f, 0.0393656007945538f, 0.0445833578705788f,
+// 0.1811574995517731f, -0.1428554803133011f, -0.0016989761497825f,
+// 0.0464389510452747f, 0.0011768714757636f, 0.0657811611890793f,
+// 0.0049138618633151f, 0.1032983213663101f, -0.2471569478511810f,
+// 0.1018852517008781f, 0.0789820328354836f, -0.0126617904752493f,
+// 0.0527672842144966f, 0.1956192553043365f, 0.0391206704080105f,
+// -0.1991813182830811f, -0.1799965798854828f, 0.1175812855362892f,
+// 0.0132352476939559f, 0.0702352523803711f, 0.2214858233928680f,
+// 0.1564911007881165f, 0.0446887053549290f, 0.0898382365703583f,
+// 0.1108002886176109f, -0.0511674731969833f, -0.1227050349116325f,
+// -0.0686719194054604f, -0.1637637466192245f, -0.1686640977859497f,
+// -0.0169594492763281f, -0.0102135529741645f, -0.0225989539176226f,
+// 0.1495187282562256f, -0.1019729226827621f, -0.1053871810436249f,
+// -0.0020472991745919f, 0.1252124458551407f, -0.0487372279167175f,
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+// -0.0482823401689529f, 0.0037969443947077f, 0.0812561661005020f,
+// -0.1244208961725235f, -0.0625018626451492f, 0.0213330872356892f,
+// 0.0303647927939892f, -0.0718785598874092f, -0.0284499954432249f,
+// 0.0688714385032654f, -0.0904124677181244f, 0.0364760011434555f,
+// -0.1333056092262268f, 0.1768662780523300f, 0.1972743719816208f,
+// 0.1790831238031387f, -0.0148302307352424f, -0.1891036331653595f,
+// -0.0803935453295708f, 0.1864317506551743f, -0.1418409347534180f,
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+// 0.1455782502889633f, -0.0069482526741922f, 0.0629748478531837f,
+// -0.0840674042701721f, -0.0517137497663498f, 0.0029174326919019f,
+// -0.1454419493675232f, -0.2037513554096222f, 0.2351006567478180f,
+// 0.0246584564447403f, -0.1599640399217606f, 0.1091224625706673f,
+// -0.0126211661845446f, -0.1638000011444092f, -0.2911465466022491f,
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+// -0.0423522777855396f, -0.1522083282470703f, -0.0445525646209717f,
+// -0.0836364105343819f, 0.0385956242680550f, -0.0339670442044735f,
+// 0.1446139961481094f, 0.1450899392366409f, 0.1539156287908554f,
+// -0.0062353298999369f, -0.0147529589012265f, 0.0282012689858675f,
+// -0.0288142375648022f, 0.2160197645425797f, -0.0752451866865158f,
+// 0.0214825011789799f, -0.2429380267858505f, 0.0370178483426571f,
+// -0.0412995368242264f, -0.1441085338592529f, 0.0517850294709206f,
+// 0.0070630759000778f, 0.0832872465252876f, -0.0114870006218553f,
+// 0.2288380712270737f, 0.1885838955640793f, -0.0730772912502289f,
+// 0.0087908264249563f, -0.0900564789772034f, 0.0819780454039574f,
+// 0.0006482307217084f, -0.0245730690658092f, -0.0964125245809555f,
+// 0.0762761384248734f, 0.4246636331081390f, 0.1138819456100464f,
+// 0.0105022992938757f, 0.0008363610832021f, -0.1426776200532913f,
+// 0.0330112762749195f, -0.0390948094427586f, 0.2625973224639893f,
+// -0.1235488653182983f, -0.0425786785781384f, 0.0074098221957684f,
+// 0.0108526824042201f, -0.0351473093032837f, -0.0169854778796434f,
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+// -0.0463579781353474f, 0.1510650217533112f, 0.2124273031949997f,
+// -0.0007902351208031f, -0.0399611406028271f, -0.0962318778038025f,
+// -0.0455383732914925f, 0.0138793094083667f, 0.0373521521687508f,
+// 0.0320328399538994f, -0.0085103167220950f, 0.0040090102702379f,
+// -0.0718325600028038f, -0.0500103868544102f, -0.0247612334787846f,
+// 0.1002800092101097f, 0.0198234189301729f, 0.0944705232977867f,
+// 0.0795515552163124f, -0.0156148849055171f, -0.2421914935112000f,
+// 0.0189311467111111f, 0.0136592583730817f, 0.0557755492627621f,
+// -0.0848597809672356f, 0.0675975903868675f, 0.0007717291009612f,
+// 0.0089664282277226f, 0.2369871139526367f, -0.0397173464298248f,
+// 0.0441740080714226f, -0.0694444030523300f, -0.0160166863352060f,
+// -0.1755478382110596f, 0.0178955756127834f, 0.2111767679452896f,
+// 0.0764642357826233f, 0.0424373298883438f, 0.0804371163249016f,
+// -0.0371816270053387f, -0.1282641887664795f, -0.0563771873712540f,
+// -0.0669650584459305f, -0.0214992519468069f, 0.0780751034617424f,
+// 0.0134029956534505f, -0.0729406252503395f, 0.0122546199709177f,
+// -0.0889038294553757f, -0.0723734572529793f, -0.0748314112424850f,
+// 0.0774794220924377f, -0.0750551149249077f, -0.1767835468053818f,
+// -0.0769128128886223f, -0.0320755057036877f, -0.0461665317416191f,
+// 0.0541505888104439f, 0.0337853915989399f, 0.1166592463850975f,
+// 0.0363865680992603f, -0.0831474885344505f, 0.0329656824469566f,
+// 0.0826740562915802f, -0.0588761940598488f, -0.0235717128962278f,
+// -0.1224157363176346f, -0.0303315985947847f, 0.0032174983061850f,
+// -0.0183449778705835f, 0.1269046217203140f, -0.1752059012651443f,
+// -0.0625565648078918f, 0.0439131408929825f, 0.1641421765089035f,
+// -0.0334399044513702f, -0.1011813580989838f, 0.0653419867157936f,
+// -0.2629381716251373f, -0.4263016283512115f, -0.0264297667890787f,
+// -0.0679647922515869f, 0.0012379598338157f, -0.1152262315154076f,
+// 0.2260819822549820f, 0.0138499122112989f, -0.2540936172008514f,
+// 0.0710316747426987f, 0.0597474165260792f, 0.3569871187210083f,
+// -0.0970500186085701f, 0.1018327623605728f, 0.2961482405662537f,
+// -0.0835851654410362f, 0.0061521492898464f, 0.0876464322209358f,
+// -0.1374511271715164f, 0.0498932786285877f, 0.0182282179594040f,
+// 0.2959185242652893f, 0.0747583433985710f, -0.5113818645477295f,
+// 0.0357646793127060f, -0.0284922197461128f, 0.0853188410401344f,
+// 0.0409507416188717f, 0.1276202499866486f, 0.0070483270101249f,
+// -0.1558059006929398f, -0.1902582943439484f, 0.2762999534606934f,
+// 0.6160352230072021f, 0.2738423943519592f, -0.8241607546806335f,
+// -0.1773925721645355f, -0.2928967773914337f, 0.2864287495613098f,
+// -0.1489850878715515f, -0.1174923256039619f, 0.1652690619230270f,
+// -0.4835466146469116f, 0.2626637220382690f, 0.0533090643584728f,
+// -0.3799187242984772f, -0.2041940391063690f, 0.5791236758232117f,
+// 0.0561702437698841f, 0.2298431694507599f, -0.1198691874742508f,
+// -0.2694389820098877f, 0.0000510087193106f, 0.3546921610832214f,
+// 0.0112113691866398f, 0.0379001311957836f, 0.0142445443198085f,
+// -0.0794466659426689f, 0.0820474997162819f, -0.0093114906921983f,
+// -0.0566410310566425f, -0.0061155571602285f, 0.0090680094435811f,
+// 0.0345985181629658f, 0.0450940802693367f, -0.0093504283577204f,
+// -0.0935023650527000f, 0.0195171404629946f, -0.0183419995009899f,
+// 0.0391614325344563f, -0.5121891498565674f, -0.6687004566192627f,
+// 0.9917605519294739f, -0.0210490524768829f, -0.2893266081809998f,
+// 0.1215797439217567f, -0.6205708384513855f, -0.0794832706451416f,
+// 0.5176062583923340f, -0.8354176282882690f, 1.2010480165481567f,
+// 0.9594748020172119f, -0.1379863321781158f, -0.1795917153358459f,
+// 0.6028102636337280f, -1.0556331872940063f, 0.0525154247879982f,
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+// 0.1093455627560616f, 0.1153903454542160f, 0.1207851395010948f,
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+// 0.2282506823539734f, 0.2710544168949127f, -0.0136018563061953f,
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+// 0.2476447224617004f, 0.0093221291899681f, -0.0667056739330292f,
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+// 0.0188038200139999f, -0.0177161544561386f, 0.0355775579810143f,
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+// 0.3786133229732513f, 0.1218430772423744f, 0.0396988503634930f,
+// 0.1030738800764084f, -0.1429519653320312f, -0.0382298193871975f,
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+// 0.0535276718437672f, -0.0910151675343513f, -0.2684104442596436f,
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+// 0.1163832023739815f, 0.0630314648151398f, -0.1122179627418518f,
+// 0.0312713570892811f, -0.2228856682777405f, 0.1076095551252365f,
+// 0.1975958496332169f, -0.1434646993875504f, 0.0081013087183237f,
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+// 0.0727546662092209f, -0.1553122997283936f, 0.0417129918932915f,
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+// -0.1369005441665649f, -0.2390962392091751f, 0.0024375389330089f,
+// 0.1115006431937218f, 0.0663523375988007f, 0.0951579138636589f,
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+// 0.0930276066064835f, -0.0933868288993835f, 0.0718567743897438f,
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+// -0.0641773566603661f, 0.0978113263845444f, 0.1789615750312805f,
+// 0.0747304037213326f, -0.0372986942529678f, 0.1306611448526382f,
+// 0.3728033304214478f, 0.1171047687530518f, 0.0702980607748032f,
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+// 0.2065934836864471f, -0.1057194769382477f, -0.0857231542468071f,
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+// 0.1207673475146294f, -0.1154693514108658f, 0.0027352985925972f,
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+// 0.3365089893341064f, -0.0403482466936111f, -0.0328563675284386f,
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+// -0.1017340868711472f, 0.2974070310592651f, 0.2210731208324432f,
+// 0.3533378839492798f, 0.3502863049507141f, 0.0582765676081181f,
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+// 0.1054410636425018f, -0.1993426382541656f, 0.0780057758092880f,
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+// -0.0216590985655785f, 0.1607030779123306f, -0.2575193345546722f,
+// 0.0695946887135506f, 0.2870674729347229f, -0.0660185888409615f,
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+// 0.0423683635890484f, -0.0161939579993486f, -0.1003662273287773f,
+// 0.0677077099680901f, -0.1503618806600571f, -0.2118269354104996f,
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+// 0.1900429278612137f, -0.1483856737613678f, -0.0343045666813850f,
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+// -0.0886480882763863f, -0.0715486183762550f, -0.0118775302544236f,
+// 0.3031563460826874f, -0.1199106872081757f, -0.1827986687421799f,
+// -0.0217756908386946f, -0.1394552439451218f, -0.0212255995720625f,
+// 0.1364105492830276f, 0.0307547803968191f, -0.0344934761524200f,
+// 0.2225001454353333f, 0.1611603796482086f, 0.0294682029634714f,
+// 0.0206141751259565f, 0.1585433632135391f, -0.0620258785784245f,
+// 0.0152152962982655f, 0.0016174763441086f, 0.0110861537978053f,
+// 0.1104811057448387f, 0.3871656656265259f, 0.0419528409838676f,
+// -0.3089349865913391f, -0.0854183807969093f, 0.1943933963775635f,
+// 0.1667490452528000f, 0.1076019555330276f, -0.0837732106447220f,
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+// 0.0872882381081581f, -0.1108269616961479f, 0.2571115791797638f,
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+// 0.4249170422554016f, -0.1261430531740189f, 0.2949620187282562f,
+// 0.0369671024382114f, 0.1544607430696487f, -0.0710825547575951f,
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+// 0.0161852296441793f, -0.0270081944763660f, 0.1162303909659386f,
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+// 0.1256739050149918f, 0.2061168998479843f, 0.0148658938705921f,
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+// 0.0227867402136326f, -0.2321236729621887f, 0.2313296198844910f,
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+// -0.1369665116071701f, -0.0994857698678970f, 0.0797817483544350f,
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+// -0.0810139849781990f, -0.1165102645754814f, -0.0395633392035961f,
+// 0.1469996124505997f, 0.1363371163606644f, 0.0874181538820267f,
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+// -0.1791488379240036f, 0.0269580576568842f, -0.0302843544632196f,
+// 0.1354919373989105f, 0.0633941143751144f, -0.0269965734332800f,
+// 0.0666595548391342f, -0.0464111007750034f, 0.0970299169421196f,
+// 0.0381624251604080f, -0.0421104095876217f, 0.1212913691997528f,
+// -0.0475185513496399f, -0.0513341762125492f, 0.0650672689080238f,
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+// 0.1245638504624367f, -0.2378986477851868f, -0.0108543168753386f,
+// 0.0665224269032478f, 0.0458335317671299f, 0.1591640859842300f,
+// 0.1585987657308578f, 0.2744040191173553f, 0.1549030989408493f,
+// -0.1441929489374161f, 0.0910146459937096f, 0.0753629431128502f,
+// 0.1399861276149750f, -0.0777972564101219f, 0.1757298409938812f,
+// -0.0972793772816658f, -0.0286695752292871f, -0.0961130261421204f,
+// 0.1051636040210724f, -0.1660098582506180f, 0.1130620539188385f,
+// 0.2631500661373138f, -0.2231564223766327f, -0.1757420450448990f,
+// 0.0775376260280609f, 0.0181281976401806f, -0.0727695971727371f,
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+// 0.0939532518386841f, -0.2200393378734589f, 0.0436523072421551f,
+// -0.0433272756636143f, -0.0914834439754486f, 0.0505776479840279f,
+// 0.1022464632987976f, 0.1459463387727737f, -0.1190353035926819f,
+// 0.2003114223480225f, 0.3734146952629089f, 0.1688542664051056f,
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+// -0.1094769239425659f, 0.0717625468969345f, 0.0171967428177595f,
+// 0.0693440213799477f, 0.1161517202854156f, -0.1482351422309875f,
+// -0.0527954623103142f, -0.2061173617839813f, 0.0015312288887799f,
+// -0.0870700553059578f, 0.0721013322472572f, 0.0908060297369957f,
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+// -0.1405198276042938f, 0.0524829737842083f, 0.0131116826087236f,
+// -0.0661652311682701f, 0.1561692953109741f, 0.0961418896913528f,
+// -0.0387788936495781f, -0.0248648636043072f, -0.0113855497911572f,
+// -0.0881337523460388f, 0.2002922147512436f, 0.0937845855951309f,
+// 0.0770952031016350f, -0.1672172397375107f, 0.0375956408679485f,
+// -0.1145847961306572f, -0.0995001718401909f, 0.0130494581535459f,
+// -0.0333772450685501f, -0.0707886815071106f, -0.0862217396497726f,
+// 0.0570426881313324f, -0.1579607427120209f, -0.2092322260141373f,
+// 0.1500418782234192f, 0.0027825061697513f, 0.0223845299333334f,
+// -0.0768262445926666f, 0.1709239482879639f, 0.0602882429957390f,
+// -0.0178609788417816f, -0.0578219518065453f, -0.1126151829957962f,
+// 0.0907006710767746f, 0.3088326752185822f, -0.0098354117944837f,
+// -0.1122854053974152f, -0.0215447302907705f, -0.1563781052827835f,
+// 0.0319213159382343f, 0.0461141504347324f, 0.1089784055948257f,
+// -0.0468449480831623f, -0.1103684231638908f, 0.0523271672427654f,
+// 0.0970082283020020f, 0.0003151137498207f, 0.0280394665896893f,
+// -0.0244269035756588f, 0.1757394820451736f, -0.0406786650419235f,
+// 0.2700901925563812f, -0.1414983719587326f, 0.2856762409210205f,
+// 0.1808325052261353f, -0.0884146541357040f, 0.0894261822104454f,
+// 0.0792104080319405f, -0.2354325652122498f, 0.0666357651352882f,
+// -0.0961195603013039f, 0.0134357316419482f, -0.0377625226974487f,
+// 0.0121926777064800f, -0.0248180497437716f, -0.0956555157899857f,
+// 0.1386297792196274f, 0.2122491002082825f, -0.0635866001248360f,
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+// -0.0312537774443626f, 0.1183333694934845f, -0.0239673182368279f,
+// 0.0219212453812361f, 0.0722134187817574f, 0.0432669334113598f,
+// 0.1770490556955338f, -0.0334726758301258f, -0.0970422625541687f,
+// 0.0730579495429993f, -0.2324937731027603f, -0.0647482350468636f,
+// 0.3207351267337799f, 0.0502215214073658f, -0.1806760877370834f,
+// 0.0914437472820282f, -0.0576261207461357f, 0.0207699965685606f,
+// -0.0218109190464020f, -0.0677828341722488f, 0.1272961646318436f,
+// 0.0851818993687630f, -0.1522843241691589f, -0.1603651195764542f,
+// 0.1202934160828590f, -0.0073252813890576f, -0.1744964569807053f,
+// -0.0474111586809158f, -0.2173368036746979f, -0.0242933668196201f,
+// 0.0188443437218666f, -0.0049744127318263f, -0.0870547443628311f,
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+// -0.0122366556897759f, 0.0455913878977299f, 0.1210150793194771f,
+// 0.0126438438892365f, -0.1638556718826294f, -0.0194818936288357f,
+// 0.0359559729695320f, 0.1446994394063950f, -0.1889744997024536f,
+// -0.0204027965664864f, -0.0233468078076839f, -0.0968362689018250f,
+// -0.1502992212772369f, -0.1792789846658707f, -0.0082423537969589f,
+// -0.0590886324644089f, -0.1423509418964386f, 0.2592583596706390f,
+// 0.0273712370544672f, -0.0039504207670689f, -0.0739362612366676f,
+// 0.0519393421709538f, -0.0763773098587990f, 0.0220349933952093f,
+// -0.0191066879779100f, -0.0463334359228611f, 0.1748371422290802f,
+// 0.3127614557743073f, -0.1898039430379868f, -0.0608385130763054f,
+// -0.4708963036537170f, -0.1571139991283417f, -0.1975501924753189f,
+// -0.3562301397323608f, -0.0655168890953064f, -0.1367894858121872f,
+// 0.2602920532226562f, 0.0420096814632416f, 0.1749608665704727f,
+// 0.1065022870898247f, -0.1303322911262512f, -0.1077217310667038f,
+// 0.1505750417709351f, -0.2198125869035721f, -0.1539839506149292f,
+// 0.0439731404185295f, -0.1083691418170929f, 0.1466861963272095f,
+// 0.0753150731325150f, 0.0621398761868477f, -0.1449284106492996f,
+// -0.4172681272029877f, -0.1218186244368553f, 0.0133974663913250f,
+// 0.2802741527557373f, -0.1468246281147003f, 0.0561642423272133f,
+// -0.1973892897367477f, 0.1425260305404663f, 0.1200959235429764f,
+// -0.2540864944458008f, -0.0451332852244377f, -0.0774713307619095f,
+// 0.1043525934219360f, -0.2008667141199112f, -0.0922299697995186f,
+// 0.1249082535505295f, 0.0753674954175949f, 0.1794690936803818f,
+// 0.0481610000133514f, 0.2290256321430206f, 0.0065677673555911f,
+// -0.1316900104284286f, 0.0517593771219254f, -0.0278395041823387f,
+// 0.1025687456130981f, -0.0924220755696297f, 0.1303273886442184f,
+// 0.0131958033889532f, -0.0026033148169518f, -0.0903415232896805f,
+// 0.0860455855727196f, 0.0394442863762379f, 0.0011147280456498f,
+// 0.0110142966732383f, 0.0553604438900948f, 0.0380987413227558f,
+// -0.0301202572882175f, 0.0754162743687630f, 0.6681923270225525f,
+// 0.6316007375717163f, 0.5362718701362610f, -0.8213173747062683f,
+// -0.3215168714523315f, 0.3318290114402771f, 0.3521389365196228f,
+// -0.3562639355659485f, 0.2637158036231995f, 0.3961311876773834f,
+// -1.4484114646911621f, 0.2748066186904907f, -0.1623894721269608f,
+// -0.6479159593582153f, -0.0295416079461575f, -0.5205885171890259f,
+// 0.0867275893688202f, -0.3208928704261780f, 0.0703487545251846f,
+// -0.0955524593591690f, 0.3234241902828217f, -0.0168523900210857f,
+// -0.1740704029798508f, -0.0560244619846344f, -0.2357091009616852f,
+// 0.1901086121797562f, 0.0481014065444469f, -0.1535841673612595f,
+// 0.0685922801494598f, 0.0790470317006111f, 0.2868210375308990f,
+// 0.1454970538616180f, -0.0094223665073514f, -0.3079305291175842f,
+// 0.0063943052664399f, -0.2601941227912903f, -0.1146657690405846f,
+// 0.0406668484210968f, 0.0460451580584049f, -0.1738330423831940f,
+// -0.0950062125921249f, 0.1378656029701233f, 0.0337428003549576f,
+// -0.0938330665230751f, -0.2417292147874832f, -0.0163973309099674f,
+// 0.1528589129447937f, 0.1970895677804947f, -0.1839562356472015f,
+// 0.1459633260965347f, -0.0341233871877193f, -0.2587058842182159f,
+// -0.3193149566650391f, 0.0435526371002197f, -0.1281607598066330f,
+// -0.0131546333432198f, 0.0555017031729221f, -0.0336095802485943f,
+// -0.1269194781780243f, -0.1513453125953674f, 0.2411169856786728f,
+// -0.2541488111019135f, -0.1244575902819633f, 0.0887695848941803f,
+// 0.0128328967839479f, -0.1110535413026810f, -0.1428905725479126f,
+// 0.1972058862447739f, 0.1103013604879379f, 0.2220357209444046f,
+// 0.1790663152933121f, 0.1567227095365524f, -0.1351126283407211f,
+// -0.2197245210409164f, -0.0211505498737097f, -0.4470945596694946f,
+// 0.0926721394062042f, 0.2450220435857773f, 0.1497591137886047f,
+// -0.0998463258147240f, 0.0555943325161934f, 0.1221810728311539f,
+// -0.0608536005020142f, 0.2098911702632904f, 0.0115941679105163f,
+// -0.0674353539943695f, 0.0006982820341364f, 0.0538154542446136f,
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+// -0.1395203173160553f, -0.0207257047295570f, 0.0047744712792337f,
+// 0.1958790272474289f, 0.1226971521973610f, 0.0507005229592323f,
+// -0.0971429198980331f, 0.0197005178779364f, 0.0745770782232285f,
+// -0.0555057749152184f, 0.0941618159413338f, 0.1198589950799942f,
+// -0.1864831596612930f, 0.1066691279411316f, -0.1551116853952408f,
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+// 0.0650537312030792f, -0.1043618246912956f, 0.1136299967765808f,
+// 0.2263264507055283f, 0.0690380036830902f, -0.0856620147824287f,
+// -0.1094242930412292f, -0.0332741662859917f, 0.2534106969833374f,
+// 0.2466552108526230f, -0.0282907504588366f, 0.0833334550261497f,
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+// 0.1182646229863167f, -0.0239937640726566f, 0.0174511708319187f,
+// 0.1029690206050873f, 0.0554951131343842f, -0.3961259424686432f,
+// 0.0320917516946793f, 0.1041571348905563f, -0.0720538571476936f,
+// 0.2545490562915802f, 0.0599945969879627f, -0.1997217386960983f,
+// -0.1914409697055817f, 0.0698372274637222f, -0.0032093448098749f,
+// 0.0657015964388847f, 0.0117887714877725f, 0.2888590395450592f,
+// 0.0521594025194645f, 0.0388358868658543f, -0.0576213337481022f,
+// 0.4330531656742096f, 0.2691972851753235f, 0.0372633412480354f,
+// 0.3821379244327545f, -0.0842721015214920f, 0.1933181583881378f,
+// -0.1397679746150970f, 0.4160114526748657f, -0.3656279146671295f,
+// -0.1079362034797668f, 0.0837938115000725f, -0.0045389086008072f,
+// 0.2289495617151260f, -0.0560545548796654f, 0.1650007069110870f,
+// 0.2641780376434326f, -0.0361910127103329f, 0.1329219192266464f,
+// -0.2106186449527740f, -0.0236701387912035f, -0.2362307608127594f,
+// 0.0643483847379684f, -0.0761788114905357f, -0.1683549433946609f,
+// 0.1203127205371857f, -0.1442517787218094f, -0.0105598540976644f,
+// -0.0247587058693171f, -0.1658469140529633f, 0.0945092290639877f,
+// 0.1597421467304230f, -0.0041760206222534f, -0.2136207073926926f,
+// 0.2530310750007629f, -0.0618494674563408f, -0.2203333973884583f,
+// -0.1109683066606522f, -0.1094078496098518f, -0.2094247341156006f,
+// -0.0059005464427173f, -0.1072451770305634f, 0.3659992218017578f,
+// 0.4427329003810883f, -0.0303660221397877f, -0.1043204441666603f,
+// -0.0137985786423087f, -0.2778229713439941f, -0.0959384664893150f,
+// 0.3666695058345795f, 0.2842301130294800f, -0.0283856112509966f,
+// 0.3892648220062256f, 0.0497923567891121f, -0.1631491929292679f,
+// -0.3468397259712219f, 0.3105171024799347f, 0.1941643208265305f,
+// 0.3015421330928802f, -0.1483277678489685f, 0.0071847010403872f,
+// -0.0827584043145180f, 0.0179677885025740f, 0.0778496712446213f,
+// -0.0593084506690502f, -0.0149650862440467f, 0.2169589102268219f,
+// 0.0278623476624489f, 0.1544311046600342f, 0.0490665249526501f,
+// 0.2423795014619827f, 0.0901412963867188f, 0.0043124761432409f,
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+// 0.1041186079382896f, -0.0424462221562862f, -0.1692581325769424f,
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+// 0.0806336328387260f, -0.2091737687587738f, 0.1492128074169159f,
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+// 0.0877645537257195f, -0.0649409517645836f, 0.0695746764540672f,
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+// -0.1527331918478012f, -0.1652346104383469f, 0.2449037283658981f,
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+// 0.0995136201381683f, -0.1150716021656990f, -0.0764078050851822f,
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+// -0.0830969065427780f, -0.0463324524462223f, 0.0412169247865677f,
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+// 0.1696011424064636f, 0.1290095895528793f, -0.0302001237869263f,
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+// -0.0125074153766036f, -0.0286178551614285f, 0.0309653058648109f,
+// 0.0464372448623180f, -0.2313171774148941f, -0.0482147485017776f,
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+// 0.2309416830539703f, -0.0291974805295467f, -0.0395665131509304f,
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+// 0.1266385912895203f, -0.1021424010396004f, 0.0045360750518739f,
+// 0.0314533375203609f, -0.1365369111299515f, -0.0347279235720634f,
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+// 0.0284361708909273f, -0.1016578301787376f, -0.1145663708448410f,
+// 0.0606947988271713f, -0.1940838247537613f, 0.0126973940059543f,
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+// -0.0189130119979382f, -0.0315966084599495f, -0.0157221890985966f,
+// 0.2291333377361298f, 0.0123773226514459f, 0.2210101336240768f,
+// -0.1972611844539642f, -0.1209637075662613f, -0.1411139219999313f,
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+// 0.1648572236299515f, 0.0564788505434990f, 0.1755364537239075f,
+// 0.1692955642938614f, 0.0303093343973160f, 0.2394215166568756f,
+// 0.0565703548491001f, 0.0511648096144199f, 0.2110276520252228f,
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+// 0.2963657379150391f, -0.4579209983348846f, -0.0046650613658130f,
+// 0.1799484640359879f, 0.1897033005952835f, -0.1359965354204178f,
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+// 0.3200229406356812f, -0.0120745645835996f, -0.0494608581066132f,
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+// 0.4925916194915771f, -0.0505388937890530f, -0.1025306656956673f,
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+// 0.0049551692791283f, 0.0809677243232727f, 0.1717177778482437f,
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+// 0.1068105995655060f, -0.1271140724420547f, 0.1384425759315491f,
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+// 0.2868227660655975f, -0.1300112903118134f, 0.0198988467454910f,
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+// 0.6361710429191589f, 0.2204178124666214f, -0.1568987518548965f,
+// 0.1149112209677696f, 0.3067569434642792f, 0.0615913458168507f,
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+// 0.3750589787960052f, -0.1952226012945175f, -0.0790153071284294f,
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+// -0.1985560506582260f, 0.1928349882364273f, 0.1561378389596939f,
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+// -0.1895079463720322f, 0.0927981734275818f, 0.0333512835204601f,
+// 0.1992869079113007f, -0.0312908627092838f, -0.0149518540129066f,
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+// -0.0684843212366104f, 0.0781661793589592f, -0.0067289890721440f,
+// 0.1290438920259476f, -0.0537219718098640f, 0.0115450965240598f,
+// -0.2369331419467926f, -0.1265742033720016f, -0.0164060126990080f,
+// 0.0052112331613898f, -0.1829767972230911f, -0.0602909661829472f,
+// 0.1225484535098076f, 0.2503139376640320f, 0.0699351504445076f,
+// -0.0533467046916485f, 0.0657910704612732f, -0.1880515813827515f,
+// 0.1622430831193924f, -0.1427335292100906f, 0.0538796298205853f,
+// -0.0004921349463984f, 0.2428364604711533f, -0.0909080281853676f,
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+// -0.1282693743705750f, -0.0495833903551102f, 0.0278256610035896f,
+// -0.0663326755166054f, 0.0838592275977135f, 0.2313254326581955f,
+// -0.2199959754943848f, 0.0235796868801117f, -0.0407694019377232f,
+// -0.0703621581196785f, 0.0629681125283241f, -0.1138029992580414f,
+// 0.2555616796016693f, -0.0839884653687477f, -0.1953315585851669f,
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+// -0.1502161771059036f, -0.2584075927734375f, 0.2805217802524567f,
+// 0.0551475510001183f, 0.2100235521793365f, -0.1751943975687027f,
+// 0.0122900912538171f, -0.0464167408645153f, 0.0213084556162357f,
+// -0.2803128361701965f, 0.1201025769114494f, -0.0224970225244761f,
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+// -0.1656913757324219f, 0.0775236338376999f, 0.0464210584759712f,
+// 0.0123868165537715f, -0.0678479596972466f, 0.1282611489295959f,
+// -0.0202953983098269f, -0.0993030741810799f, 0.1929417848587036f,
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+// -0.1109331101179123f, 0.0145028978586197f, 0.1542881131172180f,
+// 0.2346950471401215f, -0.1361192017793655f, -0.0308647900819778f,
+// -0.0489426366984844f, 0.1718769222497940f, 0.2053886950016022f,
+// -0.2539495229721069f, -0.1018095239996910f, 0.0845039114356041f,
+// 0.0175074748694897f, -0.0688851252198219f, 0.1283828914165497f,
+// 0.2643659412860870f, -0.0406027771532536f, -0.0594156645238400f,
+// 0.0197443272918463f, -0.0941221639513969f, -0.2053193151950836f,
+// 0.1276859194040298f, 0.0331459939479828f, 0.0145516544580460f,
+// 0.0156483296304941f, -0.0750918984413147f, 0.0564464554190636f,
+// 0.1294697523117065f, -0.0885504707694054f, 0.1214636564254761f,
+// -0.3569331765174866f, -0.0028916716109961f, 0.0934935882687569f,
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+// -0.0492803715169430f, 0.1165777146816254f, -0.3131483495235443f,
+// -0.0272703934460878f, 0.0698637813329697f, 0.1031246855854988f,
+// 0.0132356602698565f, 0.1784261316061020f, -0.0016409255331382f,
+// -0.0313125327229500f, -0.1318468004465103f, -0.0835071504116058f,
+// -0.0926908701658249f, -0.1341038793325424f, 0.1179625988006592f,
+// -0.0902648717164993f, 0.0245866570621729f, -0.0896214023232460f,
+// 0.0196530465036631f, 0.0207235291600227f, -0.1221037581562996f,
+// 0.0434450581669807f, -0.0846474319696426f, 0.1051371768116951f,
+// 0.0332174263894558f, -0.1202881261706352f, -0.0533026941120625f,
+// 0.0631469711661339f, -0.0419523864984512f, -0.2012638151645660f,
+// 0.1645533442497253f, 0.0277804154902697f, 0.0165271479636431f,
+// 0.0927421972155571f, -0.1261221617460251f, 0.0409524366259575f,
+// -0.0583577789366245f, -0.0199796445667744f, 0.0251666307449341f,
+// 0.1364693939685822f, -0.0411914624273777f, 0.0603740513324738f,
+// -0.2406388521194458f, -0.0320866852998734f, -0.1976006031036377f,
+// 0.0039697722531855f, -0.1254921853542328f, -0.0105804074555635f,
+// 0.3773926794528961f, 0.2423142492771149f, 0.0184606835246086f,
+// -0.1536319553852081f, -0.1058158278465271f, -0.0001398056047037f,
+// -0.0589615479111671f, -0.1631432026624680f, 0.0079887565225363f,
+// 0.0943696498870850f, -0.0579817667603493f, -0.0575003027915955f,
+// -0.0495418347418308f, -0.1235411316156387f, 0.0198634508997202f,
+// 0.1241424903273582f, 0.0315700359642506f, 0.1840870827436447f,
+// -0.1974976509809494f, 0.0410114564001560f, 0.2968510985374451f,
+// -0.1252246052026749f, 0.0399858504533768f, 0.0208173207938671f,
+// -0.1142217144370079f, 0.0788220837712288f, -0.0882162153720856f,
+// 0.1083799675107002f, 0.0465777106583118f, -0.2438936382532120f,
+// 0.0104710683226585f, 0.1250163167715073f, -0.0033580935560167f,
+// 0.0159356445074081f, 0.0691958367824554f, 0.2616451382637024f,
+// -0.1606348454952240f, -0.0211692955344915f, 0.0705282613635063f,
+// 0.0688264742493629f, 0.0623508580029011f, 0.0510939098894596f,
+// -0.3835167884826660f, -0.0153954690322280f, 0.1115010380744934f,
+// -0.0240041334182024f, 0.0666085705161095f, -0.0342428348958492f,
+// -0.0646605864167213f, 0.0082503147423267f, -0.0385219827294350f,
+// 0.0688725635409355f, 0.0341519117355347f, 0.0558726340532303f,
+// -0.0415631532669067f, -0.0361984595656395f, -0.0593137033283710f,
+// -0.0302594285458326f, -0.1148351579904556f, -0.0853656232357025f,
+// -0.0676017701625824f, 0.1161052882671356f, 0.0915120691061020f,
+// 0.4906959831714630f, -0.0307663828134537f,
+// 0.2017363607883453f, 1.2648358345031738f, 0.5083269476890564f,
+// 0.4334732890129089f, -0.1585585922002792f, -0.2111468464136124f,
+// 0.4176878929138184f, 0.7735207080841064f, 0.1244546622037888f,
+// -0.6843889355659485f, 0.1594558954238892f, -0.0877284482121468f,
+// -0.0934081301093102f, 0.2201144546270370f, 0.1858011037111282f,
+// -0.1924093365669250f, -0.4220013916492462f, 0.4142990410327911f,
+// 0.0831182077527046f, -0.1979080438613892f, -0.0733913034200668f,
+// -0.0110376719385386f, 0.1638949662446976f, 0.0239491481333971f,
+// 0.1725535988807678f, 0.2106739878654480f, 0.1223915889859200f,
+// 0.0009053151588887f, 0.1026817709207535f, -0.1727186590433121f,
+// 0.1742674559354782f, 0.3389405608177185f, -0.0395730920135975f,
+// -0.1830768585205078f, 0.0266164876520634f, -0.2730126976966858f,
+// -0.5858401656150818f, 0.2268160134553909f, 0.3413348197937012f,
+// -0.0047271233052015f, 0.2049348950386047f, 0.0657818242907524f,
+// 0.2228711098432541f, 0.1135584712028503f, 0.4326843321323395f,
+// 0.2298161238431931f, 0.2015644907951355f, 0.1110046952962875f,
+// 0.0606575943529606f, -0.0331467874348164f, 0.2595092952251434f,
+// -0.0272643137723207f, 0.1298983395099640f, -0.0148730883374810f,
+// 0.1309608817100525f, -0.0275207310914993f, 0.4099220931529999f,
+// 0.1363433301448822f, -0.0575377196073532f, -0.0543120987713337f,
+// 0.3322158157825470f, 0.2720876634120941f, 0.3057950437068939f,
+// 0.0403622798621655f, 0.0821062028408051f, -0.0296456608921289f,
+// -0.1418694555759430f, 0.0146760717034340f, 0.2052378654479980f,
+// -0.1993263512849808f, -0.1300887614488602f, 0.0546308718621731f,
+// -0.1884693503379822f, -0.2196718156337738f, -0.0639357492327690f,
+// 0.0606384426355362f, 0.3647794425487518f, -0.3693757653236389f,
+// -0.1787857711315155f, 0.0548747181892395f, 0.1209919974207878f,
+// 0.1872123777866364f, 0.0118963140994310f, -0.1876832097768784f,
+// 0.1268126070499420f, 0.0892164930701256f, 0.0669552609324455f,
+// 0.1282535046339035f, -0.0362701527774334f, -0.0891116708517075f,
+// 0.1187989488244057f, -0.1218328699469566f, 0.0730293989181519f,
+// -0.1497168838977814f, 0.0403952151536942f, 0.0019880044274032f,
+// 0.1015618592500687f, 0.3091747760772705f, -0.1411400437355042f,
+// -0.0084361173212528f, 0.6711298227310181f, -0.1305765509605408f,
+// -0.0398643612861633f, -0.2870938777923584f, 0.1473812609910965f,
+// 0.1249510124325752f, -0.1608543992042542f, 0.0623804591596127f,
+// 0.1378208100795746f, 0.3917649686336517f, 0.1356630325317383f,
+// 0.1122467443346977f, 0.2286794930696487f, 0.3637783527374268f,
+// 0.3201762139797211f, 0.1155377253890038f, -0.1625074744224548f,
+// 0.1323388218879700f, -0.0357423722743988f, -0.1572718769311905f,
+// -0.0914098694920540f, 0.1874687522649765f, 0.3547669351100922f,
+// -0.1421812474727631f, -0.0498560294508934f, 0.0934837982058525f,
+// 0.0057309493422508f, 0.1298130899667740f, -0.1076349839568138f,
+// 0.2979903519153595f, 0.0441858284175396f, -0.2824388146400452f,
+// -0.3421679437160492f, -0.1948067992925644f, -0.1548708230257034f,
+// -0.0151881789788604f, -0.1906343996524811f, -0.2233033776283264f,
+// -0.0025106708053499f, -0.3046376109123230f, 0.0830271318554878f,
+// -0.2071068882942200f, -0.2143314033746719f, 0.1321865767240524f,
+// -0.2019658982753754f, 0.2465751618146896f, 0.1856192201375961f,
+// -0.1204193234443665f, -0.2843474149703979f, -0.3374885022640228f,
+// 0.2858335077762604f, 0.1195557713508606f, 0.0670883655548096f,
+// -0.3206422924995422f, -0.2742331326007843f, -0.0928037613630295f,
+// -0.5012315511703491f, -0.0942867174744606f, -0.5944977998733521f,
+// -0.0041611478663981f, 0.0033302386291325f, -0.3633164763450623f,
+// 0.1445295810699463f, -0.1802263408899307f, -0.0178903415799141f,
+// 0.2509276270866394f, 0.3885625898838043f, 0.0998945310711861f,
+// 0.1790759414434433f, -0.4489183127880096f, 0.1723191440105438f,
+// 0.2155605852603912f, -0.1229243278503418f, 0.2718102931976318f,
+// -0.0886086896061897f, -0.1289067566394806f, -0.2031675875186920f,
+// 0.1981451213359833f, 0.1044244840741158f, -0.3955842554569244f,
+// -0.0794375911355019f, 0.1811661124229431f, 0.1728780418634415f,
+// 0.0610668994486332f, 0.2468217462301254f, 0.2921097278594971f,
+// 0.1142985895276070f, 0.3477379381656647f, 0.3293513357639313f,
+// 0.1314746439456940f, -0.0993788242340088f, -0.0188899822533131f,
+// 0.0800663307309151f, 0.0990362316370010f, -0.0121280634775758f,
+// -0.1416599601507187f, 0.0002598203427624f, 0.1144914776086807f,
+// -0.0293272752314806f, -0.1005495861172676f, 0.0578081905841827f,
+// 0.2167759835720062f, 0.1142117083072662f, 0.1034634858369827f,
+// -0.0635139793157578f, -0.4752087295055389f, 0.0639986172318459f,
+// 0.1197117716073990f, 0.2155970782041550f, 0.1068556010723114f,
+// -0.2490482479333878f, 0.0153332334011793f, -0.1077664569020271f,
+// 0.1456943750381470f, -0.0772428959608078f, -0.3198736608028412f,
+// -0.3284392356872559f, -0.0941986516118050f, -0.0947097167372704f,
+// -0.5818620324134827f, 0.0823518559336662f, 0.1411766856908798f,
+// -0.1265856623649597f, -0.2444332540035248f, 0.2538483440876007f,
+// 0.3819897472858429f, 0.0565630123019218f, 0.3063717484474182f,
+// -0.4330874979496002f, 0.1154900640249252f, 0.0880522802472115f,
+// -0.0140164699405432f, 0.0462376475334167f, -0.0867302343249321f,
+// -0.0830317959189415f, 0.0233352873474360f, -0.2371585667133331f,
+// -0.1616594791412354f, -0.7031175494194031f, 0.2137373238801956f,
+// -0.2317192852497101f, -0.0558283776044846f, 0.1402771025896072f,
+// -0.4506579339504242f, 0.8182275891304016f, 0.2079046964645386f,
+// 0.1213639602065086f, -0.0727791115641594f, -0.1097266376018524f,
+// 0.0458481386303902f, 0.0143051790073514f, -0.2508694231510162f,
+// 0.0437158122658730f, -0.0550359934568405f, -0.0009142401395366f,
+// -0.0006459500873461f, -0.2016801238059998f, -0.0224555283784866f,
+// -0.0263301078230143f, 0.1223381161689758f, 0.0802955180406570f,
+// 0.4759286940097809f, 0.0967681258916855f, -0.1173584535717964f,
+// 0.1718259155750275f, 0.1183396130800247f, 0.2069330513477325f,
+// 0.3323628306388855f, -0.0242404062300920f, -0.1492614597082138f,
+// 0.1356578469276428f, -0.0460810363292694f, 0.1242129281163216f,
+// 0.0803259238600731f, 0.0540379844605923f, -0.1706735789775848f,
+// -0.1244456470012665f, 0.1190400198101997f, 0.0617938004434109f,
+// 0.0610688254237175f, -0.1892026960849762f, 0.0082607548683882f,
+// 0.1872266381978989f, 0.1204855218529701f, -0.0087748952209949f,
+// 0.0803978890180588f, 0.0792196169495583f, -0.1111150160431862f,
+// -0.0632781758904457f, -0.0793473646044731f, 0.0357510633766651f,
+// 0.0672980919480324f, 0.0021323298569769f, -0.0398143865168095f,
+// 0.0342406481504440f, -0.0384650789201260f, 0.0137053448706865f,
+// 0.0789078995585442f, -0.3018771409988403f, 0.1033568456768990f,
+// 0.0288300756365061f, -0.1085600480437279f, 0.0874207168817520f,
+// -0.0615032725036144f, 0.1283917129039764f, 0.0329267680644989f,
+// -0.0021595414727926f, -0.2071515023708344f, 0.2103916555643082f,
+// -0.1109147518873215f, 0.0436856597661972f, 0.0211482588201761f,
+// -0.2956878244876862f, 0.0567309185862541f, -0.0540873073041439f,
+// -0.0959775894880295f, 0.0491675399243832f, 0.0388988107442856f,
+// 0.2045937180519104f, 0.1203789487481117f, 0.0777890160679817f,
+// -0.0016901766648516f, -0.0909724682569504f, 0.0806366503238678f,
+// -0.1937101483345032f, 0.0770263001322746f, -0.0273292995989323f,
+// -0.0456049554049969f, -0.0417494960129261f, 0.2113896608352661f,
+// 0.0842658355832100f, 0.1011218130588531f, -0.0302428267896175f,
+// -0.0014064185088500f, -0.0199753995984793f, -0.0811152979731560f,
+// 0.0793390199542046f, -0.0187237858772278f, -0.0435786843299866f,
+// -0.0669528692960739f, -0.0115003865212202f, -0.0164016447961330f,
+// 0.1106721237301826f, 0.0771998912096024f, -0.0639739409089088f,
+// -0.2212756276130676f, -0.0211697425693274f, -0.0380606614053249f,
+// 0.0917909443378448f, -0.1082800626754761f, 0.1184694021940231f,
+// -0.0135805364698172f, 0.1647592782974243f, -0.1543314754962921f,
+// 0.0793095529079437f, 0.1303938478231430f, 0.0085686063393950f,
+// 0.1761832535266876f, 0.0335636585950851f, 0.0482380017638206f,
+// 0.1061349064111710f, 0.0070698903873563f, 0.0077055823057890f,
+// 0.0032947303261608f, 0.0672478824853897f, -0.1958143711090088f,
+// -0.1832076311111450f, 0.0725818872451782f, 0.2096267640590668f,
+// -0.0789861157536507f, 0.0679391399025917f, 0.0592983737587929f,
+// 0.1742247939109802f, -0.0785380974411964f, 0.0431108176708221f,
+// 0.0255559924989939f, -0.0578532554209232f, -0.1394288539886475f,
+// 0.0678613558411598f, -0.1875225156545639f, 0.0352321378886700f,
+// 0.0769396647810936f, 0.1884858608245850f, -0.1028645560145378f,
+// -0.0083084078505635f, 0.0410979241132736f, 0.0826147571206093f,
+// -0.1311978101730347f, -0.0680200085043907f, -0.0579532794654369f,
+// -0.0739540085196495f, 0.1291463375091553f, -0.2162090241909027f,
+// -0.0464517213404179f, -0.0945962667465210f, 0.0196109358221292f,
+// 0.0277852881699800f, 0.0542504638433456f, -0.0394079051911831f,
+// -0.0835742950439453f, -0.0057364343665540f, 0.0653834119439125f,
+// 0.0374273210763931f, 0.0390655286610126f, -0.0202709082514048f,
+// 0.0630072876811028f, 0.1708988398313522f, -0.0576840415596962f,
+// -0.0069675263948739f, 0.1335385590791702f, 0.0345381014049053f,
+// -0.0728230252861977f, -0.1203008368611336f, 0.0697158351540565f,
+// -0.0186442509293556f, -0.0794694349169731f, 0.0049100699834526f,
+// -0.1088575646281242f, 0.0930832102894783f, 0.1740644723176956f,
+// 0.0202288050204515f, -0.0920946076512337f, 0.0336422882974148f,
+// 0.0250011738389730f, 0.1517502814531326f, -0.1233569085597992f,
+// -0.0804528743028641f, -0.0372736081480980f, -0.0885115563869476f,
+// 0.1355061084032059f, -0.1287315040826797f, -0.0995895117521286f,
+// -0.0399249605834484f, -0.0382501445710659f, 0.1088246032595634f,
+// -0.0097158337011933f, -0.0961456522345543f, 0.0913006067276001f,
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+// -0.5849738717079163f, 0.0006962603074498f, 0.0294442623853683f,
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+// 0.0842550545930862f, -0.0766806304454803f, 0.1439929753541946f,
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+// -0.1077023968100548f, 0.0047123250551522f, -0.1044406220316887f,
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+// -0.2391578406095505f, 0.3183420598506927f, -0.0011616670526564f,
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+// 0.0038191901985556f, -0.0088969776406884f, -0.0943416506052017f,
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+// 0.1585037261247635f, -0.1536106020212173f, -0.0544715598225594f,
+// 0.1566033512353897f, -0.3454085588455200f, -0.1592298001050949f,
+// 0.1513053774833679f, -0.6867334842681885f, 0.0471354275941849f,
+// 0.1711468845605850f, 0.1654737591743469f, 0.1059892177581787f,
+// 0.0095621896907687f, -0.3974560499191284f, 0.0202331542968750f,
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+// 0.1134569495916367f, 0.5970299839973450f, 0.1295541822910309f,
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+// 0.0794251635670662f, -0.2955388128757477f, -0.0048130005598068f,
+// 0.0014303924981505f, -0.0384212844073772f, -0.0493005812168121f,
+// 0.0995424166321754f, -0.1330551058053970f, -0.0162966735661030f,
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+// 0.0281810034066439f, -0.0192590244114399f, -0.1801510006189346f,
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+// 0.1838940382003784f, -0.0334108769893646f, -0.0056527559645474f,
+// 0.0394067317247391f, -0.0043484922498465f, 0.0189596451818943f,
+// 0.0689497888088226f, -0.0914151892066002f, 0.0117832133546472f,
+// -0.3677459359169006f, 0.2733487188816071f, 0.2462087124586105f,
+// -0.1202889606356621f, 0.5017691254615784f, -0.3640452027320862f,
+// 0.1674048304557800f, -0.0674246251583099f, -0.1233489289879799f,
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+// -0.2665018439292908f, -0.5659303665161133f, -0.1228908076882362f,
+// 0.1278892308473587f, -0.1163613647222519f, -0.1888944655656815f,
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+// 0.2548401057720184f, 0.1270710378885269f, 0.0852860063314438f,
+// 0.2557488679885864f, -0.3595704734325409f, -0.0471774712204933f,
+// 0.0538053140044212f, 0.0809341818094254f, -0.1914331763982773f,
+// 0.1716655939817429f, 0.3202314674854279f, -0.3923493623733521f,
+// 0.1125030964612961f, 0.3250627219676971f, -0.1821906417608261f,
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+// 0.1454582065343857f, -0.4706846475601196f, 0.0226443260908127f,
+// 0.1180284991860390f, 0.1446667313575745f, 0.1008275449275970f,
+// 0.0341080240905285f, 0.1527266055345535f, -0.1676338165998459f,
+// -0.0441326051950455f, 0.1138002127408981f, 0.0673571079969406f,
+// 0.0358247868716717f, 0.2864479124546051f, -0.0666197612881660f,
+// -0.0407672971487045f, -0.0683787986636162f, -0.0166290681809187f,
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+// 0.2726861238479614f, 0.0612599477171898f, 0.1119486987590790f,
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+// -0.0624030306935310f, -0.1774487048387527f, 0.0290118958801031f,
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+// 0.0830852836370468f, -0.0983831956982613f, 0.0826247334480286f,
+// -0.0027033588849008f, -0.0131979379802942f, 0.0574866682291031f,
+// 0.6030196547508240f, 0.4371406733989716f, 0.6748744845390320f,
+// -1.0458281040191650f, 0.6835021376609802f, -0.7192609310150146f,
+// 0.7533596158027649f, 0.6062704324722290f, -0.2861645221710205f,
+// 0.3679776191711426f, 0.3583964109420776f, 0.2588345408439636f,
+// 0.2232366204261780f, 0.2025820910930634f, -0.1513050347566605f,
+// 0.2359194457530975f, -0.0605516470968723f, -0.1811601966619492f,
+// 0.1182630658149719f, -0.1828397065401077f, 0.0849191471934319f,
+// 0.1505678892135620f, -0.1207071170210838f, 0.1417415738105774f,
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+// -0.0872730687260628f, 0.0884886756539345f, -0.0896501764655113f,
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+// -0.0527526102960110f, 0.0488304011523724f, -0.1775394231081009f,
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+// 0.3322355449199677f, -0.1445040702819824f, 0.1586818099021912f,
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+// 0.3064008057117462f, -0.2797845005989075f, -0.2062651962041855f,
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+// 0.2774669528007507f, -0.0777032822370529f, 0.0856506824493408f,
+// 0.1406725198030472f, 0.1683871001005173f, 0.1999176293611526f,
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+// -0.1018841117620468f, 0.1689682602882385f, 0.2429608702659607f,
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+// -0.4627757370471954f, -0.2212356179952621f, -0.0327787920832634f,
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+// -0.1991052478551865f, -0.0564929805696011f, -0.2049905061721802f,
+// -0.0449820719659328f, 0.3604230582714081f, 0.3397291600704193f,
+// 0.2521075606346130f, 0.0271630324423313f, 0.2400465458631516f,
+// -0.3700110614299774f, 0.2348449528217316f, 0.1587323397397995f,
+// 0.0492181219160557f, 0.1936464309692383f, -0.0607553981244564f,
+// 0.1058558374643326f, -0.0023343835491687f, 0.1047520712018013f,
+// -0.0106239160522819f, 0.0786515176296234f, -0.1909460276365280f,
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+// -0.2092219740152359f, 0.0619665347039700f, -0.2257533371448517f,
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+// -0.2055506855249405f, -0.1297843903303146f, 0.1179552972316742f,
+// 0.0746687278151512f, 0.0652263537049294f, 0.1312853842973709f,
+// 0.1604429632425308f, -0.3699014484882355f, 0.2807027995586395f,
+// -0.1730733066797256f, 0.0746814236044884f, -0.0702038034796715f,
+// -0.0716262310743332f, 0.2064413428306580f, -0.3605144321918488f,
+// 0.3668577373027802f, -0.3688357770442963f, 0.2401331365108490f,
+// -0.2826835513114929f, 0.0622708834707737f, -0.0208686999976635f,
+// 0.0958568006753922f, -0.1426644772291183f, 0.0804482325911522f,
+// -0.1305373162031174f, 0.0087690958753228f, -0.0017968157771975f,
+// 0.0116403223946691f, 0.2186574041843414f, -0.0839144811034203f,
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+// -0.2441837787628174f, 0.1201303824782372f, -0.0308279208838940f,
+// 0.1359865665435791f, 0.0733170956373215f, -0.2901234626770020f,
+// -0.0615523904561996f, -0.1423406004905701f, 0.1430884301662445f,
+// 0.0844142213463783f, 0.2157065272331238f, 0.0734384581446648f,
+// 0.1639619022607803f, 0.0335504896938801f, -0.0849560722708702f,
+// 0.0119116473942995f, 0.0246604420244694f, -0.0384564585983753f,
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+// 0.0460431203246117f, 0.0458285398781300f, 0.1656490713357925f,
+// 0.0317273959517479f, -0.2480902522802353f, -0.0453086122870445f,
+// 0.0665298253297806f, -0.1760722100734711f, 0.0019363120663911f,
+// -0.0650781542062759f, 0.1495559513568878f, 0.1851104050874710f,
+// 0.0667488351464272f, 0.1458794921636581f, -0.0332851782441139f,
+// 0.0353490002453327f, 0.1401965171098709f, 0.0560675524175167f,
+// -0.1265243589878082f, 0.0624196603894234f, -0.0037329343613237f,
+// 0.0574449375271797f, -0.1051802337169647f, 0.2338313609361649f,
+// 0.0624222084879875f, 0.1966224759817123f, 0.0058572934940457f,
+// 0.0136102577671409f, 0.1309786289930344f, 0.0882922336459160f,
+// 0.0736867412924767f, 0.0118357334285975f, -0.0233143512159586f,
+// -0.0445005558431149f, -0.0545534491539001f, 0.1651175320148468f,
+// 0.0269459560513496f, 0.2433619797229767f, 0.0620021112263203f,
+// 0.0133079299703240f, 0.0045060589909554f, -0.0139698665589094f,
+// -0.0119789270684123f, 0.0135429874062538f, 0.2158075720071793f,
+// -0.0665057599544525f, -0.0862092375755310f, 0.0435760542750359f,
+// 0.0496985502541065f, 0.0267252195626497f, -0.2276500761508942f,
+// 0.0193444583564997f, 0.1079035401344299f, -0.0266093406826258f,
+// -0.0669950172305107f, -0.0084517551586032f, -0.0067852870561182f,
+// 0.1274545937776566f, -0.1045455113053322f, -0.1738298833370209f,
+// -0.1352054476737976f, 0.0744953602552414f, -0.2389223724603653f,
+// -0.1215361207723618f, -0.0431345812976360f, 0.0246959067881107f,
+// 0.1211705207824707f, -0.1905250102281570f, 0.0299821011722088f,
+// 0.0511014685034752f, -0.0247416533529758f, 0.1018844768404961f,
+// 0.0641893297433853f, 0.0498286187648773f, 0.0601293668150902f,
+// -0.1305269449949265f, -0.0628710687160492f, 0.0993981510400772f,
+// 0.0269540883600712f, 0.0007375808199868f, -0.1308915615081787f,
+// 0.0102985808625817f, 0.0237090382725000f, 0.0174226295202971f,
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+// -0.0860218331217766f, -0.1432624608278275f, 0.0902495831251144f,
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+// -0.0896481573581696f, 0.0590362139046192f, -0.1021478995680809f,
+// 0.0433662608265877f, 0.1088711246848106f, -0.0031521392520517f,
+// -0.0250228065997362f, -0.0163611229509115f, -0.1062580719590187f,
+// -0.0785095244646072f, -0.0452989488840103f, -0.1168002113699913f,
+// 0.0281316563487053f, -0.0774543955922127f, 0.1120008677244186f,
+// -0.0363741591572762f, -0.0109504833817482f, 0.1299537718296051f,
+// 0.1493279039859772f, -0.0711448341608047f, 0.0220136232674122f,
+// -0.1012632623314857f, 0.0365059152245522f, 0.1091644465923309f,
+// -0.0112483333796263f, -0.0669699013233185f, -0.2129128277301788f,
+// 0.0366214998066425f, -0.0278309006243944f, -0.0867262631654739f,
+// -0.0764938145875931f, -0.2110697031021118f, 0.0234866160899401f,
+// -0.0582616105675697f, 0.0595317631959915f, 0.0257988665252924f,
+// -0.1354613304138184f, -0.0274840854108334f, 0.1965632438659668f,
+// -0.1890367418527603f, 0.1011053696274757f, -0.1377941817045212f,
+// 0.0566991865634918f, 0.0383193194866180f, -0.2094675898551941f,
+// 0.1116235032677650f, -0.0146881518885493f, 0.0547494962811470f,
+// -0.0329081565141678f, 0.0926065742969513f, -0.0248326230794191f,
+// 0.0121662626042962f, 0.0858743190765381f, -0.1027604490518570f,
+// -0.1116288378834724f, -0.1267064958810806f, -0.3230932652950287f,
+// 0.0136316260322928f, -0.1268850713968277f, -0.1384650766849518f,
+// 0.0115729011595249f, -0.0187231246381998f, -0.1109136790037155f,
+// -0.0268277823925018f, 0.0839694067835808f, -0.1113827899098396f,
+// 0.0879323557019234f, 0.0896763503551483f, 0.1344237625598907f,
+// 0.1178349405527115f, -0.1419216990470886f, -0.3088560104370117f,
+// -0.0774299353361130f, 0.0022350065410137f, -0.1719482988119125f,
+// 0.0611945912241936f, -0.1127103269100189f, -0.0548406764864922f,
+// -0.0054743262007833f, 0.0013789935037494f, 0.1767961978912354f,
+// 0.1043517738580704f, 0.0263401735574007f, 0.0937112942337990f,
+// -0.0857565924525261f, -0.1792472451925278f, -0.1548034846782684f,
+// -0.1498838961124420f, -0.0553631298243999f, -0.1114140972495079f,
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+// -0.0524651892483234f, 0.0014775666641071f, -0.0521595589816570f,
+// 0.1445611715316772f, 0.0465734787285328f, -0.0138005092740059f,
+// -0.1332941204309464f, -0.0417342409491539f, -0.0468001589179039f,
+// 0.0246353242546320f, -0.4072751104831696f, -0.0195949859917164f,
+// 0.0446222573518753f, 0.1785507649183273f, 0.0296881720423698f,
+// 0.0606773905456066f, -0.1356818825006485f, 0.0024880999699235f,
+// -0.1517279893159866f, 0.0463006570935249f, 0.1270211338996887f,
+// 0.2449791878461838f, -0.2020605206489563f, 0.0326733104884624f,
+// -0.1124228760600090f, -0.2459415793418884f, -0.0430964641273022f,
+// 0.0484786741435528f, 0.3052351176738739f, -0.2601210772991180f,
+// 0.0981012433767319f, -0.0489771962165833f, -0.2368840724229813f,
+// -0.0159478317946196f, -0.0230305846780539f, 0.1484253853559494f,
+// -0.1377372145652771f, -0.2690135836601257f, -0.0288745146244764f,
+// -0.1052068471908569f, -0.0306154824793339f, -0.1046887859702110f,
+// -0.0671103671193123f, -0.0565510168671608f, -0.1435144692659378f,
+// -0.0541116781532764f, 0.2201123982667923f, 0.2937335371971130f,
+// -0.0401249602437019f, 0.1331492960453033f, 0.1380819529294968f,
+// 0.0775337293744087f, -0.2225734442472458f, -0.0531511083245277f,
+// -0.0234672185033560f, -0.2191170305013657f, 0.1562778055667877f,
+// -0.0059010568074882f, 0.3464935719966888f, 0.0296747740358114f,
+// -0.1382914632558823f, 0.1725502908229828f, 0.1316856145858765f,
+// 0.0964523702859879f, 0.1991766691207886f, 0.2431268393993378f,
+// -0.1414196938276291f, 0.0756529867649078f, 0.1816277951002121f,
+// 0.0621179081499577f, -0.0122482189908624f, -0.0883079767227173f,
+// 0.0408411175012589f, -0.1722108125686646f, 0.1402370780706406f,
+// -0.0867809355258942f, -0.1257717460393906f, -0.0528866462409496f,
+// -0.1201027929782867f, -0.0225917510688305f, 0.1187544316053391f,
+// -0.1195028200745583f, -0.0649442672729492f, -0.0635389536619186f,
+// -0.0258640311658382f, -0.0589111410081387f, -0.0191753432154655f,
+// -0.0004646728630178f, -0.1238084509968758f, 0.0948118716478348f,
+// -0.0713055953383446f, -0.1223599687218666f, -0.2208527177572250f,
+// 0.0794220268726349f, -0.0119987884536386f, -0.0009825591696426f,
+// -0.0039038653485477f, -0.0823622494935989f, 0.0951793342828751f,
+// 0.0644549503922462f, 0.1442252546548843f, 0.0537418127059937f,
+// 0.2005795240402222f, -0.0517650321125984f, 0.0672174245119095f,
+// 0.2256665229797363f, -0.4035553634166718f, 0.0735207200050354f,
+// -0.2436017990112305f, -0.0315279588103294f, -0.0889356061816216f,
+// 0.0211600847542286f, -0.1388427466154099f, -0.0197546537965536f,
+// 0.0056235031224787f, 0.0294467248022556f, 0.0134874321520329f,
+// 0.0883866325020790f, -0.1463381797075272f, -0.2001271396875381f,
+// 0.0967670604586601f, -0.0658679679036140f, -0.1636702567338943f,
+// -0.0774376392364502f, -0.1282687485218048f, -0.2215309739112854f,
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+// 0.0485155060887337f, -0.1712456792593002f, -0.0919748172163963f,
+// 0.0118346037343144f, -0.0450698845088482f, 0.2785760164260864f,
+// -0.1624427735805511f, -0.0155313955619931f, 0.0319835022091866f,
+// 0.0633366480469704f, -0.0772280395030975f, 0.2236471772193909f,
+// 0.0803037360310555f, 0.1346082985401154f, -0.0949643328785896f,
+// -0.0687158778309822f, 0.0904182270169258f, 0.1211263462901115f,
+// -0.0237875543534756f, -0.0000363590879715f, 0.0483787693083286f,
+// -0.0197730027139187f, 0.0160310827195644f, -0.1804943084716797f,
+// 0.2300530076026917f, -0.0222214870154858f, 0.2709228396415710f,
+// -0.0445593856275082f, -0.1359429508447647f, -0.1343242377042770f,
+// 0.1931809633970261f, 0.0570430830121040f, 0.0790255889296532f,
+// -0.0903789624571800f, -0.0654287263751030f, 0.1942499727010727f,
+// 0.0578285567462444f, 0.1196963191032410f, -0.0138105032965541f,
+// -0.1667324006557465f, 0.0814348831772804f, 0.1442107111215591f,
+// 0.0006640531355515f, -0.0232254397124052f, -0.2734210193157196f,
+// -0.0441328510642052f, -0.1739105582237244f, 0.0876096338033676f,
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+// -0.2029397338628769f, 0.1217761337757111f, 0.2023519724607468f,
+// -0.1296245604753494f, 0.2109632939100266f, 0.0684172511100769f,
+// 0.0704121217131615f, -0.0819868370890617f, -0.1013147681951523f,
+// -0.0275268293917179f, -0.0671682357788086f, 0.1840820759534836f,
+// 0.0577620156109333f, -0.1444515287876129f, -0.0450365841388702f,
+// 0.1695894300937653f, -0.0955168157815933f, 0.0939782559871674f,
+// 0.1040040105581284f, 0.0162853673100471f, 0.1028079912066460f,
+// -0.1431438773870468f, 0.0778040140867233f, 0.0918401479721069f,
+// 0.1111955195665359f, -0.0592624396085739f, 0.0895786061882973f,
+// 0.0168430879712105f, -0.0375135131180286f, -0.0900413468480110f,
+// 0.1867190897464752f, 0.0517647042870522f, -0.2088749110698700f,
+// 0.0594537742435932f, -0.0396091043949127f, 0.1518417000770569f,
+// 0.0447514243423939f, 0.0611500814557076f, 0.0713938549160957f,
+// -0.0215239543467760f, -0.1958498209714890f, 0.1138185411691666f,
+// -0.0921332165598869f, 0.0076367985457182f, 0.2066366672515869f,
+// 0.0272970218211412f, -0.0120848473161459f, -0.0982346609234810f,
+// -0.0047718952409923f, -0.0331688597798347f, 0.0950364768505096f,
+// 0.1197607144713402f, 0.0996351912617683f, -0.0250526405870914f,
+// -0.0319690890610218f, -0.0175906196236610f, -0.1142450571060181f,
+// 0.0274251718074083f, -0.0812403336167336f, -0.0801825299859047f,
+// -0.0643264800310135f, -0.0333987846970558f, 0.0060658529400826f,
+// 0.1505826413631439f, 0.2158137112855911f, -0.1362227648496628f,
+// 0.0662486925721169f, 0.0708885937929153f, 0.0985234081745148f,
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+// -0.0167894847691059f, 0.1777824014425278f, -0.3090494573116302f,
+// 0.0542610287666321f, 0.0228850301355124f, -0.0855251997709274f,
+// -0.0969798639416695f, 0.0336831435561180f, 0.0232908558100462f,
+// -0.1162769496440887f, -0.0513251386582851f, 0.2468192428350449f,
+// 0.1636345386505127f, -0.1654557883739471f, 0.2321714460849762f,
+// -0.0831245854496956f, 0.0528251938521862f, -0.0293914712965488f,
+// 0.0065994830802083f, -0.0041343523189425f, -0.1158747151494026f,
+// 0.0246581863611937f, -0.0508146733045578f, 0.1395989507436752f,
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+// -0.0023285900242627f, -0.1161763668060303f, -0.1900463253259659f,
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+// -0.0054727848619223f, 0.1848051846027374f, -0.0753328278660774f,
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+// 0.1380319595336914f, -0.0838481709361076f, -0.0462381169199944f,
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+// -0.0134278656914830f, 0.0034120592754334f, 0.2660149633884430f,
+// -0.0864097997546196f, 0.0335543602705002f, -0.0602160282433033f,
+// -0.0093337111175060f, -0.0683209225535393f, -0.0501621104776859f,
+// -0.1126521676778793f, 0.0491046085953712f, 0.0200583152472973f,
+// 0.0089597720652819f, 0.1254414916038513f, -0.1463211774826050f,
+// 0.1735193133354187f, -0.0626413449645042f, -0.0762193873524666f,
+// 0.1059594377875328f, -0.1044549718499184f, -0.4073096811771393f,
+// -0.0820173695683479f, 0.0930420383810997f, -0.0404611565172672f,
+// 0.0223743915557861f, -0.0496171601116657f, 0.0476595759391785f,
+// 0.0556484051048756f, -0.1079509630799294f, -0.0368140488862991f,
+// -0.1155155375599861f, -0.1136842519044876f, 0.0755930170416832f,
+// -0.0648834705352783f, 0.0676693692803383f, 0.0495222695171833f,
+// -0.1087670996785164f, 0.1072775349020958f, -0.0078140553086996f,
+// -0.1024337038397789f, -0.0746596157550812f, 0.1973480433225632f,
+// 0.1820084601640701f, 0.0613411739468575f, 0.1552209705114365f,
+// -0.0372941642999649f, -0.1379967480897903f, 0.2705684602260590f,
+// -0.0465910211205482f, -0.0094156088307500f, -0.3406550586223602f,
+// 0.0104286028072238f, -0.1576771289110184f, 0.1547662019729614f,
+// -0.1583909541368484f, -0.1663937270641327f, 0.0180264115333557f,
+// -0.0255260057747364f, 0.0344384796917439f, 0.2107715606689453f,
+// 0.0890299752354622f, -0.1458379924297333f, -0.1202902570366859f,
+// 0.1571009457111359f, 0.1407037675380707f, 0.0790772065520287f,
+// -0.0936755910515785f, 0.0537285692989826f, 0.0481917858123779f,
+// 0.0771145671606064f, -0.0169954374432564f, -0.1293322741985321f,
+// -0.0561429075896740f, -0.0888760238885880f, -0.1739718019962311f,
+// -0.1589372307062149f, 0.0565973930060863f, 0.0113947289064527f,
+// -0.0131669780239463f, 0.0000350170703314f, -0.1640058457851410f,
+// 0.0952663198113441f, 0.1251005828380585f, -0.0316342674195766f,
+// -0.1253357380628586f, -0.0750626325607300f, -0.0836123973131180f,
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+// -0.0835765972733498f, 0.1584283858537674f, 0.1895041167736053f,
+// 0.0523229762911797f, 0.0354408770799637f, 0.0939576849341393f,
+// 0.1152569204568863f, -0.0655694082379341f, -0.1429115533828735f,
+// 0.0404233261942863f, 0.2876803874969482f, 0.0120913833379745f,
+// 0.0740013271570206f, 0.1444854587316513f, -0.1622543334960938f,
+// -0.0956332832574844f, 0.1268942803144455f, 0.0520098172128201f,
+// 0.0884140655398369f, 0.1115978285670280f, -0.0089265545830131f,
+// 0.0046780006960034f, 0.1327392160892487f, -0.1371010541915894f,
+// -0.0529159456491470f, 0.0800568684935570f, -0.0942933708429337f,
+// 0.0369822643697262f, -0.0733163878321648f, 0.0627497062087059f,
+// -0.0597207732498646f, 0.0157051607966423f, -0.1479590088129044f,
+// -0.0393161699175835f, -0.0625243186950684f, 0.1309251487255096f,
+// 0.1488112360239029f, -0.0004657934478018f, -0.3043886423110962f,
+// 0.0295499898493290f, 0.0136356642469764f, 0.1771257668733597f,
+// -0.1311923116445541f, 0.2537534236907959f, 0.1910816282033920f,
+// 0.0010252989595756f, -0.1964323669672012f, 0.0147995306178927f,
+// -0.0162061844021082f, 0.1482839435338974f, -0.0898823887109756f,
+// 0.0122741376981139f, 0.0321864262223244f, 0.2937439680099487f,
+// -0.0326930917799473f, 0.0077670384198427f, 0.1089275553822517f,
+// -0.0037555508315563f, 0.0052666412666440f, -0.4776847362518311f,
+// 0.0617485530674458f, -0.0266661848872900f, -0.0553902238607407f,
+// 0.0003519214515109f, 0.0188715606927872f, -0.1635286957025528f,
+// -0.0382419675588608f, 0.1135704666376114f, -0.4005137681961060f,
+// -0.0400396808981895f, 0.0090307667851448f, 0.1095584481954575f,
+// 0.0131932199001312f, 0.0825238004326820f, 0.3803710341453552f,
+// -0.0034464488271624f, 0.0159909073263407f, 0.3099822103977203f,
+// 0.0104706399142742f, -0.0997653901576996f, -0.2072687000036240f,
+// 0.0261683370918036f, 0.0484369918704033f, -0.2942692637443542f,
+// 0.0050360993482172f, 0.0098741753026843f, -0.2513394057750702f,
+// -0.0639532953500748f, 0.0093299029394984f, 0.0971275269985199f,
+// 0.0771611407399178f, -0.0235131941735744f, 0.0862761735916138f,
+// -0.0130971865728498f, -0.0475809574127197f, -0.5667194128036499f,
+// 0.0866827890276909f, 0.0082241026684642f, -0.0771675035357475f,
+// 0.0563929826021194f, -0.1127800866961479f, 0.1122357323765755f,
+// 0.1622539162635803f, -0.1736394762992859f, 0.0672124847769737f,
+// 0.0145556498318911f, 0.2034469842910767f, 0.0382831990718842f,
+// -0.0917794927954674f, -0.0244791470468044f, -0.0268108621239662f,
+// -0.0891593545675278f, -0.0724903270602226f, 0.0865140706300735f,
+// 0.0640864819288254f, -0.2805127203464508f, 0.1941776871681213f,
+// -0.1174904704093933f, 0.0510195083916187f, 0.0675572752952576f,
+// -0.1007992774248123f, 0.0064969630911946f, 0.1337445825338364f,
+// -0.1113895624876022f, 0.0842561721801758f, 0.1084996834397316f,
+// 0.0019049957627431f, 0.0579368919134140f, 0.1545345634222031f,
+// 0.2663949728012085f, 0.0314235016703606f, -0.2248091250658035f,
+// 0.0485050380229950f, -0.0275516882538795f, -0.0839130654931068f,
+// -0.0287241861224174f, 0.2260170429944992f, 0.0122557450085878f,
+// 0.0899791195988655f, -0.1251325458288193f, -0.0380256883800030f,
+// -0.0073536806739867f, 0.2115486860275269f, -0.0735085308551788f,
+// -0.1127746552228928f, -0.2698718607425690f, -0.1971575766801834f,
+// 0.0286440812051296f, 0.0301675014197826f, 0.0767932087182999f,
+// -0.0738875046372414f, 0.1965285241603851f, 0.0306107215583324f,
+// 0.1099971085786819f, -0.0899861007928848f, 0.0392918363213539f,
+// -0.0195813234895468f, -0.0369387380778790f, -0.0036821796093136f,
+// 0.0381225235760212f, 0.0636682286858559f, -0.1438088417053223f,
+// 0.0226791575551033f, 0.2841083109378815f, -0.0170288216322660f,
+// -0.2948448359966278f, -0.0924745202064514f, 0.6946722269058228f,
+// 0.8847374916076660f, 0.2898308336734772f, 0.0329158380627632f,
+// -0.0647436007857323f, -0.2006756514310837f,
+// -0.5920046567916870f, 1.1353050470352173f, 0.8455220460891724f,
+// 0.3792351782321930f, 0.8663153648376465f, -0.8824025392532349f,
+// 0.2501059174537659f, -0.0269941892474890f, 0.1046612635254860f,
+// -0.0766939148306847f, -0.1639057099819183f, 0.1105236262083054f,
+// 0.0134973004460335f, -0.1443326175212860f, 0.0272236689925194f,
+// -0.1030777469277382f, 0.0507695637643337f, 0.3107487261295319f,
+// -0.0024800256360322f, 0.0308995246887207f, 0.0198377296328545f,
+// -0.1880303621292114f, 0.1784047633409500f, -0.0735245496034622f,
+// 0.1128673627972603f, 0.0967759862542152f, 0.0827022045850754f,
+// -0.0337634384632111f, -0.0588248521089554f, -0.2811493277549744f,
+// -0.1439599096775055f, 0.1034760475158691f, 0.2266758531332016f,
+// 0.3002040088176727f, 0.2780060470104218f, -0.2512286901473999f,
+// 0.1240329518914223f, -0.1117806509137154f, -0.0286076273769140f,
+// -0.0963207036256790f, 0.0303900446742773f, 0.2914741337299347f,
+// 0.0530045405030251f, -0.1428391784429550f, 0.0397147648036480f,
+// -0.0103764524683356f, 0.2597011327743530f, 0.1202799826860428f,
+// -0.2659638822078705f, 0.1566831320524216f, -0.1807757467031479f,
+// -0.0963153243064880f, 0.1121245548129082f, 0.0881196483969688f,
+// 0.2475219368934631f, 0.2264259755611420f, 0.0162743069231510f,
+// -0.0355165414512157f, 0.1059609279036522f, 0.0841223523020744f,
+// -0.1784930974245071f, 0.0652983188629150f, -0.1424558609724045f,
+// -0.2222695797681808f, -0.2194864302873611f, -0.0264761932194233f,
+// -0.0614231973886490f, 0.1944721341133118f, -0.2740547955036163f,
+// -0.1009605824947357f, -0.0033164452761412f, -0.1308415979146957f,
+// -0.1103593185544014f, -0.1092289760708809f, 0.0074873212724924f,
+// -0.1155094131827354f, 0.1134597659111023f, -0.0929021090269089f,
+// 0.0187796335667372f, 0.1766432225704193f, 0.1746120601892471f,
+// -0.0385249219834805f, 0.0091941440477967f, -0.0781163722276688f,
+// -0.1386806964874268f, -0.0148799028247595f, -0.0725540071725845f,
+// -0.0590873584151268f, -0.2115356922149658f, -0.0732565894722939f,
+// -0.1327400803565979f, -0.0541311316192150f, -0.1206098571419716f,
+// 0.4058507084846497f, -0.1362764537334442f, -0.3332628905773163f,
+// -0.1969233602285385f, -0.1920680254697800f, 0.4149487614631653f,
+// 0.1406662017107010f, 0.2028126567602158f, -0.0932444706559181f,
+// 0.1975253969430923f, 0.1260168254375458f, -0.2170890569686890f,
+// -0.0990178138017654f, -0.0966763421893120f, -0.0382168628275394f,
+// -0.0209532026201487f, -0.3022250235080719f, -0.0534277483820915f,
+// 0.2183794528245926f, -0.0249309614300728f, -0.1678454875946045f,
+// -0.2866469025611877f, 0.1769800186157227f, 0.1322986483573914f,
+// -0.0423364266753197f, 0.0810143500566483f, 0.0830262154340744f,
+// -0.0669728219509125f, -0.1359617561101913f, 0.6124252080917358f,
+// 0.2248876094818115f, -0.1370726078748703f, 0.1045518815517426f,
+// 0.1567987352609634f, -0.2825512588024139f, -0.0329426415264606f,
+// 0.1612363010644913f, -0.3049055039882660f, 0.1571613550186157f,
+// -0.2454168051481247f, -0.0889087766408920f, 0.0880006849765778f,
+// 0.1697432547807693f, 0.0214425269514322f, 0.2920794785022736f,
+// 0.2444104701280594f, -0.4035662412643433f, -0.1139396876096725f,
+// 0.3155550360679626f, -0.2999731302261353f, 0.0579635985195637f,
+// -0.0683231949806213f, 0.0567277744412422f, 0.4111801981925964f,
+// -0.1985262781381607f, -0.0896092504262924f, -0.1199427023530006f,
+// -0.3451531231403351f, 0.3490760624408722f, 0.2757760584354401f,
+// -0.2055836617946625f, -0.0227132346481085f, -0.1136761829257011f,
+// -0.0526759847998619f, -0.1379816681146622f, -0.1963548213243484f,
+// -0.1149208098649979f, 0.1553239673376083f, -0.0631523802876472f,
+// 0.4324884116649628f, 0.3179998397827148f, 0.0206474624574184f,
+// -0.2977500855922699f, -0.2926046252250671f, 0.0247984621673822f,
+// -0.0330708362162113f, 0.1534693688154221f, 0.2944041192531586f,
+// -0.1253813505172729f, -0.1046770364046097f, 0.1691714376211166f,
+// -0.1032376363873482f, 0.0218945071101189f, 0.1150633394718170f,
+// -0.2812787890434265f, -0.0824627578258514f, -0.3492566943168640f,
+// 0.1592484265565872f, 0.1517154872417450f, 0.0650286301970482f,
+// -0.0485412999987602f, -0.0144279375672340f, 0.1546634286642075f,
+// -0.0176712833344936f, -0.1169971078634262f, -0.1387049555778503f,
+// 0.2800461351871490f, 0.0763742178678513f, 0.0694008097052574f,
+// -0.0807223170995712f, -0.1045925319194794f, 0.0437939390540123f,
+// 0.3020221889019012f, -0.1329954713582993f, 0.1459405720233917f,
+// -0.0243461374193430f, -0.0137006007134914f, -0.0020017435308546f,
+// 0.1786081790924072f, 0.2092578709125519f, 0.3499994874000549f,
+// 0.2089757770299911f, 0.1789388656616211f, 0.0092325843870640f,
+// -0.0171269997954369f, 0.1325661987066269f, 0.2211400568485260f,
+// 0.2654303908348083f, -0.1288143694400787f, 0.2509453296661377f,
+// -0.1747971624135971f, 0.0299847573041916f, 0.2846413254737854f,
+// 0.1819767951965332f, 0.1559792608022690f, 0.1661557108163834f,
+// -0.0762998908758163f, 0.1101708933711052f, -0.1639545708894730f,
+// -0.0033727244008332f, 0.2922022640705109f, 0.3793787956237793f,
+// 0.0179675519466400f, -0.1955338418483734f, -0.2286965996026993f,
+// -0.1629247516393661f, 0.2452561557292938f, 0.2403077930212021f,
+// -0.1173960417509079f, -0.1350169926881790f, -0.0212057996541262f,
+// 0.1287294030189514f, -0.1776470839977264f, 0.2109401226043701f,
+// -0.1590826064348221f, 0.1505362093448639f, 0.1648064553737640f,
+// -0.1415051072835922f, -0.0392571501433849f, 0.0087896268814802f,
+// 0.0051480610854924f, 0.4756706953048706f, 0.3486688733100891f,
+// -0.0782877877354622f, -0.1254254579544067f, -0.0479893758893013f,
+// 0.0300150308758020f, -0.0621269457042217f, -0.1815799623727798f,
+// 0.0061633028090000f, -0.1681788265705109f, 0.5754742026329041f,
+// 0.2969702184200287f, 0.1426486223936081f, 0.0014448392903432f,
+// -0.6195610165596008f, 0.3333047926425934f, 0.0423246249556541f,
+// 0.3793240785598755f, -0.0405663475394249f, 0.2127478420734406f,
+// -0.1615688055753708f, -0.1618401557207108f, 0.0595127753913403f,
+// 0.1603180319070816f, 0.0501020886003971f, -0.1156788915395737f,
+// -0.0954973474144936f, 0.1379464268684387f, -0.2055423706769943f,
+// -0.0612994059920311f, 0.0264420881867409f, -0.2100935280323029f,
+// -0.1798245012760162f, -0.1122967898845673f, -0.0015275938203558f,
+// -0.0191588010638952f, -0.0081481840461493f, 0.0125901913270354f,
+// 0.0920227542519569f, -0.0873022526502609f, -0.0141603443771601f,
+// -0.0528484135866165f, -0.2281163632869720f, 0.0167977046221495f,
+// 0.0642863810062408f, -0.0990109518170357f, -0.0797733590006828f,
+// -0.0844631567597389f, -0.1045793741941452f, 0.1044271737337112f,
+// 0.0284633785486221f, 0.0761338174343109f, -0.0565029680728912f,
+// -0.0263414438813925f, -0.1907089352607727f, -0.0235156547278166f,
+// 0.0114850774407387f, -0.3895348608493805f, 0.1486459225416183f,
+// 0.0347057729959488f, 0.0503906086087227f, 0.0544775910675526f,
+// 0.0418283194303513f, -0.0579061992466450f, -0.1753562092781067f,
+// -0.1381318569183350f, 0.5436702966690063f, -0.0600630640983582f,
+// 0.0366583019495010f, 0.0412317439913750f, -0.0085185635834932f,
+// 0.1328828036785126f, -0.8007208108901978f, -0.0812456831336021f,
+// -0.2384399175643921f, 0.2161929309368134f, -0.0091815879568458f,
+// 0.0533405132591724f, -0.1034200116991997f, -0.1246838644146919f,
+// -0.2033324539661407f, -0.1750406324863434f, 0.0331273414194584f,
+// -0.0671958923339844f, 0.1816132068634033f, 0.0386656336486340f,
+// -0.0361556969583035f, -0.0347995311021805f, -0.1440780013799667f,
+// -0.1529785543680191f, -0.0504007488489151f, 0.1866478025913239f,
+// 0.0500442646443844f, -0.0199352614581585f, -0.0319508500397205f,
+// 0.0431500971317291f, 0.1564645916223526f, 0.0568574070930481f,
+// -0.0434417873620987f, -0.0167464334517717f, 0.0427590161561966f,
+// 0.0345743410289288f, 0.1014467030763626f, -0.0306274220347404f,
+// 0.0880514159798622f, 0.0682316794991493f, 0.0886527299880981f,
+// 0.0404376052320004f, 0.1815847009420395f, 0.0895976051688194f,
+// -0.0055911703966558f, -0.1546121090650558f, -0.1519525200128555f,
+// -0.2077405005693436f, 0.0300522744655609f, -0.0490227825939655f,
+// -0.0730589032173157f, 0.0821001902222633f, -0.0612629279494286f,
+// -0.0011816809419543f, -0.2451617866754532f, -0.0881977602839470f,
+// -0.1610833406448364f, 0.0583012625575066f, -0.0559430718421936f,
+// -0.0641824230551720f, 0.1561771482229233f, -0.0724386796355247f,
+// -0.0394818708300591f, 0.1269833445549011f, 0.0097798136994243f,
+// 0.1472719758749008f, 0.1737971007823944f, -0.0346882119774818f,
+// 0.0562359653413296f, 0.0555336065590382f, 0.0694529786705971f,
+// 0.1553186476230621f, 0.2104387581348419f, -0.0189249664545059f,
+// 0.2972865700721741f, -0.0696999207139015f, 0.0513410754501820f,
+// 0.0050645316950977f, 0.0765809044241905f, 0.1058170944452286f,
+// 0.0437974706292152f, -0.0911607369780540f, 0.0571125485002995f,
+// 0.0115104215219617f, 0.0473373644053936f, -0.0210942197591066f,
+// -0.0377595350146294f, 0.1031574532389641f, 0.0706454887986183f,
+// -0.1675054430961609f, 0.0522268190979958f, -0.0341175757348537f,
+// 0.0231215246021748f, -0.1711715161800385f, -0.0813240334391594f,
+// -0.1619275957345963f, -0.0258402135223150f, -0.0848204642534256f,
+// -0.0909969881176949f, -0.0130626549944282f, 0.0199521798640490f,
+// 0.0581375509500504f, -0.1913820356130600f, -0.0087797967717052f,
+// -0.2555371820926666f, 0.2163895219564438f, -0.0541884712874889f,
+// -0.0054308683611453f, 0.1111702620983124f, -0.1593284904956818f,
+// -0.0740808472037315f, 0.2224733531475067f, -0.0513053424656391f,
+// 0.1199584230780602f, 0.1922366470098495f, -0.0418727956712246f,
+// 0.0057660830207169f, 0.0032988502644002f, -0.0130077861249447f,
+// 0.0032098842784762f, -0.1140648648142815f, -0.2786416411399841f,
+// 0.2365940660238266f, -0.0835971459746361f, 0.1347545981407166f,
+// 0.0411320663988590f, 0.0220124889165163f, 0.0565601103007793f,
+// 0.1027578711509705f, -0.0236562602221966f, -0.0492152832448483f,
+// 0.1145111098885536f, 0.0823987200856209f, -0.0371027477085590f,
+// -0.1820722520351410f, 0.0697419866919518f, -0.0117600085213780f,
+// 0.0061167790554464f, 0.1297914534807205f, -0.1644172817468643f,
+// 0.0035404490772635f, -0.0173435471951962f, 0.0684957727789879f,
+// 0.1962365359067917f, -0.0922697186470032f, -0.0574829168617725f,
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+// -0.0680143013596535f, 0.0817918628454208f, 0.1640718877315521f,
+// 0.1476038545370102f, -0.0824649855494499f, 0.0354053340852261f,
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+// -0.1746877431869507f, -0.1511063277721405f, 0.1925625503063202f,
+// 0.1068346574902534f, 0.1089938879013062f, -0.1291730552911758f,
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+// -0.0128174517303705f, 0.2473996877670288f, -0.0166378486901522f,
+// 0.0278355088084936f, 0.0667702853679657f, -0.0225169640034437f,
+// 0.0414313077926636f, -0.0709195658564568f, -0.0837018266320229f,
+// 0.0780024081468582f, -0.1734661906957626f, -0.0656869783997536f,
+// 0.0733428597450256f, 0.0648859441280365f, 0.0039081568829715f,
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+// 0.0956663414835930f, -0.0496917814016342f, -0.0134499892592430f,
+// -0.0090498747304082f, 0.0530668087303638f, 0.0663934499025345f,
+// 0.0348068587481976f, -0.2587448060512543f, 0.0642520263791084f,
+// 0.0403823517262936f, -0.0967943742871284f, -0.0829663649201393f,
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+// 0.0543253570795059f, -0.1038152799010277f, 0.1079066693782806f,
+// 0.1137421876192093f, 0.3458546698093414f, -0.0292824059724808f,
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+// -0.1102837026119232f, 0.0656955316662788f, 0.1411650925874710f,
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+// -0.1234225332736969f, -0.0214791521430016f, -0.0154145797714591f,
+// 0.0057817567139864f, -0.0371882840991020f, -0.0113741355016828f,
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+// -0.1066118851304054f, 0.1174533665180206f, 0.0333828143775463f,
+// 0.1993417292833328f, 0.0822994783520699f, 0.0649797320365906f,
+// 0.0017323129577562f, -0.1601581871509552f, -0.0343425571918488f,
+// -0.3440316319465637f, -0.0734761059284210f, 0.0504644773900509f,
+// 0.0479135587811470f, -0.1764235496520996f, 0.0880582407116890f,
+// 0.0492375344038010f, -0.0246042050421238f, -0.0667268037796021f,
+// 0.0833064466714859f, 0.0814240351319313f, 0.0816468074917793f,
+// 0.0121304700151086f, 0.1622041910886765f, -0.0373354367911816f,
+// -0.0840902999043465f, -0.2629553675651550f, -0.0347244776785374f,
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+// -0.1193427368998528f, 0.0224290937185287f, 0.0312844291329384f,
+// 0.0265623200684786f, 0.1696560382843018f, -0.0459463782608509f,
+// 0.1745041757822037f, 0.0055804266594350f, 0.0449956469237804f,
+// -0.1228013038635254f, -0.0596689805388451f, 0.0362015962600708f,
+// -0.0076166610233486f, 0.0215802788734436f, 0.0014772025169805f,
+// 0.0050764256156981f, 0.1066617742180824f, 0.0446214117109776f,
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+// 0.1803253889083862f, -0.0106190061196685f, -0.0421919971704483f,
+// 0.0175105985254049f, 0.0559675022959709f, -0.0290975403040648f,
+// -0.1005601286888123f, -0.2521570920944214f, 0.0141723789274693f,
+// 0.0655799657106400f, 0.0713101327419281f, 0.0403162054717541f,
+// 0.1513010114431381f, 0.0840884074568748f, -0.0163238123059273f,
+// 0.0443655289709568f, -0.1442489922046661f, -0.0000286201830022f,
+// 0.0136300912126899f, -0.1334576159715652f, 0.0164101310074329f,
+// 0.1904837787151337f, -0.1002026721835136f, -0.0283141545951366f,
+// 0.1682114005088806f, 0.0764474719762802f, 0.0313815511763096f,
+// 0.0326362773776054f, 0.0413733534514904f, 0.0381677597761154f,
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+// -0.0336951725184917f, 0.0592118501663208f, -0.0255791656672955f,
+// -0.1788703203201294f, -0.0424824431538582f, -0.0367715694010258f,
+// -0.0307217221707106f, -0.2187304794788361f, -0.0655889734625816f,
+// 0.1212677061557770f, 0.1557164788246155f, -0.0285769384354353f,
+// -0.1712760329246521f, 0.1868131905794144f, 0.0552734136581421f,
+// -0.2206015884876251f, 0.0495539195835590f, -0.0995035320520401f,
+// -0.1543704867362976f, 0.5281047821044922f, -0.0593253932893276f,
+// -0.0451705045998096f, 0.0201253853738308f, 0.0321728512644768f,
+// 0.0964026004076004f, -0.0961164757609367f, 0.1040094271302223f,
+// 0.0742786750197411f, -0.1401248723268509f, -0.0840163081884384f,
+// 0.0366384945809841f, 0.0891197547316551f, -0.0114902108907700f,
+// 0.0139152454212308f, 0.1473547071218491f, -0.2027254253625870f,
+// 0.1427373737096786f, -0.0287272129207850f, -0.1060566604137421f,
+// -0.0806579440832138f, 0.0763323977589607f, -0.0669556781649590f,
+// 0.1879978775978088f, -0.2247862964868546f, -0.0880662053823471f,
+// 0.2293493449687958f, -0.0109390448778868f, 0.1007886081933975f,
+// 0.1003312617540359f, 0.0775149986147881f, 0.0610520839691162f,
+// -0.2086125314235687f, -0.0904736220836639f, -0.0374595001339912f,
+// -0.0181420184671879f, 0.0269959047436714f, -0.1535955369472504f,
+// 0.1103652119636536f, -0.0849204435944557f, 0.1647916138172150f,
+// 0.2755997478961945f, 0.0068362359888852f, 0.0731195583939552f,
+// 0.0991890877485275f, 0.0724862739443779f, 0.2324725985527039f,
+// 0.0449298508465290f, 0.0039884485304356f, 0.0414748154580593f,
+// 0.1115695834159851f, -0.1859960705041885f, -0.0494243763387203f,
+// -0.1002294719219208f, -0.2005838304758072f, 0.0165393985807896f,
+// 0.1911116540431976f, 0.1826690137386322f, -0.0650519356131554f,
+// 0.0367582999169827f, -0.0604279674589634f, -0.0819679945707321f,
+// 0.0110532911494374f, 0.1129723265767097f, 0.1455673426389694f,
+// 0.1223503798246384f, -0.1387783288955688f, 0.0034823380410671f,
+// 0.0743014141917229f, 0.0634629055857658f, 0.0211085733026266f,
+// -0.0235922653228045f, -0.1429269313812256f, 0.1407868117094040f,
+// 0.0569909997284412f, -0.0655489936470985f, -0.0209637153893709f,
+// -0.0282189808785915f, 0.0165965817868710f, -0.0922788232564926f,
+// -0.1405425369739532f, 0.1312199532985687f, 0.0149540472775698f,
+// 0.0864631906151772f, 0.0120270224288106f, 0.1302533298730850f,
+// 0.0851815044879913f, -0.3413860797882080f, -0.1011561602354050f,
+// -0.0377544350922108f, 0.1621438711881638f, -0.0295340213924646f,
+// -0.0144784161821008f, 0.1722636818885803f, -0.1198927313089371f,
+// 0.0098854359239340f, 0.2547433972358704f, 0.1057946458458900f,
+// -0.0726865381002426f, 0.2182331383228302f, -0.0524359047412872f,
+// -0.0170265231281519f, 0.2205260396003723f, 0.0253858920186758f,
+// 0.0703659132122993f, 0.2392407804727554f, 0.0154428454115987f,
+// -0.0246252883225679f, -0.0005400188965723f, 0.1076791509985924f,
+// 0.0371701344847679f, 0.4417640268802643f, -0.0905448496341705f,
+// 0.0048756231553853f, -0.0667234286665916f, 0.0236065555363894f,
+// -0.0460075139999390f, 0.0838640928268433f, 0.0113282287493348f,
+// -0.0169237088412046f, 0.2710824012756348f, -0.1157330870628357f,
+// 0.0540931448340416f, 0.3232085406780243f, -0.0693945810198784f,
+// 0.0254445485770702f, 0.3601182699203491f, 0.1627245247364044f,
+// 0.0172808784991503f, -0.1226656809449196f, -0.0115078799426556f,
+// 0.0139475381001830f, -0.0993041619658470f, -0.0849993377923965f,
+// -0.0254402067512274f, 0.4622512459754944f, 0.1410230696201324f,
+// 0.1738828867673874f, -0.3187795579433441f, 0.0452790670096874f,
+// -0.0430744662880898f, 0.0912373885512352f, 0.0157717857509851f,
+// -0.0392933227121830f, 0.4113553166389465f, -0.0683187767863274f,
+// -0.0299986656755209f, -0.0051438179798424f, -0.0135844787582755f,
+// 0.0379728637635708f, 0.1640758961439133f, -0.0656882822513580f,
+// 0.0680322200059891f, -0.0364254377782345f, -0.0667535737156868f,
+// 0.0688440874218941f, 0.0243968684226274f, 0.0526280477643013f,
+// -0.0196467917412519f, -0.0037935262080282f, 0.0584651492536068f,
+// 0.0901323407888412f, -0.2060195654630661f, 0.0166560653597116f,
+// 0.0193143077194691f, -0.0693000480532646f, -0.0058118053711951f,
+// 0.0681619569659233f, -0.0341146476566792f, 0.1312854588031769f,
+// 0.0349215827882290f, -0.1336696147918701f, -0.0728182867169380f,
+// 0.0417305342853069f, 0.0944365933537483f, -0.1151940673589706f,
+// -0.1289341002702713f, 0.2396414577960968f, -0.0730099529027939f,
+// -0.0706257149577141f, 0.0893485695123672f, 0.0223447028547525f,
+// 0.0577742457389832f, -0.1774707436561584f, -0.0533111691474915f,
+// -0.0442084781825542f, -0.1267523318529129f, -0.0072809052653611f,
+// -0.0257841926068068f, -0.1021227538585663f, -0.1534639149904251f,
+// -0.0849351212382317f, 0.0488884598016739f, 0.0178933553397655f,
+// -0.0086436681449413f, 0.0295312572270632f, 0.0294469874352217f,
+// 0.0096987541764975f, -0.1443994492292404f, -0.0482364781200886f,
+// 0.0188159644603729f, 0.0576046071946621f, 0.1132384389638901f,
+// 0.0812878236174583f, 0.0969335809350014f, -0.1391676664352417f,
+// -0.0822849571704865f, 0.1065761595964432f, 0.1097351089119911f,
+// -0.1085064560174942f, -0.0517913959920406f, -0.0280004944652319f,
+// 0.0627585947513580f, -0.1131491214036942f, -0.0900032669305801f,
+// -0.1099423840641975f, 0.1321012526750565f, 0.1641872823238373f,
+// -0.1826971173286438f, 0.1147996336221695f, 0.0561573728919029f,
+// -0.0164269953966141f, -0.1270263791084290f, -0.0032529560849071f,
+// 0.0284139439463615f, -0.0586479082703590f, -0.0063868141733110f,
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+// -0.4399400651454926f, -0.2645640075206757f, -0.0162304900586605f,
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+// -0.1453975290060043f, 0.0770585983991623f, -0.0989120453596115f,
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+// -0.0786007344722748f, -0.1325569599866867f, 0.0201882515102625f,
+// 0.0387673825025558f, 0.2967460751533508f, -0.0987441614270210f,
+// -0.0786463022232056f, -0.1064490750432014f, -0.0264120474457741f,
+// 0.0565990805625916f, -0.0917375236749649f, 0.0718446597456932f,
+// 0.0043706307187676f, 0.3735512793064117f, -0.1501050293445587f,
+// -0.0428035557270050f, 0.2364259213209152f, -0.0506985075771809f,
+// 0.0219576265662909f, -0.0169963296502829f, 0.1642770320177078f,
+// 0.1439498811960220f, -0.3296299874782562f, -0.0469635538756847f,
+// 0.0192383341491222f, -0.0493768639862537f, -0.0694084018468857f,
+// -0.1057134792208672f, 0.2834724187850952f, 0.0636288300156593f,
+// 0.1275113224983215f, -0.1968575716018677f, 0.0940595716238022f,
+// 0.0096344538033009f, 0.0956815853714943f, 0.1084114015102386f,
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+// -0.0271600615233183f, -0.0391778647899628f, 0.1711533218622208f,
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+// -0.1862816810607910f, -0.0848787650465965f, 0.1160581260919571f,
+// 0.0518346615135670f, -0.3041551411151886f, -0.0873452350497246f,
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+// 0.0678702592849731f, 0.1571369022130966f, -0.1706527173519135f,
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+// -0.2795804142951965f, 0.1451189070940018f, -0.0139362402260303f,
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+// 0.0317930728197098f, 0.4636239111423492f, -0.0551396459341049f,
+// 0.1887559145689011f, 0.0550292544066906f, -0.0289282985031605f,
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+// 0.1149188354611397f, -0.3936622440814972f, 0.0530975386500359f,
+// 0.0867408215999603f, -0.6206668019294739f, -0.0071484870277345f,
+// 0.1407564282417297f, 0.4048687219619751f, 0.0102988751605153f,
+// 0.1126826927065849f, -0.3886005580425262f, 0.0219266563653946f,
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+// -0.2162764668464661f, -0.0508437566459179f, -0.0085746841505170f,
+// 0.0229612179100513f, -0.3021938502788544f, -0.0169742237776518f,
+// 0.1443880945444107f, -0.4054447412490845f, 0.0306759905070066f,
+// -0.0892804935574532f, 0.2963629364967346f, -0.0034372138325125f,
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+// -0.0901422649621964f, 0.0723073184490204f, 0.1559722870588303f,
+// -0.1988085806369781f, 0.0290211569517851f, 0.0209284834563732f,
+// -0.0050694392994046f, -0.1049600914120674f, 0.0124571649357677f,
+// -0.0747912004590034f, 0.2054199278354645f, 0.0013141349190846f,
+// 0.0459637716412544f, 0.0703571885824203f, 0.0345760956406593f,
+// -0.3032391965389252f, -0.6264198422431946f, -0.2439969182014465f,
+// -0.2732734680175781f, -1.0012452602386475f, -1.3258676528930664f,
+// 0.2801207900047302f, -0.2818130552768707f, -0.2798595428466797f,
+// 0.8663133382797241f, -0.3753421604633331f, -0.4753561615943909f,
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+// 0.3709774017333984f, -0.0253006611019373f, 0.0338253080844879f,
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+// 0.0235592909157276f, 0.0434921272099018f, -0.9452955722808838f,
+// -0.0267760343849659f, -0.1614509522914886f, -0.1919398009777069f,
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+// -0.0294919740408659f, -0.0476139225065708f, 0.0471649207174778f,
+// -0.1554540693759918f, -0.1853116601705551f, -0.0006790581392124f,
+// 0.0115356668829918f, 0.1161828115582466f, 0.0162325259298086f,
+// -0.2171325683593750f, -0.0990257039666176f, -0.2797844111919403f,
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+// -0.0702967867255211f, -0.0646019279956818f, 0.1351034939289093f,
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+// 0.0541203469038010f, -0.0144345546141267f, 0.0783040821552277f,
+// -0.0535695478320122f, -0.1217158138751984f, -0.1009971946477890f,
+// 0.1533527374267578f, 0.1853719353675842f, -0.2185774147510529f,
+// 0.0031053461134434f, 0.0243307203054428f, -0.0105732092633843f,
+// -0.0066633564420044f, -0.0065743084996939f, -0.2404791116714478f,
+// 0.0879125297069550f, 0.1992384642362595f, -0.3012913167476654f,
+// 0.0501162968575954f, 0.1347581595182419f, -0.1512281447649002f,
+// 0.1129892766475677f, 0.0277744550257921f, -0.0388805419206619f,
+// -0.2595855891704559f, 0.0207540802657604f, 0.0612765513360500f,
+// 0.1031953841447830f, -0.0694367885589600f, -0.1078882962465286f,
+// -0.2568969130516052f, 0.0011223681503907f, -0.1231435388326645f,
+// 0.0707387924194336f, -0.0027113056275994f, -0.0439813248813152f,
+// -0.0157297309488058f, 0.0081186806783080f, 0.0844228044152260f,
+// 0.0012503468897194f, -0.0421150512993336f, 0.1124999076128006f,
+// 0.1015276908874512f, 0.0306430719792843f, 0.1293505132198334f,
+// 0.0185103639960289f, -0.2038096040487289f, 0.0207227300852537f,
+// 0.2016383409500122f, -0.0870957300066948f, 0.1730916500091553f,
+// -0.1318205595016479f, -0.0261460617184639f, -0.0568961128592491f,
+// -0.1497796177864075f, 0.0210582427680492f, -0.0797210484743118f,
+// -0.0971746370196342f, 0.0156109407544136f, -0.2230744510889053f,
+// -0.0778070241212845f, -0.0465305894613266f, 0.0248477719724178f,
+// -0.1859313249588013f, 0.0926006361842155f, 0.1844630092382431f,
+// 0.0971203818917274f, -0.0851901322603226f, -0.0584502927958965f,
+// -0.1572157293558121f, 0.1957768648862839f, -0.0640770792961121f,
+// -0.2474796473979950f, -0.1705325990915298f, -0.0714155584573746f,
+// 0.0788560137152672f, 0.0085481246933341f, -0.0641366764903069f,
+// -0.1159530654549599f, 0.0509161539375782f, 0.3176740407943726f,
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+// -0.0441518500447273f, -0.0811629667878151f, 0.1154484674334526f,
+// 0.0197824463248253f, -0.0756083428859711f, 0.0201077442616224f,
+// 0.0976702645421028f, 0.0382740758359432f, 0.0873170197010040f,
+// 0.0472518131136894f, -0.0620307885110378f, 0.4918564856052399f,
+// 0.0398779027163982f, 0.0619361139833927f, -0.1299195438623428f,
+// -0.0637084022164345f, -0.0279254652559757f, -0.1408895403146744f,
+// 0.0165728088468313f, 0.0859600976109505f, -0.0569353774189949f,
+// -0.0603900104761124f, -0.0389042794704437f, -0.1315126419067383f,
+// -0.1278192996978760f, -0.1176947280764580f, 0.0604958534240723f,
+// 0.1457364857196808f, 0.2576144039630890f, 0.2584804594516754f,
+// 0.0678561255335808f, 0.1018837317824364f, 0.0878392010927200f,
+// 0.0240693222731352f, -0.0066971965134144f, 0.1599958240985870f,
+// -0.1120248213410378f, -0.0165915973484516f, 0.1346962898969650f,
+// 0.0322082377970219f, -0.0304463207721710f, 0.2521690130233765f,
+// -0.1017533615231514f, -0.0757516324520111f, 0.2171749174594879f,
+// -0.0002234512794530f, 0.0868634805083275f, 0.1039585024118423f,
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+// -0.0609563291072845f, -0.1178759112954140f, -0.2998937070369720f,
+// 0.0225755348801613f, 0.0715130418539047f, 0.1138006672263145f,
+// -0.0463526435196400f, -0.0151628507301211f, 0.3981377482414246f,
+// 0.0318189635872841f, -0.0821706056594849f, -0.0359763018786907f,
+// -0.0280167981982231f, -0.0368989743292332f, 0.0817688107490540f,
+// 0.1179616674780846f, 0.1816166192293167f, -0.3387052416801453f,
+// 0.0125588783994317f, -0.0337966158986092f, 0.0305429156869650f,
+// -0.0764550939202309f, -0.1010136753320694f, -0.1053711250424385f,
+// 0.1702450215816498f, 0.1822928786277771f, 0.1857831329107285f,
+// 0.0795813873410225f, 0.0632570311427116f, -0.0062402361072600f,
+// 0.0500121377408504f, -0.0212455932050943f, 0.3520399332046509f,
+// -0.0679248347878456f, -0.0288789737969637f, 0.3590849041938782f,
+// -0.0330481305718422f, 0.0675571933388710f, -0.1975956410169601f,
+// -0.1328265070915222f, -0.0298210475593805f, 0.1643951386213303f,
+// 0.0228595975786448f, 0.1158242225646973f, 0.1760519593954086f,
+// 0.0057220677845180f, -0.0123360119760036f, 0.0774640589952469f,
+// -0.0634230747818947f, -0.1036548316478729f, -0.0870916545391083f,
+// 0.0722195133566856f, 0.0703595280647278f, 0.1509282290935516f,
+// -0.0244495328515768f, -0.0024995456915349f, -0.0257911588996649f,
+// 0.0618958808481693f, -0.1321187615394592f, 0.1083598360419273f,
+// -0.0621230565011501f, 0.0111669423058629f, -0.1022806763648987f,
+// 0.1334842592477798f, 0.2287627756595612f, -0.0934759974479675f,
+// 0.1022763326764107f, 0.0296244472265244f, -0.1232114657759666f,
+// -0.0502394214272499f, -0.0207374021410942f, 0.2256766855716705f,
+// 0.1509632468223572f, 0.1096458137035370f, 0.1305897533893585f,
+// 0.0946663618087769f, 0.0735818818211555f, 0.1303192526102066f,
+// 0.0681874454021454f, 0.1192929521203041f, 0.0898978337645531f,
+// -0.0189084243029356f, 0.1058107018470764f, 0.0510280802845955f,
+// -0.0718338489532471f, -0.0879809558391571f, 0.0031629221048206f,
+// -0.1046181470155716f, -0.0169915612787008f, 0.0278237853199244f,
+// -0.1024666130542755f, -0.1465166211128235f, 0.0196753069758415f,
+// 0.0542838908731937f, 0.0463965535163879f, -0.0666163563728333f,
+// 0.0583342649042606f, -0.0619718618690968f, 0.1499993056058884f,
+// 0.0658723711967468f, 0.0322192385792732f, 0.0166597310453653f,
+// 0.0314100906252861f, -0.0728576853871346f, 0.1497338563203812f,
+// 0.0786861330270767f, -0.2315355390310287f, -0.0307714585214853f,
+// 0.0138852046802640f, 0.0444737710058689f, -0.0178366340696812f,
+// -0.1525228321552277f, 0.0360899604856968f, 0.1387436389923096f,
+// 0.0485521294176579f, -0.0982960686087608f, -0.0788924843072891f,
+// -0.0034131559077650f, -0.0067238863557577f, -0.0492293834686279f,
+// -0.1305403411388397f, 0.1431712359189987f, 0.0813627690076828f,
+// -0.0349138639867306f, -0.0896352455019951f, 0.0699837729334831f,
+// -0.1102239564061165f, 0.2257417738437653f, -0.1284259706735611f,
+// -0.0967574194073677f, -0.1237919554114342f, -0.0855020955204964f,
+// 0.0784973800182343f, 0.0671424865722656f, 0.0243165027350187f,
+// -0.1310917288064957f, -0.1746931523084641f, 0.0726330354809761f,
+// -0.0390232577919960f, 0.1295467168092728f, -0.0093856267631054f,
+// -0.0194841772317886f, -0.0693997964262962f, -0.0482497923076153f,
+// -0.0004215279768687f, -0.0373230390250683f, -0.1239394918084145f,
+// -0.0393771231174469f, 0.0731801167130470f, -0.1195040568709373f,
+// -0.0198368262499571f, -0.0783863365650177f, 0.0995682328939438f,
+// -0.0094440272077918f, -0.0268889330327511f, -0.1358914375305176f,
+// 0.0100499065592885f, 0.0493746437132359f, 0.1235748231410980f,
+// -0.0472690090537071f, 0.0446495003998280f, 0.0356867313385010f,
+// -0.0599660724401474f, 0.1259299963712692f, -0.0365311019122601f,
+// -0.0196294058114290f, -0.1482785940170288f, 0.0514592193067074f,
+// -0.0887195691466331f, 0.0559983290731907f, -0.1468140929937363f,
+// -0.0260523930191994f, -0.0345228537917137f, -0.1077378168702126f,
+// -0.0360951349139214f, 0.0912763848900795f, 0.1183215901255608f,
+// 0.0093327602371573f, 0.0721995085477829f, -0.2526864111423492f,
+// -0.0218491051346064f, 0.0038491834420711f, -0.1984527409076691f,
+// -0.0027201306074858f, -0.0438411124050617f, 0.0071242265403271f,
+// -0.0104242702946067f, 0.0981302261352539f, 0.1836938858032227f,
+// 0.0156839434057474f, 0.0132135199382901f, -0.4767211079597473f,
+// -0.0093587888404727f, -0.0117981098592281f, -0.1667831987142563f,
+// -0.0080045768991113f, -0.0097699454054236f, -0.3658328652381897f,
+// 0.0217447225004435f, -0.0676950141787529f, 0.1498678624629974f,
+// 0.0131524810567498f, -0.0329774543642998f, -0.5435885190963745f,
+// -0.0039872289635241f, -0.0327502191066742f, -0.3668422102928162f,
+// -0.0254254136234522f, 0.1125988811254501f, -0.4369912445545197f,
+// -0.0173652395606041f, -0.0108449738472700f, 0.1550551652908325f,
+// -0.0021074565593153f, -0.0287794414907694f, 0.4194664657115936f,
+// -0.0298372842371464f, 0.0348758026957512f, -0.0781351178884506f,
+// 0.0139163359999657f, 0.0198636911809444f, 0.0710014253854752f,
+// -0.0067253694869578f, 0.0036573808174580f, 0.0304828379303217f,
+// -0.0222050398588181f, 0.0668700188398361f, -0.1172292307019234f,
+// 0.0557696856558323f, 0.0668816044926643f, -0.0610916800796986f,
+// -0.1486452966928482f, 0.0693650990724564f, -0.0921343713998795f,
+// 0.0402981974184513f, 0.0285329185426235f, -0.0718525126576424f,
+// 0.0347774028778076f, -0.0259605646133423f, 0.0124837551265955f,
+// 0.0200376994907856f, -0.2360414713621140f, 0.8088269233703613f,
+// 0.3666249215602875f, 0.7275481820106506f, 0.0708103999495506f,
+// 0.6654303669929504f, 0.2556853294372559f, -0.7762141823768616f,
+// -1.0435554981231689f,
+// 0.5503522157669067f, 1.1235927343368530f, 1.3195496797561646f,
+// -0.5474681258201599f, 0.6897432208061218f, -0.0716017559170723f,
+// 0.5024916529655457f, 0.0475910380482674f, -0.0302082784473896f,
+// -0.2625969052314758f, 0.2297173440456390f, -0.0617483593523502f,
+// 0.0624447651207447f, 0.0683373436331749f, 0.4028191268444061f,
+// 0.1021604314446449f, -0.0515899620950222f, -0.0147278262302279f,
+// -0.0859885066747665f, -0.2307883501052856f, 0.0208108443766832f,
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+// -0.2033080607652664f, -0.1506783068180084f, 0.1777284145355225f,
+// 0.1167847439646721f, 0.1655934005975723f, 0.0945790633559227f,
+// -0.2482723742723465f, 0.1792757809162140f, 0.0215896368026733f,
+// 0.2340768277645111f, -0.2441953122615814f, 0.1561125516891479f,
+// -0.1287454515695572f, 0.0588276684284210f, -0.0543488189578056f,
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+// -0.1818275600671768f, 0.1946217715740204f, -0.1268916279077530f,
+// 0.0450930073857307f, -0.0236995536834002f, -0.0902123153209686f,
+// -0.2739755511283875f, -0.1979535222053528f, -0.0264006275683641f,
+// -0.0261624027043581f, 0.1690888106822968f, 0.1718302667140961f,
+// -0.1651113927364349f, -0.1195175573229790f, -0.1537057012319565f,
+// 0.0746699571609497f, 0.1099733188748360f, -0.1748132258653641f,
+// -0.0469941720366478f, -0.1500727087259293f, -0.0732865855097771f,
+// 0.2118384242057800f, 0.0784979015588760f, 0.1901907175779343f,
+// -0.2691223919391632f, -0.0251511838287115f, 0.0511631816625595f,
+// -0.0172951463609934f, -0.1373666524887085f, -0.1197123304009438f,
+// 0.2054472267627716f, 0.0918495133519173f, 0.2860390841960907f,
+// 0.1238257735967636f, 0.1382637470960617f, -0.0250368956476450f,
+// 0.0668867900967598f, -0.0732767581939697f, 0.0406535491347313f,
+// 0.0686183348298073f, 0.0924964919686317f, -0.0229020249098539f,
+// -0.1721753180027008f, -0.0563538670539856f, 0.0349142886698246f,
+// -0.1468899846076965f, -0.0957385376095772f, -0.0174824818968773f,
+// -0.0131684299558401f, 0.0743657872080803f, -0.2585874795913696f,
+// -0.1986766606569290f, 0.2757526636123657f, -0.1646734029054642f,
+// 0.1287933140993118f, 0.0010635402286425f, 0.0559434778988361f,
+// 0.2513576745986938f, -0.1325760632753372f, 0.1562484353780746f,
+// 0.2422229349613190f, 0.1419349908828735f, -0.2494964450597763f,
+// 0.0465989075601101f, 0.1606212556362152f, -0.0089199114590883f,
+// 0.0974808558821678f, 0.0107071595266461f, 0.1229511871933937f,
+// -0.1826544702053070f, -0.1404869109392166f, 0.1565381437540054f,
+// -0.1284366995096207f, 0.2026359289884567f, 0.0501506961882114f,
+// 0.2306211292743683f, -0.0552665814757347f, 0.2426324784755707f,
+// 0.0018783777486533f, 0.0851922035217285f, -0.1322316527366638f,
+// 0.3079032003879547f, 0.0041848071850836f, -0.4812103211879730f,
+// -0.0613851845264435f, 0.3128149807453156f, 0.0507771335542202f,
+// -0.2506083548069000f, -0.2074258178472519f, 0.0962183251976967f,
+// 0.0341102443635464f, -0.0031034552957863f, -0.0892680808901787f,
+// -0.4152185320854187f, -0.0371784344315529f, -0.0438370555639267f,
+// 0.4203791618347168f, 0.2473257780075073f, -0.0681976079940796f,
+// 0.2452239990234375f, 0.1608535498380661f, 0.0368631556630135f,
+// -0.2807374000549316f, 0.0572959817945957f, -0.0893598347902298f,
+// -0.0401408337056637f, 0.1250578761100769f, 0.1114709973335266f,
+// 0.3375707864761353f, 0.2969027459621429f, -0.0037771272473037f,
+// 0.2549957334995270f, 0.1727421879768372f, 0.1793968379497528f,
+// 0.0644485726952553f, -0.0499892309308052f, -0.4152791500091553f,
+// -0.1186690777540207f, 0.0504055693745613f, 0.1519839316606522f,
+// -0.2300613224506378f, 0.2624985575675964f, 0.1153113767504692f,
+// -0.0593918375670910f, 0.0578333847224712f, -0.0821096599102020f,
+// 0.3816260993480682f, 0.1891238242387772f, -0.0066618318669498f,
+// 0.5538274645805359f, 0.0405019856989384f, -0.1322236806154251f,
+// -0.0668660327792168f, 0.1024461686611176f, -0.0266351439058781f,
+// -0.0756742805242538f, 0.0163808856159449f, -0.1481841355562210f,
+// -0.2096360176801682f, 0.0126413973048329f, -0.0890566706657410f,
+// -0.0455370210111141f, -0.0265836324542761f, 0.1062089279294014f,
+// -0.0996756553649902f, -0.0049661220982671f, 0.0467751510441303f,
+// 0.0046054418198764f, 0.1811282485723495f, -0.0956077873706818f,
+// 0.1924115568399429f, -0.0181547943502665f, -0.0485163703560829f,
+// 0.1359182596206665f, 0.0958892107009888f, -0.0305493790656328f,
+// 0.0163593273609877f, -0.1978376656770706f, 0.1425369530916214f,
+// 0.1516430228948593f, -0.0267892964184284f, -0.1954641342163086f,
+// -0.0348543897271156f, -0.2263830900192261f, -0.2955451011657715f,
+// 0.1789751648902893f, 0.1066187694668770f, 0.1291668117046356f,
+// 0.2813055217266083f, -0.2068120092153549f, 0.0890734121203423f,
+// -0.0926951691508293f, -0.3705195486545563f, -0.0630164071917534f,
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+// 0.3096104562282562f, -0.1709195822477341f, -0.1556964516639709f,
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+// 0.1209899187088013f, -0.0090310657396913f, -0.0430855005979538f,
+// 0.0063456431962550f, -0.1436854749917984f, -0.1070081517100334f,
+// 0.0383087433874607f, -0.1386834084987640f, 0.0849481448531151f,
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+// -0.2075043767690659f, 0.0812069252133369f, 0.0168901644647121f,
+// 0.0876513123512268f, 0.0159347243607044f, 0.4410264790058136f,
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+// 0.1113683059811592f, -0.0987064763903618f, -0.1579048782587051f,
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+// 0.0524841025471687f, -0.1160329729318619f, 0.0457265973091125f,
+// 0.2994688749313354f, -0.0756509080529213f, -0.0468397401273251f,
+// 0.1180915459990501f, 0.1158877760171890f, 0.0306773744523525f,
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+// -0.0919265076518059f, -0.0615264698863029f, 0.3151536285877228f,
+// 0.1897670477628708f, 0.3080634772777557f, 0.3019611835479736f,
+// 0.0560731105506420f, -0.2851409018039703f, 0.1977333277463913f,
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+// -0.0413789227604866f, -0.0233825575560331f,
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+// -0.0897687971591949f, -0.3593353629112244f, -0.2849197387695312f,
+// 0.0823253318667412f, 0.4122974574565887f, 0.4852996766567230f,
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+// 0.1657729446887970f, -0.0266821235418320f, -0.1960736811161041f,
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+// -0.1599591821432114f, 0.1137880906462669f, 0.2800127863883972f,
+// 0.2541310787200928f, 0.0162645131349564f, -0.0368805937469006f,
+// 0.1033608987927437f, -0.0826993137598038f, -0.4916746616363525f,
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+// 0.1955528408288956f, 0.2291877716779709f, -0.1144999638199806f,
+// 0.0657032728195190f, -0.0159763898700476f, -0.1100466474890709f,
+// 0.1058837547898293f, 0.1173116862773895f, 0.1391998529434204f,
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+// 0.0324565321207047f, -0.3196246325969696f, -0.0066855689510703f,
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+// -0.0686727613210678f, -0.2516424357891083f, 0.1371879875659943f,
+// 0.0629687160253525f, 0.1734845936298370f, -0.2287237346172333f,
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+// 0.0158568639308214f, -0.1406323611736298f, -0.2070694714784622f,
+// 0.0697662457823753f, 0.0662801787257195f, 0.0606634207069874f,
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+// 0.0251683350652456f, 0.0993150919675827f, -0.0653635114431381f,
+// 0.1672188043594360f, 0.0031521115452051f, 0.0533302798867226f,
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+// 0.0592609457671642f, 0.0218077711760998f, -0.2621725201606750f,
+// 0.0377946346998215f, -0.0907088443636894f, -0.0602085739374161f,
+// -0.1209654584527016f, -0.1874467283487320f, -0.4236384034156799f,
+// 0.0372238159179688f, -0.1044986844062805f, -0.4768217504024506f,
+// -0.1755119115114212f, -0.1851440966129303f, -0.1445132493972778f,
+// 0.1840600371360779f, -0.2283357828855515f, 0.0691771656274796f,
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+// 0.0117416363209486f, 0.0890015661716461f, 0.0974157303571701f,
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+// -0.2649127840995789f, -0.0255978181958199f, -0.0785706266760826f,
+// 0.2867144942283630f, 0.3140647113323212f, 0.1461330652236938f,
+// -0.0771010890603065f, -0.1495222449302673f, 0.1286202520132065f,
+// -0.1023134514689445f, -0.0554765574634075f, -0.1682029068470001f,
+// 0.0278436299413443f, 0.1852084994316101f, 0.0545953400433064f,
+// -0.1384050995111465f, -0.0541551150381565f, -0.0580307543277740f,
+// -0.1819591522216797f, 0.2713106572628021f, 0.0463674701750278f,
+// 0.0262052696198225f, 0.3652226328849792f, 0.1431291997432709f,
+// -0.2110203504562378f, 0.0237106624990702f, -0.1142617017030716f,
+// 0.1929450780153275f, 0.1458335220813751f, -0.2050037235021591f,
+// -0.2209392338991165f, -0.2403073608875275f, -0.1413891017436981f,
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+// 0.2976784408092499f, -0.1834312081336975f, 0.0822290256619453f,
+// -0.2115547955036163f, -0.0389730669558048f, -0.0772162005305290f,
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+// 0.1027548387646675f, 0.1771736592054367f, 0.0363082624971867f,
+// 0.0668584480881691f, 0.0719419419765472f, -0.0034850663505495f,
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+// -0.1111102253198624f, 0.0876687914133072f, 0.1795725524425507f,
+// 0.1141410842537880f, 0.2706945836544037f, 0.1889487504959106f,
+// -0.0129860658198595f, 0.0065688658505678f, 0.1270708739757538f,
+// 0.0539610832929611f, -0.0384354107081890f, -0.1132745295763016f,
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+// 0.0459422208368778f, 0.1187837645411491f, -0.2797903716564178f,
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+// -0.2119045704603195f, 0.3354896008968353f, -0.0463718362152576f,
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+// 0.4451198279857635f, -0.3492844700813293f, -0.3848979771137238f,
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+// -0.1712453663349152f, 0.0323849692940712f, 0.2541809976100922f,
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+// 0.0870592221617699f, -0.1995157450437546f, 0.1387645900249481f,
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+// 0.0272569078952074f, 0.0514541640877724f, 0.1604039818048477f,
+// 0.2431612610816956f, -0.1223862767219543f, 0.1680334508419037f,
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+// -0.1452646404504776f, 0.0297459401190281f, -0.1848651319742203f,
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+// 0.0899975895881653f, 0.0390978567302227f, 0.0693566426634789f,
+// -0.1051918715238571f, 0.0977170541882515f, -0.1468180716037750f,
+// -0.3253954350948334f, 0.3040422797203064f, 0.1969997733831406f,
+// 0.1083386912941933f, -0.3286624550819397f, -0.0766459926962852f,
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+// 0.0216066278517246f, -0.1626466959714890f, 0.3130508065223694f,
+// 0.2914875149726868f, -0.0908857360482216f, 0.1023429781198502f,
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+// 0.0378231257200241f, 0.1729525029659271f, 0.1660959571599960f,
+// 0.1423238068819046f, -0.2247675657272339f, -0.1246151402592659f,
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+// -0.0021125657949597f, -0.0490273311734200f, -0.0512670464813709f,
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+// -0.0848846286535263f, 0.1905792057514191f, 0.0720281004905701f,
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+// 0.2833685278892517f, -0.5170956254005432f, -0.4422380626201630f,
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+// -0.2178887873888016f, 0.3970628380775452f, 0.3040881752967834f,
+// 0.3121468126773834f, -0.1561459749937057f, 0.4305599331855774f,
+// 0.2107383757829666f, -0.0513405017554760f, 0.1309141069650650f,
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+// 0.2862324714660645f, 0.2122892886400223f, 0.0233466532081366f,
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+// 0.3792024850845337f, -0.0778846368193626f, -0.0354521088302135f,
+// -0.1044693142175674f, 0.0684539005160332f, 0.1171274036169052f,
+// 0.0365500859916210f, 0.1125769093632698f, 0.0547877810895443f,
+// -0.0765585452318192f, 0.1291604638099670f, 0.0797917023301125f,
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+// 0.1947870552539825f, -0.0613771304488182f, 0.2068402618169785f,
+// 0.0295089278370142f, -0.2457870095968246f, 0.0590615533292294f,
+// 0.2270316630601883f, 0.0567506067454815f, -0.1393799632787704f,
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+// -0.0270044859498739f, -0.1261922568082809f, 0.1297008097171783f,
+// 0.0828882828354836f, -0.1020809635519981f, -0.0531063675880432f,
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+// -0.2122028619050980f, -0.0597294867038727f, 0.0349381491541862f,
+// 0.0809110999107361f, 0.1044176593422890f, 0.1422409415245056f,
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+// -0.3017661869525909f, -0.1246563717722893f, 0.2603316009044647f,
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+// 0.1536049097776413f, -0.1786976307630539f, 0.1585507690906525f,
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+// -0.0980883687734604f, -0.0291637666523457f, 0.1070054695010185f,
+// 0.2125611603260040f, 0.1994185745716095f, -0.1041230484843254f,
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+// -0.1658797711133957f, -0.0012069758959115f, 0.0001097530548577f,
+// 0.1090539991855621f, -0.1253118067979813f, 0.0014015949564055f,
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+// 0.1014091968536377f, -0.2367227971553802f, 0.0073524150066078f,
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+// 0.1698362827301025f, -0.0648948177695274f, 0.0239521916955709f,
+// 0.1220546215772629f, 0.0313194580376148f, -0.1681414991617203f,
+// 0.2170575559139252f, -0.1357684880495071f, 0.0967948585748672f,
+// -0.1020687967538834f, -0.1575752943754196f, -0.0226258058100939f,
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+// 0.0462394766509533f, -0.0528581365942955f, 0.0577456541359425f,
+// -0.1936739534139633f, 0.0452058427035809f, 0.2203948497772217f,
+// 0.1896889656782150f, -0.1808883398771286f, 0.0140448892489076f,
+// 0.1120018362998962f, -0.0290267635136843f, -0.1652595996856689f,
+// 0.1147301942110062f, 0.2829959690570831f, -0.0483969487249851f,
+// 0.0512813292443752f, -0.0539490953087807f, -0.2595172524452209f,
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+// -0.2311304807662964f, -1.1241534948348999f, 0.2847048342227936f,
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+// 0.1527945697307587f, -0.1208893582224846f, 0.0357252694666386f,
+// 0.2191336601972580f, -0.1241405382752419f, -0.1168866977095604f,
+// 0.0421690009534359f, -0.3602877259254456f, 0.2280210554599762f,
+// 0.3817453086376190f, -0.0851022824645042f, 0.3778326809406281f,
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+// 0.3306213915348053f, -0.0285493321716785f, -0.2534328699111938f,
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+// 0.3592135310173035f, -0.2624724209308624f, -0.0135834170505404f,
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+// -0.0180670246481895f, -0.1842213869094849f, -0.0174507182091475f,
+// 0.3015522658824921f, 0.2013451159000397f, -0.8653223514556885f,
+// -0.1131948754191399f, 0.3916999697685242f, 0.3497596085071564f,
+// 0.0903264358639717f, -0.3715775310993195f, 0.2272141277790070f,
+// 0.3285101056098938f, 0.2512899637222290f, 0.1900104135274887f,
+// -0.1601302921772003f, -0.2930262684822083f, 0.3837843835353851f,
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+// 0.2479647994041443f, 0.0197615604847670f, 0.0689226090908051f,
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+// 0.2261690348386765f, 0.1984623223543167f, 0.1201516389846802f,
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+// -0.1803514957427979f, -0.4599880576133728f, -0.6099383831024170f,
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+// -0.9984856247901917f, -0.2480498254299164f, -0.0933760553598404f,
+// 0.3526032269001007f, -0.0368203148245811f, -0.0736394152045250f,
+// 0.4693384170532227f, 0.7413011789321899f, -0.0372199006378651f,
+// 0.2787767052650452f, 0.2911886274814606f, 0.0575715973973274f,
+// -0.0338015258312225f, 0.1445402801036835f, 0.2508115172386169f,
+// 0.0869016200304031f, 0.2157263904809952f, 0.3321065902709961f,
+// 0.0111975148320198f, 0.5005723834037781f, -0.1552089601755142f,
+// -0.2510560452938080f, 0.0012845232849941f, -0.5361264944076538f,
+// 0.0679067075252533f, -0.2240480184555054f, -0.2589494585990906f,
+// 0.4244262576103210f, 0.2529625594615936f, -0.5229920744895935f,
+// -0.1662651002407074f, -0.4186590015888214f, -0.0748652517795563f,
+// 0.2661439180374146f, 0.2303549498319626f, 0.4624764919281006f,
+// 0.4369391202926636f, 0.0008294148719870f, -0.4079197645187378f,
+// -0.9524279832839966f, -0.2432948201894760f, -0.3180467486381531f,
+// 0.2540805339813232f, -0.2684391438961029f, 0.1882566660642624f,
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+// -0.1851517260074615f, 0.0432925783097744f, 0.0365790762007236f,
+// 0.3751431107521057f, 0.2523667514324188f, -0.2625288069248199f,
+// -0.1427539139986038f, -0.0827232822775841f, -0.0888825953006744f,
+// -0.0166781656444073f, 0.0935476198792458f, 0.2058736979961395f,
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+// 0.2384140789508820f, 0.0942977443337440f, 0.0179731082171202f,
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+// 0.0679417178034782f, 0.2500242590904236f, -0.0866370275616646f,
+// 0.0446146130561829f, -0.1012856885790825f, -0.1077733933925629f,
+// -0.0565991513431072f, 0.0070720952935517f, -0.0550474934279919f,
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+// -0.0152556328102946f, -0.1075812056660652f, 0.2176989912986755f,
+// 0.1019859164953232f, 0.0398337319493294f, 0.1631014347076416f,
+// -0.0428467690944672f, -0.2383475601673126f, -0.1193812713027000f,
+// 0.0349979400634766f, -0.2321526259183884f, 0.0888284370303154f,
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+// -0.0768946930766106f, 0.0015160934999585f, -0.1226744949817657f,
+// 0.0978055596351624f, -0.0895125716924667f, -0.1181609854102135f,
+// -0.0027177918236703f, 0.2333136945962906f, 0.1464601010084152f,
+// -0.0854985043406487f, -0.0767679810523987f, 0.0192067585885525f,
+// 0.1405018568038940f, -0.1873522996902466f, -0.0473112761974335f,
+// 0.0245375111699104f, -0.1308185160160065f, -0.1747742742300034f,
+// -0.1018682569265366f, -0.2006540298461914f, -0.0831774696707726f,
+// 0.0868936553597450f, -0.0649664103984833f, 0.1854733526706696f,
+// -0.1000875532627106f, 0.1071570590138435f, -0.0871054455637932f,
+// -0.1315570324659348f, 0.0792143195867538f, -0.0959369838237762f,
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+// -0.0035245548933744f, 0.1654260903596878f, 0.1237986385822296f,
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+// -0.0955527499318123f, -0.1193333566188812f, 0.1441927999258041f,
+// -0.0965453684329987f, -0.0124768381938338f, -0.0140063939616084f,
+// -0.0215901006013155f, 0.0756797194480896f, 0.1814691424369812f,
+// -0.0249704588204622f, 0.0588743090629578f, 0.0470614023506641f,
+// 0.0989643558859825f, 0.1002574190497398f, 0.0740977525711060f,
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+// -0.1305612474679947f, 0.3203187584877014f, -0.0669609978795052f,
+// 0.2131438106298447f, 0.0154922213405371f, -0.1190443858504295f,
+// -0.0971974804997444f, 0.1236771121621132f, -0.0585810877382755f,
+// 0.0406465195119381f, -0.1040305122733116f, -0.0156381167471409f,
+// 0.0968469157814980f, 0.0771055892109871f, -0.0704678595066071f,
+// 0.1359270364046097f, -0.0369901210069656f, -0.1141615062952042f,
+// 0.0569358654320240f, 0.0061419047415257f, -0.1228349804878235f,
+// 0.1991153657436371f, -0.1293544173240662f, 0.1708342880010605f,
+// -0.0114093180745840f, -0.1369563639163971f, -0.1077355220913887f,
+// -0.1096846088767052f, 0.1874965876340866f, 0.1716325432062149f,
+// 0.1827303469181061f, 0.1862433552742004f, 0.1880656331777573f,
+// 0.1361310034990311f, 0.2107706516981125f, 0.1894685178995132f,
+// 0.0293350107967854f, 0.2346275895833969f, 0.1305739879608154f,
+// 0.0698833391070366f, 0.2789212167263031f, 0.0936894491314888f,
+// 0.0805512592196465f, 0.1337435990571976f, 0.3345678150653839f,
+// 0.1867365539073944f, -0.0020651123486459f, 0.2252079546451569f,
+// 0.1819836497306824f, -0.1289304196834564f, -0.2053095698356628f,
+// -0.1627950221300125f, -0.1171078756451607f, 0.2891613543033600f,
+// 0.1564458161592484f, 0.0287269856780767f, -0.0191041715443134f,
+// 0.1232019364833832f, 0.1177391707897186f, 0.0065387110225856f,
+// -0.0823416262865067f, 0.1012463122606277f, 0.0767855718731880f,
+// -0.2277948111295700f, -0.0365994572639465f, -0.1909829676151276f,
+// -0.1404775977134705f, -0.1424533724784851f, -0.1250339895486832f,
+// -0.2348314076662064f, -0.2144490778446198f, -0.1020353287458420f,
+// -0.0352617278695107f, -0.1357240825891495f, 0.1038873493671417f,
+// -0.1430746912956238f, 0.1437552273273468f, -0.2847013473510742f,
+// -0.1788490563631058f, -0.1872721314430237f, -0.3918784856796265f,
+// -0.2809172868728638f, -0.2947713434696198f, -0.0826533213257790f,
+// 0.1816065907478333f, 0.0905860736966133f, -0.1725815832614899f,
+// 0.0954151824116707f, -0.0641878321766853f, 0.2449508607387543f,
+// -0.1780791133642197f, 0.4829954206943512f, 0.3020409643650055f,
+// 0.3727412819862366f, 0.0170099940150976f, 0.4986437559127808f,
+// 0.4062259495258331f, 0.6407068967819214f, -0.2363049387931824f,
+// -0.0726465284824371f, 0.5570001006126404f, -0.0443486720323563f,
+// -0.5349817872047424f, 0.1273155659437180f, -0.1790994107723236f,
+// -0.4241997599601746f, 0.1327628493309021f, 0.3957374095916748f,
+// 0.3611032962799072f, 0.3574630320072174f, -0.0548853613436222f,
+// 0.0326424501836300f, 0.2885259091854095f, -0.1707606762647629f,
+// -0.0652716532349586f, -0.1021872162818909f, 0.6961697936058044f,
+// 0.1320284008979797f, -0.6932208538055420f, 0.2512930631637573f,
+// 0.3209479153156281f, -0.0850192829966545f, 0.3344039618968964f,
+// -0.1407294422388077f, 0.1110853105783463f, 0.1525448262691498f,
+// 0.0160389002412558f, 0.3062250614166260f, -0.0407409258186817f,
+// 0.2296556532382965f, -0.1655614972114563f, 0.4829877614974976f,
+// 0.2787357568740845f, -0.2441304028034210f, 0.1602226644754410f,
+// -0.3815619051456451f, 0.0694773718714714f, -0.0962686240673065f,
+// 0.2310087680816650f, -0.3450715541839600f, -0.0464171655476093f,
+// -0.1914880573749542f, 0.2654567956924438f, -0.0030703237280250f,
+// -0.2677876055240631f, -0.0676267817616463f, -0.2306504100561142f,
+// 0.0102901728823781f, 0.5276672244071960f, 0.0932221040129662f,
+// 0.1625684797763824f, -0.2590132951736450f, -0.0151294898241758f,
+// 0.3058006167411804f, -0.0268750991672277f, -0.2899991869926453f,
+// -0.4659244716167450f, -0.4095701873302460f, 0.0741936266422272f,
+// 0.1388424932956696f, 0.2485172748565674f, 0.3041733801364899f,
+// -0.2569679021835327f, 0.1257035434246063f, 0.3427589535713196f,
+// -0.1678449064493179f, -0.3950226604938507f, -0.0346566364169121f,
+// -0.1263860464096069f, 0.2886778116226196f, 0.3044680953025818f,
+// 0.1054899990558624f, 0.1635595113039017f, -0.0117110069841146f,
+// -0.0721204131841660f, -0.0516789071261883f, -0.0759342908859253f,
+// -0.1271045953035355f, -0.0281216744333506f, 0.0756800994277000f,
+// -0.1751368045806885f, -0.0872734636068344f, 0.0571221113204956f,
+// -0.1112727522850037f, -0.1351316422224045f, -0.1549229174852371f,
+// 0.0828647091984749f, 0.1658633798360825f, 0.0340778529644012f,
+// -0.0798681452870369f, 0.1196589916944504f, 0.1398663371801376f,
+// 0.1589661091566086f, -0.0918274596333504f, 0.0801186338067055f,
+// 0.0084443101659417f, 0.0019905015360564f, -0.0288601871579885f,
+// -0.1400169432163239f, -0.2169339209794998f, 0.0811400935053825f,
+// 0.0347564369440079f, -0.1611126810312271f, -0.0530624389648438f,
+// -0.0385354831814766f, 0.1456057131290436f, -0.2228501886129379f,
+// -0.0939453169703484f, 0.0171793159097433f, -0.2813740074634552f,
+// 0.0563724189996719f, 0.0330182947218418f, 0.2416441589593887f,
+// -0.2433085888624191f, -0.2115678191184998f, -0.1966424882411957f,
+// -0.0330356955528259f, -0.0991212502121925f, -0.1605641245841980f,
+// -0.1597445756196976f, 0.1149144023656845f, -0.0801033973693848f,
+// -0.1436571925878525f, -0.1044560223817825f, -0.1703877002000809f,
+// -0.1292446702718735f, 0.0200462955981493f, 0.0350734703242779f,
+// 0.0263615176081657f, 0.1290697306394577f, 0.0049224793910980f,
+// 0.0186139158904552f, -0.1780203729867935f, 0.0077899666503072f,
+// 0.1580208688974380f, 0.0740979090332985f, -0.0950405746698380f,
+// -0.1529488712549210f, -0.0931250229477882f, -0.1741664260625839f,
+// 0.0599547028541565f, 0.1421289592981339f, -0.0152926305308938f,
+// 0.0416416078805923f, 0.3422706425189972f, -0.4048630893230438f,
+// 0.1941176205873489f, -0.0993606820702553f, 0.0528276227414608f,
+// 0.1130191907286644f, 0.3804243505001068f, 0.2730641961097717f,
+// 0.1123979836702347f, 0.0829574093222618f, 0.2065037637948990f,
+// 0.0186578612774611f, -0.0849989280104637f, -0.1889767348766327f,
+// 0.1482036113739014f, -0.0897487252950668f, 0.0071616736240685f,
+// -0.1625446975231171f, 0.1687860041856766f, 0.0150698991492391f,
+// 0.0726398751139641f, -0.1149621680378914f, 0.0673575624823570f,
+// 0.1379208266735077f, 0.0043006911873817f, -0.0592521131038666f,
+// 0.1137418299913406f, 0.0541705451905727f, 0.0687666088342667f,
+// 0.2046645879745483f, 0.1253231912851334f, -0.0277974139899015f,
+// -0.1534567773342133f, 0.1379828602075577f, -0.1121865659952164f,
+// -0.0829062685370445f, 0.0607251524925232f, -0.1653422117233276f,
+// 0.3164972066879272f, -0.1724988073110580f, -0.0361508838832378f,
+// -0.1163779944181442f, -0.0070437267422676f, 0.0395733416080475f,
+// -0.1496266871690750f, -0.0260205883532763f, 0.0852447822690010f,
+// 0.3600874245166779f, -0.0537215955555439f, -0.1138070449233055f,
+// 0.1156367212533951f, 0.1495421975851059f, 0.1869458705186844f,
+// 0.3418437242507935f, 0.1060724109411240f, -0.0613453760743141f,
+// 0.2156819552183151f, 0.2022794336080551f, 0.0447670817375183f,
+// -0.0420498028397560f, 0.0899580270051956f, 0.0572320334613323f,
+// -0.0786703526973724f, -0.1238261461257935f, 0.2485022246837616f,
+// 0.2108904868364334f, -0.0367061197757721f, 0.0818998888134956f,
+// 0.0902882143855095f, 0.1715184599161148f, 0.0356111116707325f,
+// -0.2655363380908966f, 0.0416193082928658f, -0.0797414183616638f,
+// -0.3751799762248993f, -0.0312297176569700f, 0.1456058174371719f,
+// -0.1249861568212509f, -0.1006789505481720f, -0.2555179595947266f,
+// -0.2195762097835541f, -0.0917070209980011f, -0.2197812497615814f,
+// -0.1375425010919571f, -0.0276798401027918f, -0.0706085339188576f,
+// 0.2427472919225693f, 0.1333723366260529f, 0.0739406496286392f,
+// 0.0415669642388821f, -0.0922155231237411f, 0.0531686842441559f,
+// -0.1372375041246414f, -0.2078610509634018f, -0.1337622106075287f,
+// 0.1039596796035767f, 0.0333166383206844f, 0.1255333870649338f,
+// 0.1292781382799149f, 0.0405146591365337f, -0.0618078485131264f,
+// 0.2157580852508545f, -0.0104710999876261f, 0.0508491657674313f,
+// -0.1204361915588379f, 0.1498982310295105f, 0.2199699431657791f,
+// -0.0600824952125549f, 0.1812321096658707f, 0.2300267070531845f,
+// 0.0107079334557056f, -0.1190912798047066f, -0.2031449228525162f,
+// 0.0838885828852654f, 0.1473980098962784f, -0.0167782213538885f,
+// 0.2327584177255630f, 0.2174388468265533f, 0.0853212475776672f,
+// -0.1963279843330383f, -0.2292400449514389f, 0.1380736380815506f,
+// 0.0240814164280891f, 0.0291455090045929f, -0.0734040066599846f,
+// -0.1205750852823257f, 0.2394165545701981f, 0.6131336688995361f,
+// 0.5120940208435059f, 0.4402844309806824f, -0.9330961108207703f,
+// -0.3285349309444427f, -0.1392319798469543f, -1.1612532138824463f,
+// 0.8647591471672058f, 0.4198839664459229f, 0.0114653427153826f,
+// -0.1765352189540863f, 0.3912909626960754f, 0.0164307728409767f,
+// -0.0187141690403223f, 0.2123631536960602f, -0.0441250391304493f,
+// 0.5919442176818848f, -0.0361591205000877f, -0.0979050621390343f,
+// -0.0745838731527328f, -0.2738912999629974f, 0.1667791903018951f,
+// 0.1846343576908112f, 0.0481720380485058f, -0.1118823811411858f,
+// 0.0873152464628220f, 0.2685661613941193f, 0.3765151500701904f,
+// -0.0902349203824997f, 0.1099889650940895f, 0.1345854401588440f,
+// -0.0120541164651513f, 0.5132455229759216f, 0.2947216928005219f,
+// 0.2765795588493347f, -0.2740360200405121f, 0.2315596640110016f,
+// -0.1186404675245285f, -0.0213766656816006f, -0.1558385938405991f,
+// 0.0433918535709381f, 0.3208083212375641f, -0.1904454082250595f,
+// 0.3167636394500732f, 0.3478914797306061f, 0.2175346463918686f,
+// 0.1616008728742599f, -0.2822889983654022f, -0.5414195060729980f,
+// -0.1583950519561768f, 0.4105324149131775f, -0.0346768796443939f,
+// -0.3363575339317322f, -0.2898026704788208f, -0.3144956827163696f,
+// -0.2608414292335510f, -0.5253185033798218f, -0.2400231063365936f,
+// 0.1571138650178909f, 0.0881339609622955f, 0.2890198528766632f,
+// 0.0095365280285478f, -0.3723326325416565f, -0.0078342491760850f,
+// -0.5925095677375793f, -0.3003634214401245f, -0.4348835647106171f,
+// 0.0440889485180378f, -0.3004696965217590f, -0.0765804797410965f,
+// -0.1106919124722481f, -0.1529326885938644f, 0.0334486216306686f,
+// -0.2880412042140961f, -0.0867229029536247f, 0.2715213298797607f,
+// 0.3455142080783844f, 0.0421868190169334f, 0.1088623777031898f,
+// 0.3530384302139282f, 0.1036236435174942f, -0.1811016649007797f,
+// -0.0371862575411797f, -0.0815502628684044f, -0.1272235512733459f,
+// 0.2390078902244568f, 0.1050499230623245f, -0.0332150124013424f,
+// 0.3028440773487091f, 0.0770981311798096f, 0.1602268666028976f,
+// 0.1337961256504059f, 0.1006771028041840f, 0.1102172881364822f,
+// 0.1848667412996292f, 0.1684325039386749f, 0.1242713704705238f,
+// -0.1786433309316635f, 0.1373559087514877f, 0.2225612848997116f,
+// 0.2258309721946716f, 0.1677368730306625f, -0.0262125637382269f,
+// 0.2297061383724213f, 0.1107719168066978f, -0.1793202161788940f,
+// 0.1616234928369522f, 0.0589479915797710f, -0.1556434482336044f,
+// -0.0371207147836685f, 0.0083158966153860f, -0.1116892471909523f,
+// -0.0387150160968304f, -0.0716182366013527f, -0.0084692370146513f,
+// -0.0897895693778992f, 0.0745867118239403f, 0.0287218261510134f,
+// 0.0329950228333473f, -0.0902610570192337f, 0.1138846948742867f,
+// -0.0855705514550209f, 0.1880635172128677f, 0.0976239517331123f,
+// -0.1371842175722122f, -0.0210956335067749f, 0.1651720106601715f,
+// -0.0196290351450443f, 0.0792955383658409f, -0.0648245885968208f,
+// 0.0803505405783653f, -0.0074715134687722f, 0.0806355923414230f,
+// 0.2270058244466782f, 0.0261932928115129f, 0.0842201709747314f,
+// 0.1268837302923203f, 0.0036683829966933f, -0.1418737769126892f,
+// -0.0057788044214249f, 0.1467448621988297f, -0.0514633320271969f,
+// -0.0323182605206966f, -0.3030799925327301f, -0.0392444245517254f,
+// 0.0727892071008682f, 0.1349033266305923f, 0.2553310692310333f,
+// -0.0151702389121056f, 0.2435233443975449f, -0.0339750684797764f,
+// 0.2393334656953812f, -0.0123280426487327f, -0.0960634201765060f,
+// -0.1998449265956879f, 0.0209492482244968f, -0.0379791297018528f,
+// -0.1656708866357803f, 0.0078368233516812f, -0.0195985324680805f,
+// 0.1247799396514893f, -0.1443238407373428f, 0.1085884571075439f,
+// 0.1078949421644211f, -0.0696595087647438f, 0.1288003325462341f,
+// -0.3970431089401245f, -0.1024801880121231f, -0.1233044415712357f,
+// -0.1463251858949661f, -0.1819592118263245f, 0.1154757887125015f,
+// -0.0568912848830223f, 0.1153363287448883f, 0.1257448494434357f,
+// 0.0358867906033993f, -0.0538437925279140f, 0.1358876377344131f,
+// -0.1802356392145157f, 0.2287918329238892f, 0.2034094035625458f,
+// 0.2011471092700958f, 0.0429091416299343f, 0.0681071951985359f,
+// -0.0563410185277462f, -0.0257276389747858f, 0.0843018889427185f,
+// 0.0909587815403938f, 0.0664033442735672f, -0.1758099496364594f,
+// -0.0571433268487453f, 0.1711259931325912f, -0.0571946017444134f,
+// 0.0362318903207779f, -0.0376639999449253f, -0.0447276122868061f,
+// -0.1592458039522171f, -0.1119785979390144f, -0.1096779480576515f,
+// 0.0285444818437099f, -0.1093029752373695f, 0.1144370138645172f,
+// -0.1207029223442078f, -0.1724279224872589f, 0.0867907255887985f,
+// -0.1668438911437988f, 0.0574829801917076f, 0.0075742588378489f,
+// -0.4059297442436218f, 0.0318493545055389f, 0.2434604167938232f,
+// -0.0547706782817841f, -0.0525891482830048f, -0.1989204585552216f,
+// 0.0056250733323395f, 0.2155371010303497f, -0.0341610573232174f,
+// 0.1930452138185501f, -0.0858703181147575f, -0.2017534673213959f,
+// -0.0631754472851753f, -0.1143154352903366f, -0.2424092143774033f,
+// 0.0802514851093292f, -0.0295923855155706f, -0.1905903220176697f,
+// 0.0619865767657757f, -0.0115450052544475f, 0.0010406150249764f,
+// -0.0041289851069450f, 0.0622245892882347f, -0.0558483861386776f,
+// 0.0473032332956791f, 0.0326454229652882f, -0.1524653136730194f,
+// -0.0574469417333603f, 0.1663832068443298f, 0.1108400523662567f,
+// 0.0999809801578522f, -0.3094341754913330f, -0.0091841602697968f,
+// 0.0163167547434568f, 0.0542269758880138f, -0.0496890656650066f,
+// -0.1506151854991913f, -0.1521467417478561f, 0.0759391859173775f,
+// -0.0630263015627861f, -0.1965887546539307f, -0.0461340881884098f,
+// -0.0444865338504314f, -0.1686454415321350f, -0.2084407657384872f,
+// 0.1662267148494720f, -0.0039567076601088f, -0.0072231283411384f,
+// 0.1545728147029877f, -0.0883008837699890f, 0.0321789607405663f,
+// 0.0811701267957687f, -0.1567204445600510f, -0.1264952421188354f,
+// 0.0034169857390225f, 0.0123839005827904f, -0.1233986690640450f,
+// 0.0326695479452610f, -0.0816870331764221f, 0.0920929834246635f,
+// -0.2903710901737213f, -0.2450475841760635f, -0.2261900007724762f,
+// -0.1987242996692657f, 0.2289467751979828f, 0.0014403652166948f,
+// 0.1992424726486206f, 0.0862834602594376f, 0.1167134195566177f,
+// -0.1827589720487595f, 0.0768386051058769f, 0.0307491738349199f,
+// 0.2430421411991119f, -0.3573895990848541f,
+// 0.3370340466499329f, 2.0849652290344238f, 0.1329426020383835f,
+// -0.1572283804416656f, 0.0471578054130077f, -0.2013432085514069f,
+// 0.1161739975214005f, -0.1567748039960861f, 0.1606635749340057f,
+// 0.0653541758656502f, -0.3098604977130890f, 0.1017888337373734f,
+// 0.3628154695034027f, 0.3304760158061981f, -0.1518701165914536f,
+// -0.3958520889282227f, 0.0589817650616169f, 0.1504663825035095f,
+// -0.0161890815943480f, -0.2737655937671661f, 0.3386678099632263f,
+// 0.2357666939496994f, -0.3556374609470367f, -0.0245309825986624f,
+// -0.1056125611066818f, 0.3172893226146698f, 0.2594008743762970f,
+// 0.1219205632805824f, -0.0999825894832611f, -0.2794743478298187f,
+// 0.1157096922397614f, 0.1565781682729721f, 0.0411747768521309f,
+// 0.2792751193046570f, 0.1570186465978622f, -0.3064492940902710f,
+// 0.0086790677160025f, -0.1550159156322479f, 0.0469419211149216f,
+// 0.2933839857578278f, 0.2129487097263336f, 0.2768996059894562f,
+// 0.0154878785833716f, -0.0568118020892143f, -0.1020661145448685f,
+// -0.2932409942150116f, 0.1264995038509369f, 0.1396111845970154f,
+// 0.2517127394676208f, -0.2926096618175507f, -0.2608516216278076f,
+// -0.1991807073354721f, 0.2141158580780029f, 0.3587532043457031f,
+// 0.0232614111155272f, -0.2246242761611938f, 0.1227321028709412f,
+// -0.3475298881530762f, 0.2817220091819763f, -0.3135817050933838f,
+// -0.0975279733538628f, -0.1108666509389877f, 0.2326308190822601f,
+// -0.0199119467288256f, 0.2253784984350204f, 0.0377116091549397f,
+// -0.0229906626045704f, -0.2973606884479523f, 0.3631399869918823f,
+// -0.1669698357582092f, -0.3082887232303619f, -0.1056536734104156f,
+// -0.1158916503190994f, 0.3736219406127930f, 0.3264681696891785f,
+// -0.0267933253198862f, 0.3791401684284210f, 0.0316867865622044f,
+// 0.0502604730427265f, 0.1557185798883438f, -0.0346261896193027f,
+// -0.0645264461636543f, 0.0572315715253353f, -0.0332104600965977f,
+// 0.0256134141236544f, 0.1023575887084007f, 0.2198790311813354f,
+// -0.0442465767264366f, -0.0133193023502827f, -0.1185472160577774f,
+// 0.0812267363071442f, -0.2494345754384995f, -0.1705005168914795f,
+// -0.0045740231871605f, -0.0404957160353661f, -0.0309661496430635f,
+// -0.2340346276760101f, 0.0749326944351196f, -0.1908318996429443f,
+// 0.0551319904625416f, -0.2492332756519318f, -0.0235312357544899f,
+// -0.1447597742080688f, 0.0237164665013552f, 0.0910343006253242f,
+// 0.0070272390730679f, 0.1561727076768875f, 0.1421970129013062f,
+// 0.1059679388999939f, 0.0650186762213707f, -0.1093990355730057f,
+// 0.1691722571849823f, 0.2379638850688934f, 0.0502412542700768f,
+// 0.1312682330608368f, -0.0046533378772438f, -0.0014604791067541f,
+// -0.0067207920365036f, -0.2238764315843582f, -0.0223157014697790f,
+// 0.1258720755577087f, 0.2007052004337311f, -0.0791026130318642f,
+// -0.0151007557287812f, 0.0506316497921944f, 0.1905005425214767f,
+// -0.0881387591362000f, -0.0552930794656277f, -0.1524098515510559f,
+// 0.1048249155282974f, 0.0441084504127502f, -0.0911782458424568f,
+// 0.0311593934893608f, -0.2103652805089951f, -0.2042523324489594f,
+// 0.1393611282110214f, 0.2503989338874817f, 0.0359291881322861f,
+// 0.1379293799400330f, 0.1933388561010361f, 0.2294242829084396f,
+// -0.0786202400922775f, -0.0623966790735722f, -0.1787032634019852f,
+// 0.0463836230337620f, 0.0538864880800247f, 0.0888256132602692f,
+// 0.2483182251453400f, 0.0234916359186172f, -0.0500691533088684f,
+// 0.1938209682703018f, -0.1515714079141617f, -0.3341847062110901f,
+// -0.0166291706264019f, -0.0219845119863749f, -0.0967859923839569f,
+// 0.0509403273463249f, -0.2420049011707306f, 0.0335948131978512f,
+// -0.0292916651815176f, 0.0252071693539619f, 0.1248414367437363f,
+// -0.1702518463134766f, -0.1873659193515778f, -0.0716366320848465f,
+// -0.0733235925436020f, 0.2222277969121933f, 0.1001015231013298f,
+// 0.1819871217012405f, 0.0825020372867584f, -0.0418447256088257f,
+// -0.1589778512716293f, 0.0781468152999878f, -0.1537659019231796f,
+// 0.0744322016835213f, 0.0589926950633526f, 0.0035929384175688f,
+// 0.2460537105798721f, -0.1437028795480728f, -0.0360978879034519f,
+// 0.1404655277729034f, -0.0045880246907473f, -0.1200385093688965f,
+// 0.1161482706665993f, -0.0993445664644241f, 0.1035206690430641f,
+// 0.2043389976024628f, 0.0066380770877004f, 0.1182640567421913f,
+// 0.1494064182043076f, 0.3085750341415405f, 0.2310723662376404f,
+// -0.1379791349172592f, -0.1877056658267975f, 0.1587389260530472f,
+// 0.1117305234074593f, -0.1185799688100815f, 0.1709762960672379f,
+// 0.0457643084228039f, -0.2255200892686844f, -0.1225367113947868f,
+// -0.1887516528367996f, -0.0411749407649040f, -0.1572306156158447f,
+// -0.0373850725591183f, -0.0516659021377563f, -0.0028457029256970f,
+// 0.1696260273456573f, 0.1106372922658920f, -0.2047734856605530f,
+// 0.0053880028426647f, -0.1328373700380325f, -0.0649224147200584f,
+// -0.0101982131600380f, 0.0770838484168053f, -0.0951460748910904f,
+// -0.2241573780775070f, -0.1490227133035660f, -0.0707198753952980f,
+// -0.2232327610254288f, 0.0298546496778727f, -0.1661320179700851f,
+// -0.0932367295026779f, 0.1693368554115295f, 0.1590259373188019f,
+// 0.0193731356412172f, -0.0657057464122772f, 0.1089156717061996f,
+// 0.1032359302043915f, 0.1619964241981506f, 0.0000137926263051f,
+// 0.0823598131537437f, -0.0912312939763069f, 0.1062601804733276f,
+// 0.0756709203124046f, -0.0121430503204465f, 0.0763056576251984f,
+// -0.0054127606563270f, -0.3388555645942688f, -0.0430928319692612f,
+// -0.0541323386132717f, 0.0204487442970276f, -0.2136927396059036f,
+// 0.0257074441760778f, -0.2725523710250854f, 0.0085609285160899f,
+// -0.0743933543562889f, 0.0447168461978436f, 0.1216988414525986f,
+// -0.0936483293771744f, -0.0364801958203316f, -0.1163876578211784f,
+// -0.1144527718424797f, 0.0996754318475723f, 0.1016776189208031f,
+// -0.0802735090255737f, 0.0420583747327328f, 0.1409213691949844f,
+// 0.1143178790807724f, 0.1809004843235016f, 0.1841068416833878f,
+// -0.0173659548163414f, -0.1322118341922760f, -0.1313337981700897f,
+// 0.0959200412034988f, 0.2102988213300705f, 0.2287792414426804f,
+// 0.3155713379383087f, 0.1476121395826340f, 0.2918182015419006f,
+// -0.1163526400923729f, 0.1988018453121185f, 0.1008848473429680f,
+// -0.2047589570283890f, -0.0620911046862602f, 0.1552779227495193f,
+// -0.1100812256336212f, -0.1536879539489746f, 1.0569953918457031f,
+// 0.3136036694049835f, 0.0432358235120773f, -0.0242086052894592f,
+// 0.8666443824768066f, 0.2703282535076141f, -0.1575263887643814f,
+// -0.6900277733802795f, 0.3240924775600433f, -0.2684019505977631f,
+// 0.1021989881992340f, -0.1503699272871017f, 0.2512529194355011f,
+// 0.2426625192165375f, 0.1820336878299713f, -0.0936641991138458f,
+// 0.2864372432231903f, -0.0844886600971222f, 0.2345096170902252f,
+// 0.1671409904956818f, -0.2909255027770996f, -0.2231021076440811f,
+// -0.0285452902317047f, -0.2902416884899139f, -0.0911809206008911f,
+// 0.1914344131946564f, 0.3196655809879303f, -0.0279632806777954f,
+// -0.0846583843231201f, -0.2666132152080536f, 0.1073178350925446f,
+// 0.0505908429622650f, 0.1508843600749969f, -0.2990425527095795f,
+// 0.0172648727893829f, -0.1562631875276566f, -0.1995172798633575f,
+// 0.1757102906703949f, -0.2895315289497375f, -0.2112935334444046f,
+// 0.2603401839733124f, -0.2312087565660477f, 0.2381831705570221f,
+// -0.1290394067764282f, -0.2417178153991699f, -0.0228334367275238f,
+// -0.2175087481737137f, 0.0927365422248840f, 0.2515943944454193f,
+// -0.2678905427455902f, -0.2392645329236984f, -0.0614089965820312f,
+// 0.0116340816020966f, 0.3061031401157379f, 0.2777076661586761f,
+// -0.1913124620914459f, 0.2306869328022003f, 0.2046033442020416f,
+// -0.2708279490470886f, 0.2188521325588226f, 0.3408154547214508f,
+// -0.0827629566192627f, 0.3052035272121429f, 0.3354517519474030f,
+// 0.0888060927391052f, 0.0076411962509155f, 0.2934277951717377f,
+// 0.2444260418415070f, 0.3364352881908417f, -0.2267208397388458f,
+// 0.1205825805664062f, 0.2158147394657135f, -0.2301437556743622f,
+// 0.0601432025432587f, -0.1920311152935028f, -0.2548098862171173f,
+// 0.3473303616046906f, -0.2866051793098450f, -0.3235993683338165f,
+// 0.2944277822971344f, 0.0385968759655952f, 0.0506347008049488f,
+// 0.0809904187917709f, -0.0053636352531612f, -0.0067958584986627f,
+// -0.0324983447790146f, 0.0305824782699347f, -0.1963013857603073f,
+// -0.2978549301624298f, 1.0000000000000000f};
diff --git a/NeuralAmpModeler/dsp/ImpulseResponse.cpp b/NeuralAmpModeler/dsp/ImpulseResponse.cpp
@@ -10,60 +10,60 @@
#include "ImpulseResponse.h"
-dsp::ImpulseResponse::ImpulseResponse(const WDL_String& fileName,
- const double sampleRate):
- mWavState(dsp::wav::LoadReturnCode::ERROR_OTHER)
-{
+dsp::ImpulseResponse::ImpulseResponse(const WDL_String &fileName,
+ const double sampleRate)
+ : mWavState(dsp::wav::LoadReturnCode::ERROR_OTHER) {
// Try to load the WAV
- this->mWavState = dsp::wav::Load(fileName, this->mRawAudio, this->mRawAudioSampleRate);
+ this->mWavState =
+ dsp::wav::Load(fileName, this->mRawAudio, this->mRawAudioSampleRate);
if (this->mWavState != dsp::wav::LoadReturnCode::SUCCESS) {
std::stringstream ss;
ss << "Failed to load IR at " << fileName.Get() << std::endl;
- }
- else
+ } else
// Set the weights based on the raw audio.
this->_SetWeights(sampleRate);
}
-iplug::sample** dsp::ImpulseResponse::Process(iplug::sample** inputs,
+iplug::sample **dsp::ImpulseResponse::Process(iplug::sample **inputs,
const size_t numChannels,
- const size_t numFrames)
-{
+ const size_t numFrames) {
this->_PrepareBuffers(numChannels, numFrames);
this->_UpdateHistory(inputs, numChannels, numFrames);
-
- for (size_t i=0, j=this->mHistoryIndex - this->mHistoryRequired; i<numFrames; i++, j++) {
- auto input = Eigen::Map<const Eigen::VectorXf>(&this->mHistory[j], this->mHistoryRequired+1);
- this->mOutputs[0][i] = (double) this->mWeight.dot(input);
+
+ for (size_t i = 0, j = this->mHistoryIndex - this->mHistoryRequired;
+ i < numFrames; i++, j++) {
+ auto input = Eigen::Map<const Eigen::VectorXf>(&this->mHistory[j],
+ this->mHistoryRequired + 1);
+ this->mOutputs[0][i] = (double)this->mWeight.dot(input);
}
// Copy out for more-than-mono.
- for (size_t c=1; c<numChannels; c++)
- for (size_t i=0; i<numFrames; i++)
+ for (size_t c = 1; c < numChannels; c++)
+ for (size_t i = 0; i < numFrames; i++)
this->mOutputs[c][i] = this->mOutputs[0][i];
-
+
this->_AdvanceHistoryIndex(numFrames);
return this->_GetPointers();
}
-void dsp::ImpulseResponse::_SetWeights(const double sampleRate)
-{
+void dsp::ImpulseResponse::_SetWeights(const double sampleRate) {
if (this->mRawAudioSampleRate == sampleRate) {
this->mResampled.resize(this->mRawAudio.size());
- memcpy(this->mResampled.data(), this->mRawAudio.data(), this->mResampled.size());
- }
- else {
+ memcpy(this->mResampled.data(), this->mRawAudio.data(),
+ this->mResampled.size());
+ } else {
// Cubic resampling
std::vector<float> padded;
padded.resize(this->mRawAudio.size() + 2);
padded[0] = 0.0f;
- padded[padded.size()-1] = 0.0f;
+ padded[padded.size() - 1] = 0.0f;
memcpy(padded.data() + 1, this->mRawAudio.data(), this->mRawAudio.size());
- dsp::ResampleCubic<float>(padded, this->mRawAudioSampleRate, sampleRate, 0.0, this->mResampled);
+ dsp::ResampleCubic<float>(padded, this->mRawAudioSampleRate, sampleRate,
+ 0.0, this->mResampled);
}
// Simple implementation w/ no resample...
const size_t irLength = std::min(this->mResampled.size(), this->mMaxLength);
this->mWeight.resize(irLength);
- for (size_t i=0, j=irLength-1; i<irLength; i++,j--)
+ for (size_t i = 0, j = irLength - 1; i < irLength; i++, j--)
this->mWeight[j] = this->mResampled[i];
this->mHistoryRequired = irLength - 1;
}
diff --git a/NeuralAmpModeler/dsp/ImpulseResponse.h b/NeuralAmpModeler/dsp/ImpulseResponse.h
@@ -13,36 +13,37 @@
#include <Eigen/Dense>
-#include "wdlstring.h" // WDL_String
-#include "IPlugConstants.h" // sample
+#include "IPlugConstants.h" // sample
#include "dsp.h"
#include "wav.h"
+#include "wdlstring.h" // WDL_String
namespace dsp {
- class ImpulseResponse : public History {
- public:
- ImpulseResponse(const WDL_String& fileName, const double sampleRate);
- iplug::sample** Process(iplug::sample** inputs,
- const size_t numChannels,
- const size_t numFrames) override;
- // TODO states for the IR class
- dsp::wav::LoadReturnCode GetWavState() const { return this->mWavState; };
- private:
- // Set the weights, given that the plugin is running at the provided sample rate.
- void _SetWeights(const double sampleRate);
-
- // State of audio
- dsp::wav::LoadReturnCode mWavState;
- // Keep a copy of the raw audio that was loaded so that it can be resampled
- std::vector<float> mRawAudio;
- double mRawAudioSampleRate;
- // Resampled to the required sample rate.
- std::vector<float> mResampled;
-
- const size_t mMaxLength = 8192;
- // The weights
- Eigen::VectorXf mWeight;
- };
+class ImpulseResponse : public History {
+public:
+ ImpulseResponse(const WDL_String &fileName, const double sampleRate);
+ iplug::sample **Process(iplug::sample **inputs, const size_t numChannels,
+ const size_t numFrames) override;
+ // TODO states for the IR class
+ dsp::wav::LoadReturnCode GetWavState() const { return this->mWavState; };
+
+private:
+ // Set the weights, given that the plugin is running at the provided sample
+ // rate.
+ void _SetWeights(const double sampleRate);
+
+ // State of audio
+ dsp::wav::LoadReturnCode mWavState;
+ // Keep a copy of the raw audio that was loaded so that it can be resampled
+ std::vector<float> mRawAudio;
+ double mRawAudioSampleRate;
+ // Resampled to the required sample rate.
+ std::vector<float> mResampled;
+
+ const size_t mMaxLength = 8192;
+ // The weights
+ Eigen::VectorXf mWeight;
};
+}; // namespace dsp
#endif /* ImpulseResponse_h */
diff --git a/NeuralAmpModeler/dsp/RecursiveLinearFilter.cpp b/NeuralAmpModeler/dsp/RecursiveLinearFilter.cpp
@@ -1,58 +1,58 @@
//
// RecursiveLinearFilter.cpp
-//
+//
//
// Created by Steven Atkinson on 12/28/22.
//
// See: https://webaudio.github.io/Audio-EQ-Cookbook/audio-eq-cookbook.html
-#include <algorithm> // std::fill
+#include <algorithm> // std::fill
#include <stdexcept>
#include "RecursiveLinearFilter.h"
recursive_linear_filter::Base::Base(const size_t inputDegree,
- const size_t outputDegree) :
-dsp::DSP(),
-mInputStart(inputDegree), // 1 is subtracted before first use
-mOutputStart(outputDegree)
-{
+ const size_t outputDegree)
+ : dsp::DSP(), mInputStart(inputDegree), // 1 is subtracted before first use
+ mOutputStart(outputDegree) {
this->mInputCoefficients.resize(inputDegree);
this->mOutputCoefficients.resize(outputDegree);
}
-iplug::sample** recursive_linear_filter::Base::Process(iplug::sample** inputs,
+iplug::sample **recursive_linear_filter::Base::Process(iplug::sample **inputs,
const size_t numChannels,
- const size_t numFrames)
-{
+ const size_t numFrames) {
this->_PrepareBuffers(numChannels, numFrames);
- long inputStart=0;
- long outputStart=0;
+ long inputStart = 0;
+ long outputStart = 0;
// Degree = longest history
- // E.g. if y[n] explicitly depends on x[n-2], then input degree is 3 (n,n-1,n-2).
- // NOTE: output degree is never 1 because y[n] is never used to explicitly calculate...itself!
+ // E.g. if y[n] explicitly depends on x[n-2], then input degree is 3
+ // (n,n-1,n-2). NOTE: output degree is never 1 because y[n] is never used to
+ // explicitly calculate...itself!
// 0,2,3,... are fine.
const size_t inputDegree = this->_GetInputDegree();
const size_t outputDegree = this->_GetOutputDegree();
- for (auto c=0; c<numChannels; c++) {
- inputStart = this->mInputStart; // Should be plenty fine
+ for (auto c = 0; c < numChannels; c++) {
+ inputStart = this->mInputStart; // Should be plenty fine
outputStart = this->mOutputStart;
- for (auto s=0; s<numFrames; s++) {
+ for (auto s = 0; s < numFrames; s++) {
double out = 0.0;
// Compute input terms
inputStart -= 1;
if (inputStart < 0)
inputStart = inputDegree - 1;
- this->mInputHistory[c][inputStart] = inputs[c][s]; // Store current input
- for (auto i=0; i<inputDegree; i++)
- out += this->mInputCoefficients[i] * this->mInputHistory[c][(inputStart + i) % inputDegree];
-
+ this->mInputHistory[c][inputStart] = inputs[c][s]; // Store current input
+ for (auto i = 0; i < inputDegree; i++)
+ out += this->mInputCoefficients[i] *
+ this->mInputHistory[c][(inputStart + i) % inputDegree];
+
// Output terms
outputStart -= 1;
if (outputStart < 0)
outputStart = outputDegree - 1;
- for (auto i=1; i<outputDegree; i++)
- out += this->mOutputCoefficients[i] * this->mOutputHistory[c][(outputStart + i) % outputDegree];
+ for (auto i = 1; i < outputDegree; i++)
+ out += this->mOutputCoefficients[i] *
+ this->mOutputHistory[c][(outputStart + i) % outputDegree];
// Store the output!
if (outputDegree >= 1)
this->mOutputHistory[c][outputStart] = out;
@@ -64,8 +64,8 @@ iplug::sample** recursive_linear_filter::Base::Process(iplug::sample** inputs,
return this->_GetPointers();
}
-void recursive_linear_filter::Base::_PrepareBuffers(const size_t numChannels, const size_t numFrames)
-{
+void recursive_linear_filter::Base::_PrepareBuffers(const size_t numChannels,
+ const size_t numFrames) {
// Check for new channel count *before* parent class ensures they match!
const bool newChannels = this->_GetNumChannels() != numChannels;
// Parent implementation takes care of mOutputs and mOutputPointers
@@ -75,22 +75,20 @@ void recursive_linear_filter::Base::_PrepareBuffers(const size_t numChannels, co
this->mOutputHistory.resize(numChannels);
const size_t inputDegree = this->_GetInputDegree();
const size_t outputDegree = this->_GetOutputDegree();
- for (auto c=0; c<numChannels; c++) {
+ for (auto c = 0; c < numChannels; c++) {
this->mInputHistory[c].resize(inputDegree);
this->mOutputHistory[c].resize(outputDegree);
- std::fill(this->mInputHistory[c].begin(), this->mInputHistory[c].end(), 0.0);
- std::fill(this->mOutputHistory[c].begin(), this->mOutputHistory[c].end(), 0.0);
+ std::fill(this->mInputHistory[c].begin(), this->mInputHistory[c].end(),
+ 0.0);
+ std::fill(this->mOutputHistory[c].begin(), this->mOutputHistory[c].end(),
+ 0.0);
}
}
}
-void recursive_linear_filter::Biquad::_AssignCoefficients(const double a0,
- const double a1,
- const double a2,
- const double b0,
- const double b1,
- const double b2)
-{
+void recursive_linear_filter::Biquad::_AssignCoefficients(
+ const double a0, const double a1, const double a2, const double b0,
+ const double b1, const double b2) {
this->mInputCoefficients[0] = b0 / a0;
this->mInputCoefficients[1] = b1 / a0;
this->mInputCoefficients[2] = b2 / a0;
@@ -100,61 +98,61 @@ void recursive_linear_filter::Biquad::_AssignCoefficients(const double a0,
this->mOutputCoefficients[2] = -a2 / a0;
}
-void recursive_linear_filter::LowShelf::SetParams(const recursive_linear_filter::BiquadParams ¶ms)
-{
+void recursive_linear_filter::LowShelf::SetParams(
+ const recursive_linear_filter::BiquadParams ¶ms) {
const double a = params.GetA();
const double omega_0 = params.GetOmega0();
const double alpha = params.GetAlpha(omega_0);
const double cosw = params.GetCosW(omega_0);
-
+
const double ap = a + 1.0;
const double am = a - 1.0;
const double roota2alpha = 2.0 * sqrt(a) * alpha;
-
+
const double b0 = a * (ap - am * cosw + roota2alpha);
const double b1 = 2.0 * a * (am - ap * cosw);
const double b2 = a * (ap - am * cosw - roota2alpha);
const double a0 = ap + am * cosw + roota2alpha;
const double a1 = -2.0 * (am + ap * cosw);
const double a2 = ap + am * cosw - roota2alpha;
-
+
this->_AssignCoefficients(a0, a1, a2, b0, b1, b2);
}
-void recursive_linear_filter::Peaking::SetParams(const recursive_linear_filter::BiquadParams ¶ms)
-{
+void recursive_linear_filter::Peaking::SetParams(
+ const recursive_linear_filter::BiquadParams ¶ms) {
const double a = params.GetA();
const double omega_0 = params.GetOmega0();
const double alpha = params.GetAlpha(omega_0);
const double cosw = params.GetCosW(omega_0);
-
+
const double b0 = 1.0 + alpha * a;
const double b1 = -2.0 * cosw;
const double b2 = 1.0 - alpha * a;
const double a0 = 1.0 + alpha / a;
const double a1 = -2.0 * cosw;
const double a2 = 1.0 - alpha / a;
-
+
this->_AssignCoefficients(a0, a1, a2, b0, b1, b2);
}
-void recursive_linear_filter::HighShelf::SetParams(const recursive_linear_filter::BiquadParams ¶ms)
-{
+void recursive_linear_filter::HighShelf::SetParams(
+ const recursive_linear_filter::BiquadParams ¶ms) {
const double a = params.GetA();
const double omega_0 = params.GetOmega0();
const double alpha = params.GetAlpha(omega_0);
const double cosw = params.GetCosW(omega_0);
-
+
const double roota2alpha = 2.0 * sqrt(a) * alpha;
const double ap = a + 1.0;
const double am = a - 1.0;
-
+
const double b0 = a * (ap + am * cosw + roota2alpha);
const double b1 = -2.0 * a * (am + ap * cosw);
const double b2 = a * (ap + am * cosw - roota2alpha);
const double a0 = ap - am * cosw + roota2alpha;
const double a1 = 2.0 * (am - ap * cosw);
const double a2 = ap - am * cosw - roota2alpha;
-
+
this->_AssignCoefficients(a0, a1, a2, b0, b1, b2);
}
diff --git a/NeuralAmpModeler/dsp/RecursiveLinearFilter.h b/NeuralAmpModeler/dsp/RecursiveLinearFilter.h
@@ -1,6 +1,6 @@
//
// RecursiveLinearFilter.h
-//
+//
//
// Created by Steven Atkinson on 12/28/22.
//
@@ -9,117 +9,118 @@
#ifndef RecursiveLinearFilter_h
#define RecursiveLinearFilter_h
-#include <cmath> // pow, sin
-#include <vector>
-#include "IPlugConstants.h" // sample
+#include "IPlugConstants.h" // sample
#include "dsp.h"
+#include <cmath> // pow, sin
+#include <vector>
#define MATH_PI 3.14159265358979323846
// TODO refactor base DSP into a common abstraction.
namespace recursive_linear_filter {
- class Base : public dsp::DSP {
- public:
- Base(const size_t inputDegree, const size_t outputDegree);
- iplug::sample** Process(iplug::sample** inputs,
- const size_t numChannels,
- const size_t numFrames) override;
- protected:
- // Methods
- size_t _GetInputDegree() const {return this->mInputCoefficients.size();};
- size_t _GetOutputDegree() const {return this->mOutputCoefficients.size();};
- // Additionally prepares mInputHistory and mOutputHistory.
- void _PrepareBuffers(const size_t numChannels, const size_t numFrames) override;
-
- // Coefficients for the DSP filter
- std::vector<double> mInputCoefficients;
- std::vector<double> mOutputCoefficients;
-
- // Arrays holding the history on which the filter depends recursively.
- // First index is channel
- // Second index, [0] is the current input/output, [1] is the previous, [2] is before that, etc.
- std::vector<std::vector<iplug::sample>> mInputHistory;
- std::vector<std::vector<iplug::sample>> mOutputHistory;
- // Indices for history.
- // Designates which index is currently "0". Use modulus to wrap around.
- long mInputStart;
- long mOutputStart;
- };
-
- class LevelParams : public dsp::Params {
- public:
- LevelParams(const double gain) : Params(), mGain(gain) {};
- double GetGain() const {return this->mGain;};
- private:
- // The gain (multiplicative, i.e. not dB)
- double mGain;
- };
-
- class Level : public Base {
- public:
- Level() : Base(1, 0) {};
- // Invalid usage: require a pointer to recursive_linear_filter::Params so
- // that SetCoefficients() is defined.
- void SetParams(const LevelParams ¶ms) {
- this->mInputCoefficients[0] = params.GetGain();
- };;
- };
-
- // The same 3 params (frequency, quality, gain) describe a bunch of filters.
- // (Low shelf, high shelf, peaking)
- class BiquadParams : public dsp::Params {
- public:
- BiquadParams(const double sampleRate,
- const double frequency,
- const double quality,
- const double gainDB) :
- dsp::Params(),
- mFrequency(frequency),
- mGainDB(gainDB),
- mQuality(quality),
- mSampleRate(sampleRate) {};
-
- // Parameters defined in
- // https://webaudio.github.io/Audio-EQ-Cookbook/audio-eq-cookbook.html
- double GetA() const {return pow(10.0, this->mGainDB / 40.0);};
- double GetOmega0() const {return 2.0 * MATH_PI * this->mFrequency / this->mSampleRate;};
- double GetAlpha(const double omega_0) const {return sin(omega_0) / (2.0 * this->mQuality);};
- double GetCosW(const double omega_0) const {return cos(omega_0);};
- private:
- double mFrequency;
- double mGainDB;
- double mQuality;
- double mSampleRate;
- };
-
- class Biquad : public Base {
- public:
- Biquad() : Base(3, 3) {};
- virtual void SetParams(const BiquadParams ¶ms) = 0;
- protected:
- void _AssignCoefficients(const double a0,
- const double a1,
- const double a2,
- const double b0,
- const double b1,
- const double b2);
- };
-
- class LowShelf : public Biquad {
- public:
- void SetParams(const BiquadParams ¶ms) override;
+class Base : public dsp::DSP {
+public:
+ Base(const size_t inputDegree, const size_t outputDegree);
+ iplug::sample **Process(iplug::sample **inputs, const size_t numChannels,
+ const size_t numFrames) override;
+
+protected:
+ // Methods
+ size_t _GetInputDegree() const { return this->mInputCoefficients.size(); };
+ size_t _GetOutputDegree() const { return this->mOutputCoefficients.size(); };
+ // Additionally prepares mInputHistory and mOutputHistory.
+ void _PrepareBuffers(const size_t numChannels,
+ const size_t numFrames) override;
+
+ // Coefficients for the DSP filter
+ std::vector<double> mInputCoefficients;
+ std::vector<double> mOutputCoefficients;
+
+ // Arrays holding the history on which the filter depends recursively.
+ // First index is channel
+ // Second index, [0] is the current input/output, [1] is the previous, [2] is
+ // before that, etc.
+ std::vector<std::vector<iplug::sample>> mInputHistory;
+ std::vector<std::vector<iplug::sample>> mOutputHistory;
+ // Indices for history.
+ // Designates which index is currently "0". Use modulus to wrap around.
+ long mInputStart;
+ long mOutputStart;
+};
+
+class LevelParams : public dsp::Params {
+public:
+ LevelParams(const double gain) : Params(), mGain(gain){};
+ double GetGain() const { return this->mGain; };
+
+private:
+ // The gain (multiplicative, i.e. not dB)
+ double mGain;
+};
+
+class Level : public Base {
+public:
+ Level() : Base(1, 0){};
+ // Invalid usage: require a pointer to recursive_linear_filter::Params so
+ // that SetCoefficients() is defined.
+ void SetParams(const LevelParams ¶ms) {
+ this->mInputCoefficients[0] = params.GetGain();
};
-
- class Peaking : public Biquad {
- public:
- void SetParams(const BiquadParams ¶ms) override;
+ ;
+};
+
+// The same 3 params (frequency, quality, gain) describe a bunch of filters.
+// (Low shelf, high shelf, peaking)
+class BiquadParams : public dsp::Params {
+public:
+ BiquadParams(const double sampleRate, const double frequency,
+ const double quality, const double gainDB)
+ : dsp::Params(), mFrequency(frequency), mGainDB(gainDB),
+ mQuality(quality), mSampleRate(sampleRate){};
+
+ // Parameters defined in
+ // https://webaudio.github.io/Audio-EQ-Cookbook/audio-eq-cookbook.html
+ double GetA() const { return pow(10.0, this->mGainDB / 40.0); };
+ double GetOmega0() const {
+ return 2.0 * MATH_PI * this->mFrequency / this->mSampleRate;
};
-
- class HighShelf : public Biquad {
- public:
- void SetParams(const BiquadParams ¶ms) override;
+ double GetAlpha(const double omega_0) const {
+ return sin(omega_0) / (2.0 * this->mQuality);
};
+ double GetCosW(const double omega_0) const { return cos(omega_0); };
+
+private:
+ double mFrequency;
+ double mGainDB;
+ double mQuality;
+ double mSampleRate;
+};
+
+class Biquad : public Base {
+public:
+ Biquad() : Base(3, 3){};
+ virtual void SetParams(const BiquadParams ¶ms) = 0;
+
+protected:
+ void _AssignCoefficients(const double a0, const double a1, const double a2,
+ const double b0, const double b1, const double b2);
+};
+
+class LowShelf : public Biquad {
+public:
+ void SetParams(const BiquadParams ¶ms) override;
+};
+
+class Peaking : public Biquad {
+public:
+ void SetParams(const BiquadParams ¶ms) override;
+};
+
+class HighShelf : public Biquad {
+public:
+ void SetParams(const BiquadParams ¶ms) override;
};
+}; // namespace recursive_linear_filter
#endif /* RecursiveLinearFilter_h */
diff --git a/NeuralAmpModeler/dsp/Resample.h b/NeuralAmpModeler/dsp/Resample.h
@@ -9,73 +9,79 @@
#define Resample_h
#include <cmath>
-#include <vector>
#include <stdexcept>
+#include <vector>
namespace dsp {
- // Resample a provided vector in inputs to outputs.
- // Creates an array of the required length to fill all points from the SECOND
- // input to the SECOND-TO-LAST input point, exclusive.
- // (Seconds bc cubic. and ew want to only interpoalte between points 2 and
- // 3.)
- // tOutputStart: location of first output point relative to the second input
- // point (should be >=0.0)
- template<typename T>
- void ResampleCubic(const std::vector<T>& inputs,
- const double originalSampleRate,
- const double desiredSampleRate,
- const double tOutputStart,
- std::vector<T>& outputs);
- // Interpolate the 4 provided equispaced points to x in [-1,2]
- template<typename T>
- T _CubicInterpolation(T p[4], T x) {
- return p[1] + 0.5 * x * (p[2] - p[0] + x * (2.0 * p[0] - 5.0 * p[1] + 4.0 * p[2] - p[3] + x * (3.0 * (p[1] - p[2]) + p[3] - p[0])));
- };
+// Resample a provided vector in inputs to outputs.
+// Creates an array of the required length to fill all points from the SECOND
+// input to the SECOND-TO-LAST input point, exclusive.
+// (Seconds bc cubic. and ew want to only interpoalte between points 2 and
+// 3.)
+// tOutputStart: location of first output point relative to the second input
+// point (should be >=0.0)
+template <typename T>
+void ResampleCubic(const std::vector<T> &inputs,
+ const double originalSampleRate,
+ const double desiredSampleRate, const double tOutputStart,
+ std::vector<T> &outputs);
+// Interpolate the 4 provided equispaced points to x in [-1,2]
+template <typename T> T _CubicInterpolation(T p[4], T x) {
+ return p[1] + 0.5 * x *
+ (p[2] - p[0] +
+ x * (2.0 * p[0] - 5.0 * p[1] + 4.0 * p[2] - p[3] +
+ x * (3.0 * (p[1] - p[2]) + p[3] - p[0])));
};
+}; // namespace dsp
template <typename T>
-void dsp::ResampleCubic(const std::vector<T>& inputs,
+void dsp::ResampleCubic(const std::vector<T> &inputs,
const double originalSampleRate,
const double desiredSampleRate,
- const double tOutputStart,
- std::vector<T>& outputs)
-{
- if (tOutputStart < 0.0)
- throw std::runtime_error("Starting time must be non-negative");
+ const double tOutputStart, std::vector<T> &outputs) {
+ if (tOutputStart < 0.0)
+ throw std::runtime_error("Starting time must be non-negative");
+
+ // Time increment for each sample in the original audio file
+ const double timeIncrement = 1.0 / originalSampleRate;
- // Time increment for each sample in the original audio file
- const double timeIncrement = 1.0 / originalSampleRate;
+ // Time increment for each sample in the resampled audio file
+ const double resampledTimeIncrement = 1.0 / desiredSampleRate;
- // Time increment for each sample in the resampled audio file
- const double resampledTimeIncrement = 1.0 / desiredSampleRate;
-
- // Current time
- double time = timeIncrement + tOutputStart;
+ // Current time
+ double time = timeIncrement + tOutputStart;
- const double endTimeOriginal = (inputs.size() - 1) * timeIncrement;
- while (time < endTimeOriginal) {
- // Find the index of the sample in the original audio file that is just before the current time in the resampled audio file
- int index = (long) std::floor(time / timeIncrement);
+ const double endTimeOriginal = (inputs.size() - 1) * timeIncrement;
+ while (time < endTimeOriginal) {
+ // Find the index of the sample in the original audio file that is just
+ // before the current time in the resampled audio file
+ int index = (long)std::floor(time / timeIncrement);
- // Calculate the time difference between the current time in the resampled audio file and the sample in the original audio file
- double timeDifference = time - index * timeIncrement;
+ // Calculate the time difference between the current time in the resampled
+ // audio file and the sample in the original audio file
+ double timeDifference = time - index * timeIncrement;
- // Get the four surrounding samples in the original audio file for cubic interpolation
- double p[4];
- p[0] = (index == 0) ? inputs[0] : inputs[index - 1];
- p[1] = inputs[index];
- p[2] = (index == inputs.size() - 1) ? inputs[inputs.size() - 1] : inputs[index + 1];
- p[3] = (index == inputs.size() - 2) ? inputs[inputs.size() - 1] : inputs[index + 2];
+ // Get the four surrounding samples in the original audio file for cubic
+ // interpolation
+ double p[4];
+ p[0] = (index == 0) ? inputs[0] : inputs[index - 1];
+ p[1] = inputs[index];
+ p[2] = (index == inputs.size() - 1) ? inputs[inputs.size() - 1]
+ : inputs[index + 1];
+ p[3] = (index == inputs.size() - 2) ? inputs[inputs.size() - 1]
+ : inputs[index + 2];
- // Use cubic interpolation to estimate the value of the audio signal at the current time in the resampled audio file
- T resampledValue = dsp::_CubicInterpolation(p, timeDifference / timeIncrement);
+ // Use cubic interpolation to estimate the value of the audio signal at the
+ // current time in the resampled audio file
+ T resampledValue =
+ dsp::_CubicInterpolation(p, timeDifference / timeIncrement);
- // Add the estimated value to the resampled audio file
- outputs.push_back(resampledValue);
+ // Add the estimated value to the resampled audio file
+ outputs.push_back(resampledValue);
- // Update the current time in the resampled audio file
- time += resampledTimeIncrement;
- }
+ // Update the current time in the resampled audio file
+ time += resampledTimeIncrement;
+ }
}
#endif /* Resample_h */
diff --git a/NeuralAmpModeler/dsp/activations.h b/NeuralAmpModeler/dsp/activations.h
@@ -1,12 +1,8 @@
#pragma once
-#include <cmath> // expf
+#include <cmath> // expf
namespace activations {
- float relu(float x) {
- return x > 0.0f ? x : 0.0f;
- };
- float sigmoid(float x) {
- return 1.0f / (1.0f + expf(-x));
- };
-}; // namespace activations
-\ No newline at end of file
+float relu(float x) { return x > 0.0f ? x : 0.0f; };
+float sigmoid(float x) { return 1.0f / (1.0f + expf(-x)); };
+}; // namespace activations
+\ No newline at end of file
diff --git a/NeuralAmpModeler/dsp/cnpy.cpp b/NeuralAmpModeler/dsp/cnpy.cpp
@@ -1,348 +1,384 @@
-//Copyright (C) 2011 Carl Rogers
-//Released under MIT License
-//license available in LICENSE file, or at http://www.opensource.org/licenses/mit-license.php
-
-#include"cnpy.h"
-#include<cerrno>
-#include<complex>
-#include<cstdlib>
-#include<algorithm>
-#include<cstring>
-#include<iomanip>
-#include<stdint.h>
-#include<stdexcept>
-#include<iostream>
+// Copyright (C) 2011 Carl Rogers
+// Released under MIT License
+// license available in LICENSE file, or at
+// http://www.opensource.org/licenses/mit-license.php
+
+#include "cnpy.h"
+#include <algorithm>
+#include <cerrno>
+#include <complex>
+#include <cstdlib>
+#include <cstring>
+#include <iomanip>
+#include <iostream>
#include <regex>
+#include <stdexcept>
+#include <stdint.h>
char cnpy::BigEndianTest() {
- int x = 1;
- return (((char *)&x)[0]) ? '<' : '>';
+ int x = 1;
+ return (((char *)&x)[0]) ? '<' : '>';
}
-char cnpy::map_type(const std::type_info& t)
-{
- if(t == typeid(float) ) return 'f';
- if(t == typeid(double) ) return 'f';
- if(t == typeid(long double) ) return 'f';
-
- if(t == typeid(int) ) return 'i';
- if(t == typeid(char) ) return 'i';
- if(t == typeid(short) ) return 'i';
- if(t == typeid(long) ) return 'i';
- if(t == typeid(long long) ) return 'i';
-
- if(t == typeid(unsigned char) ) return 'u';
- if(t == typeid(unsigned short) ) return 'u';
- if(t == typeid(unsigned long) ) return 'u';
- if(t == typeid(unsigned long long) ) return 'u';
- if(t == typeid(unsigned int) ) return 'u';
-
- if(t == typeid(bool) ) return 'b';
-
- if(t == typeid(std::complex<float>) ) return 'c';
- if(t == typeid(std::complex<double>) ) return 'c';
- if(t == typeid(std::complex<long double>) ) return 'c';
-
- else return '?';
+char cnpy::map_type(const std::type_info &t) {
+ if (t == typeid(float))
+ return 'f';
+ if (t == typeid(double))
+ return 'f';
+ if (t == typeid(long double))
+ return 'f';
+
+ if (t == typeid(int))
+ return 'i';
+ if (t == typeid(char))
+ return 'i';
+ if (t == typeid(short))
+ return 'i';
+ if (t == typeid(long))
+ return 'i';
+ if (t == typeid(long long))
+ return 'i';
+
+ if (t == typeid(unsigned char))
+ return 'u';
+ if (t == typeid(unsigned short))
+ return 'u';
+ if (t == typeid(unsigned long))
+ return 'u';
+ if (t == typeid(unsigned long long))
+ return 'u';
+ if (t == typeid(unsigned int))
+ return 'u';
+
+ if (t == typeid(bool))
+ return 'b';
+
+ if (t == typeid(std::complex<float>))
+ return 'c';
+ if (t == typeid(std::complex<double>))
+ return 'c';
+ if (t == typeid(std::complex<long double>))
+ return 'c';
+
+ else
+ return '?';
}
-template<> std::vector<char>& cnpy::operator+=(std::vector<char>& lhs, const std::string rhs) {
- lhs.insert(lhs.end(),rhs.begin(),rhs.end());
- return lhs;
+template <>
+std::vector<char> &cnpy::operator+=(std::vector<char> &lhs,
+ const std::string rhs) {
+ lhs.insert(lhs.end(), rhs.begin(), rhs.end());
+ return lhs;
}
-template<> std::vector<char>& cnpy::operator+=(std::vector<char>& lhs, const char* rhs) {
- //write in little endian
- size_t len = strlen(rhs);
- lhs.reserve(len);
- for(size_t byte = 0; byte < len; byte++) {
- lhs.push_back(rhs[byte]);
- }
- return lhs;
+template <>
+std::vector<char> &cnpy::operator+=(std::vector<char> &lhs, const char *rhs) {
+ // write in little endian
+ size_t len = strlen(rhs);
+ lhs.reserve(len);
+ for (size_t byte = 0; byte < len; byte++) {
+ lhs.push_back(rhs[byte]);
+ }
+ return lhs;
}
-void cnpy::parse_npy_header(unsigned char* buffer,size_t& word_size, std::vector<size_t>& shape, bool& fortran_order) {
- //std::string magic_string(buffer,6);
- uint8_t major_version = *reinterpret_cast<uint8_t*>(buffer+6);
- uint8_t minor_version = *reinterpret_cast<uint8_t*>(buffer+7);
- uint16_t header_len = *reinterpret_cast<uint16_t*>(buffer+8);
- std::string header(reinterpret_cast<char*>(buffer+9),header_len);
-
- size_t loc1, loc2;
-
- //fortran order
- loc1 = header.find("fortran_order")+16;
- fortran_order = (header.substr(loc1,4) == "True" ? true : false);
-
- //shape
- loc1 = header.find("(");
- loc2 = header.find(")");
-
- std::regex num_regex("[0-9][0-9]*");
- std::smatch sm;
- shape.clear();
-
- std::string str_shape = header.substr(loc1+1,loc2-loc1-1);
- while(std::regex_search(str_shape, sm, num_regex)) {
- shape.push_back(std::stoi(sm[0].str()));
- str_shape = sm.suffix().str();
- }
-
- //endian, word size, data type
- //byte order code | stands for not applicable.
- //not sure when this applies except for byte array
- loc1 = header.find("descr")+9;
- bool littleEndian = (header[loc1] == '<' || header[loc1] == '|' ? true : false);
- assert(littleEndian);
-
- //char type = header[loc1+1];
- //assert(type == map_type(T));
-
- std::string str_ws = header.substr(loc1+2);
- loc2 = str_ws.find("'");
- word_size = atoi(str_ws.substr(0,loc2).c_str());
+void cnpy::parse_npy_header(unsigned char *buffer, size_t &word_size,
+ std::vector<size_t> &shape, bool &fortran_order) {
+ // std::string magic_string(buffer,6);
+ uint8_t major_version = *reinterpret_cast<uint8_t *>(buffer + 6);
+ uint8_t minor_version = *reinterpret_cast<uint8_t *>(buffer + 7);
+ uint16_t header_len = *reinterpret_cast<uint16_t *>(buffer + 8);
+ std::string header(reinterpret_cast<char *>(buffer + 9), header_len);
+
+ size_t loc1, loc2;
+
+ // fortran order
+ loc1 = header.find("fortran_order") + 16;
+ fortran_order = (header.substr(loc1, 4) == "True" ? true : false);
+
+ // shape
+ loc1 = header.find("(");
+ loc2 = header.find(")");
+
+ std::regex num_regex("[0-9][0-9]*");
+ std::smatch sm;
+ shape.clear();
+
+ std::string str_shape = header.substr(loc1 + 1, loc2 - loc1 - 1);
+ while (std::regex_search(str_shape, sm, num_regex)) {
+ shape.push_back(std::stoi(sm[0].str()));
+ str_shape = sm.suffix().str();
+ }
+
+ // endian, word size, data type
+ // byte order code | stands for not applicable.
+ // not sure when this applies except for byte array
+ loc1 = header.find("descr") + 9;
+ bool littleEndian =
+ (header[loc1] == '<' || header[loc1] == '|' ? true : false);
+ assert(littleEndian);
+
+ // char type = header[loc1+1];
+ // assert(type == map_type(T));
+
+ std::string str_ws = header.substr(loc1 + 2);
+ loc2 = str_ws.find("'");
+ word_size = atoi(str_ws.substr(0, loc2).c_str());
}
-void cnpy::parse_npy_header(FILE* fp, size_t& word_size, std::vector<size_t>& shape, bool& fortran_order) {
- char buffer[256];
- size_t res = fread(buffer,sizeof(char),11,fp);
- if(res != 11)
- throw std::runtime_error("parse_npy_header: failed fread");
- std::string header = fgets(buffer,256,fp);
- assert(header[header.size()-1] == '\n');
-
- size_t loc1, loc2;
-
- //fortran order
- loc1 = header.find("fortran_order");
- if (loc1 == std::string::npos)
- throw std::runtime_error("parse_npy_header: failed to find header keyword: 'fortran_order'");
- loc1 += 16;
- fortran_order = (header.substr(loc1,4) == "True" ? true : false);
-
- //shape
- loc1 = header.find("(");
- loc2 = header.find(")");
- if (loc1 == std::string::npos || loc2 == std::string::npos)
- throw std::runtime_error("parse_npy_header: failed to find header keyword: '(' or ')'");
-
- std::regex num_regex("[0-9][0-9]*");
- std::smatch sm;
- shape.clear();
-
- std::string str_shape = header.substr(loc1+1,loc2-loc1-1);
- while(std::regex_search(str_shape, sm, num_regex)) {
- shape.push_back(std::stoi(sm[0].str()));
- str_shape = sm.suffix().str();
- }
-
- //endian, word size, data type
- //byte order code | stands for not applicable.
- //not sure when this applies except for byte array
- loc1 = header.find("descr");
- if (loc1 == std::string::npos)
- throw std::runtime_error("parse_npy_header: failed to find header keyword: 'descr'");
- loc1 += 9;
- bool littleEndian = (header[loc1] == '<' || header[loc1] == '|' ? true : false);
- assert(littleEndian);
-
- //char type = header[loc1+1];
- //assert(type == map_type(T));
-
- std::string str_ws = header.substr(loc1+2);
- loc2 = str_ws.find("'");
- word_size = atoi(str_ws.substr(0,loc2).c_str());
+void cnpy::parse_npy_header(FILE *fp, size_t &word_size,
+ std::vector<size_t> &shape, bool &fortran_order) {
+ char buffer[256];
+ size_t res = fread(buffer, sizeof(char), 11, fp);
+ if (res != 11)
+ throw std::runtime_error("parse_npy_header: failed fread");
+ std::string header = fgets(buffer, 256, fp);
+ assert(header[header.size() - 1] == '\n');
+
+ size_t loc1, loc2;
+
+ // fortran order
+ loc1 = header.find("fortran_order");
+ if (loc1 == std::string::npos)
+ throw std::runtime_error(
+ "parse_npy_header: failed to find header keyword: 'fortran_order'");
+ loc1 += 16;
+ fortran_order = (header.substr(loc1, 4) == "True" ? true : false);
+
+ // shape
+ loc1 = header.find("(");
+ loc2 = header.find(")");
+ if (loc1 == std::string::npos || loc2 == std::string::npos)
+ throw std::runtime_error(
+ "parse_npy_header: failed to find header keyword: '(' or ')'");
+
+ std::regex num_regex("[0-9][0-9]*");
+ std::smatch sm;
+ shape.clear();
+
+ std::string str_shape = header.substr(loc1 + 1, loc2 - loc1 - 1);
+ while (std::regex_search(str_shape, sm, num_regex)) {
+ shape.push_back(std::stoi(sm[0].str()));
+ str_shape = sm.suffix().str();
+ }
+
+ // endian, word size, data type
+ // byte order code | stands for not applicable.
+ // not sure when this applies except for byte array
+ loc1 = header.find("descr");
+ if (loc1 == std::string::npos)
+ throw std::runtime_error(
+ "parse_npy_header: failed to find header keyword: 'descr'");
+ loc1 += 9;
+ bool littleEndian =
+ (header[loc1] == '<' || header[loc1] == '|' ? true : false);
+ assert(littleEndian);
+
+ // char type = header[loc1+1];
+ // assert(type == map_type(T));
+
+ std::string str_ws = header.substr(loc1 + 2);
+ loc2 = str_ws.find("'");
+ word_size = atoi(str_ws.substr(0, loc2).c_str());
}
-//void cnpy::parse_zip_footer(FILE* fp, uint16_t& nrecs, size_t& global_header_size, size_t& global_header_offset)
+// void cnpy::parse_zip_footer(FILE* fp, uint16_t& nrecs, size_t&
+// global_header_size, size_t& global_header_offset)
//{
-// std::vector<char> footer(22);
-// fseek(fp,-22,SEEK_END);
-// size_t res = fread(&footer[0],sizeof(char),22,fp);
-// if(res != 22)
-// throw std::runtime_error("parse_zip_footer: failed fread");
-//
-// uint16_t disk_no, disk_start, nrecs_on_disk, comment_len;
-// disk_no = *(uint16_t*) &footer[4];
-// disk_start = *(uint16_t*) &footer[6];
-// nrecs_on_disk = *(uint16_t*) &footer[8];
-// nrecs = *(uint16_t*) &footer[10];
-// global_header_size = *(uint32_t*) &footer[12];
-// global_header_offset = *(uint32_t*) &footer[16];
-// comment_len = *(uint16_t*) &footer[20];
-//
-// assert(disk_no == 0);
-// assert(disk_start == 0);
-// assert(nrecs_on_disk == nrecs);
-// assert(comment_len == 0);
-//}
-
-cnpy::NpyArray load_the_npy_file(FILE* fp) {
- std::vector<size_t> shape;
- size_t word_size;
- bool fortran_order;
- cnpy::parse_npy_header(fp,word_size,shape,fortran_order);
-
- cnpy::NpyArray arr(shape, word_size, fortran_order);
- size_t nread = fread(arr.data<char>(),1,arr.num_bytes(),fp);
- if(nread != arr.num_bytes())
- throw std::runtime_error("load_the_npy_file: failed fread");
- return arr;
+// std::vector<char> footer(22);
+// fseek(fp,-22,SEEK_END);
+// size_t res = fread(&footer[0],sizeof(char),22,fp);
+// if(res != 22)
+// throw std::runtime_error("parse_zip_footer: failed fread");
+//
+// uint16_t disk_no, disk_start, nrecs_on_disk, comment_len;
+// disk_no = *(uint16_t*) &footer[4];
+// disk_start = *(uint16_t*) &footer[6];
+// nrecs_on_disk = *(uint16_t*) &footer[8];
+// nrecs = *(uint16_t*) &footer[10];
+// global_header_size = *(uint32_t*) &footer[12];
+// global_header_offset = *(uint32_t*) &footer[16];
+// comment_len = *(uint16_t*) &footer[20];
+//
+// assert(disk_no == 0);
+// assert(disk_start == 0);
+// assert(nrecs_on_disk == nrecs);
+// assert(comment_len == 0);
+// }
+
+cnpy::NpyArray load_the_npy_file(FILE *fp) {
+ std::vector<size_t> shape;
+ size_t word_size;
+ bool fortran_order;
+ cnpy::parse_npy_header(fp, word_size, shape, fortran_order);
+
+ cnpy::NpyArray arr(shape, word_size, fortran_order);
+ size_t nread = fread(arr.data<char>(), 1, arr.num_bytes(), fp);
+ if (nread != arr.num_bytes())
+ throw std::runtime_error("load_the_npy_file: failed fread");
+ return arr;
}
-//cnpy::NpyArray load_the_npz_array(FILE* fp, uint32_t compr_bytes, uint32_t uncompr_bytes) {
+// cnpy::NpyArray load_the_npz_array(FILE* fp, uint32_t compr_bytes, uint32_t
+// uncompr_bytes) {
+//
+// std::vector<unsigned char> buffer_compr(compr_bytes);
+// std::vector<unsigned char> buffer_uncompr(uncompr_bytes);
+// size_t nread = fread(&buffer_compr[0],1,compr_bytes,fp);
+// if(nread != compr_bytes)
+// throw std::runtime_error("load_the_npy_file: failed fread");
+//
+// int err;
+// z_stream d_stream;
+//
+// d_stream.zalloc = Z_NULL;
+// d_stream.zfree = Z_NULL;
+// d_stream.opaque = Z_NULL;
+// d_stream.avail_in = 0;
+// d_stream.next_in = Z_NULL;
+// err = inflateInit2(&d_stream, -MAX_WBITS);
+//
+// d_stream.avail_in = compr_bytes;
+// d_stream.next_in = &buffer_compr[0];
+// d_stream.avail_out = uncompr_bytes;
+// d_stream.next_out = &buffer_uncompr[0];
+//
+// err = inflate(&d_stream, Z_FINISH);
+// err = inflateEnd(&d_stream);
+//
+// std::vector<size_t> shape;
+// size_t word_size;
+// bool fortran_order;
+// cnpy::parse_npy_header(&buffer_uncompr[0],word_size,shape,fortran_order);
+//
+// cnpy::NpyArray array(shape, word_size, fortran_order);
+//
+// size_t offset = uncompr_bytes - array.num_bytes();
+// memcpy(array.data<unsigned
+// char>(),&buffer_uncompr[0]+offset,array.num_bytes());
+//
+// return array;
+// }
+//
+// cnpy::npz_t cnpy::npz_load(std::string fname) {
+// FILE* fp = fopen(fname.c_str(),"rb");
+//
+// if(!fp) {
+// throw std::runtime_error("npz_load: Error! Unable to open file
+// "+fname+"!");
+// }
+//
+// cnpy::npz_t arrays;
+//
+// while(1) {
+// std::vector<char> local_header(30);
+// size_t headerres = fread(&local_header[0],sizeof(char),30,fp);
+// if(headerres != 30)
+// throw std::runtime_error("npz_load: failed fread");
//
-// std::vector<unsigned char> buffer_compr(compr_bytes);
-// std::vector<unsigned char> buffer_uncompr(uncompr_bytes);
-// size_t nread = fread(&buffer_compr[0],1,compr_bytes,fp);
-// if(nread != compr_bytes)
-// throw std::runtime_error("load_the_npy_file: failed fread");
-//
-// int err;
-// z_stream d_stream;
-//
-// d_stream.zalloc = Z_NULL;
-// d_stream.zfree = Z_NULL;
-// d_stream.opaque = Z_NULL;
-// d_stream.avail_in = 0;
-// d_stream.next_in = Z_NULL;
-// err = inflateInit2(&d_stream, -MAX_WBITS);
-//
-// d_stream.avail_in = compr_bytes;
-// d_stream.next_in = &buffer_compr[0];
-// d_stream.avail_out = uncompr_bytes;
-// d_stream.next_out = &buffer_uncompr[0];
-//
-// err = inflate(&d_stream, Z_FINISH);
-// err = inflateEnd(&d_stream);
-//
-// std::vector<size_t> shape;
-// size_t word_size;
-// bool fortran_order;
-// cnpy::parse_npy_header(&buffer_uncompr[0],word_size,shape,fortran_order);
-//
-// cnpy::NpyArray array(shape, word_size, fortran_order);
-//
-// size_t offset = uncompr_bytes - array.num_bytes();
-// memcpy(array.data<unsigned char>(),&buffer_uncompr[0]+offset,array.num_bytes());
-//
-// return array;
-//}
-//
-//cnpy::npz_t cnpy::npz_load(std::string fname) {
-// FILE* fp = fopen(fname.c_str(),"rb");
-//
-// if(!fp) {
-// throw std::runtime_error("npz_load: Error! Unable to open file "+fname+"!");
-// }
-//
-// cnpy::npz_t arrays;
-//
-// while(1) {
-// std::vector<char> local_header(30);
-// size_t headerres = fread(&local_header[0],sizeof(char),30,fp);
-// if(headerres != 30)
-// throw std::runtime_error("npz_load: failed fread");
-//
-// //if we've reached the global header, stop reading
-// if(local_header[2] != 0x03 || local_header[3] != 0x04) break;
-//
-// //read in the variable name
-// uint16_t name_len = *(uint16_t*) &local_header[26];
-// std::string varname(name_len,' ');
-// size_t vname_res = fread(&varname[0],sizeof(char),name_len,fp);
-// if(vname_res != name_len)
-// throw std::runtime_error("npz_load: failed fread");
-//
-// //erase the lagging .npy
-// varname.erase(varname.end()-4,varname.end());
-//
-// //read in the extra field
-// uint16_t extra_field_len = *(uint16_t*) &local_header[28];
-// if(extra_field_len > 0) {
-// std::vector<char> buff(extra_field_len);
-// size_t efield_res = fread(&buff[0],sizeof(char),extra_field_len,fp);
-// if(efield_res != extra_field_len)
-// throw std::runtime_error("npz_load: failed fread");
-// }
-//
-// uint16_t compr_method = *reinterpret_cast<uint16_t*>(&local_header[0]+8);
-// uint32_t compr_bytes = *reinterpret_cast<uint32_t*>(&local_header[0]+18);
-// uint32_t uncompr_bytes = *reinterpret_cast<uint32_t*>(&local_header[0]+22);
-//
-// if(compr_method == 0) {arrays[varname] = load_the_npy_file(fp);}
-// else {arrays[varname] = load_the_npz_array(fp,compr_bytes,uncompr_bytes);}
-// }
-//
-// fclose(fp);
-// return arrays;
-//}
-//
-//cnpy::NpyArray cnpy::npz_load(std::string fname, std::string varname) {
-// FILE* fp = fopen(fname.c_str(),"rb");
-//
-// if(!fp) throw std::runtime_error("npz_load: Unable to open file "+fname);
-//
-// while(1) {
-// std::vector<char> local_header(30);
-// size_t header_res = fread(&local_header[0],sizeof(char),30,fp);
-// if(header_res != 30)
-// throw std::runtime_error("npz_load: failed fread");
-//
-// //if we've reached the global header, stop reading
-// if(local_header[2] != 0x03 || local_header[3] != 0x04) break;
-//
-// //read in the variable name
-// uint16_t name_len = *(uint16_t*) &local_header[26];
-// std::string vname(name_len,' ');
-// size_t vname_res = fread(&vname[0],sizeof(char),name_len,fp);
-// if(vname_res != name_len)
-// throw std::runtime_error("npz_load: failed fread");
-// vname.erase(vname.end()-4,vname.end()); //erase the lagging .npy
-//
-// //read in the extra field
-// uint16_t extra_field_len = *(uint16_t*) &local_header[28];
-// fseek(fp,extra_field_len,SEEK_CUR); //skip past the extra field
-//
-// uint16_t compr_method = *reinterpret_cast<uint16_t*>(&local_header[0]+8);
-// uint32_t compr_bytes = *reinterpret_cast<uint32_t*>(&local_header[0]+18);
-// uint32_t uncompr_bytes = *reinterpret_cast<uint32_t*>(&local_header[0]+22);
-//
-// if(vname == varname) {
-// NpyArray array = (compr_method == 0) ? load_the_npy_file(fp) : load_the_npz_array(fp,compr_bytes,uncompr_bytes);
-// fclose(fp);
-// return array;
-// }
-// else {
-// //skip past the data
-// uint32_t size = *(uint32_t*) &local_header[22];
-// fseek(fp,size,SEEK_CUR);
-// }
-// }
-//
-// fclose(fp);
-//
-// //if we get here, we haven't found the variable in the file
-// throw std::runtime_error("npz_load: Variable name "+varname+" not found in "+fname);
-//}
+// //if we've reached the global header, stop reading
+// if(local_header[2] != 0x03 || local_header[3] != 0x04) break;
+//
+// //read in the variable name
+// uint16_t name_len = *(uint16_t*) &local_header[26];
+// std::string varname(name_len,' ');
+// size_t vname_res = fread(&varname[0],sizeof(char),name_len,fp);
+// if(vname_res != name_len)
+// throw std::runtime_error("npz_load: failed fread");
+//
+// //erase the lagging .npy
+// varname.erase(varname.end()-4,varname.end());
+//
+// //read in the extra field
+// uint16_t extra_field_len = *(uint16_t*) &local_header[28];
+// if(extra_field_len > 0) {
+// std::vector<char> buff(extra_field_len);
+// size_t efield_res =
+// fread(&buff[0],sizeof(char),extra_field_len,fp); if(efield_res !=
+// extra_field_len)
+// throw std::runtime_error("npz_load: failed fread");
+// }
+//
+// uint16_t compr_method =
+// *reinterpret_cast<uint16_t*>(&local_header[0]+8); uint32_t
+// compr_bytes = *reinterpret_cast<uint32_t*>(&local_header[0]+18);
+// uint32_t uncompr_bytes =
+// *reinterpret_cast<uint32_t*>(&local_header[0]+22);
+//
+// if(compr_method == 0) {arrays[varname] = load_the_npy_file(fp);}
+// else {arrays[varname] =
+// load_the_npz_array(fp,compr_bytes,uncompr_bytes);}
+// }
+//
+// fclose(fp);
+// return arrays;
+// }
+//
+// cnpy::NpyArray cnpy::npz_load(std::string fname, std::string varname) {
+// FILE* fp = fopen(fname.c_str(),"rb");
+//
+// if(!fp) throw std::runtime_error("npz_load: Unable to open file "+fname);
+//
+// while(1) {
+// std::vector<char> local_header(30);
+// size_t header_res = fread(&local_header[0],sizeof(char),30,fp);
+// if(header_res != 30)
+// throw std::runtime_error("npz_load: failed fread");
+//
+// //if we've reached the global header, stop reading
+// if(local_header[2] != 0x03 || local_header[3] != 0x04) break;
+//
+// //read in the variable name
+// uint16_t name_len = *(uint16_t*) &local_header[26];
+// std::string vname(name_len,' ');
+// size_t vname_res = fread(&vname[0],sizeof(char),name_len,fp);
+// if(vname_res != name_len)
+// throw std::runtime_error("npz_load: failed fread");
+// vname.erase(vname.end()-4,vname.end()); //erase the lagging .npy
+//
+// //read in the extra field
+// uint16_t extra_field_len = *(uint16_t*) &local_header[28];
+// fseek(fp,extra_field_len,SEEK_CUR); //skip past the extra field
+//
+// uint16_t compr_method =
+// *reinterpret_cast<uint16_t*>(&local_header[0]+8); uint32_t
+// compr_bytes = *reinterpret_cast<uint32_t*>(&local_header[0]+18);
+// uint32_t uncompr_bytes =
+// *reinterpret_cast<uint32_t*>(&local_header[0]+22);
+//
+// if(vname == varname) {
+// NpyArray array = (compr_method == 0) ? load_the_npy_file(fp) :
+// load_the_npz_array(fp,compr_bytes,uncompr_bytes); fclose(fp);
+// return array;
+// }
+// else {
+// //skip past the data
+// uint32_t size = *(uint32_t*) &local_header[22];
+// fseek(fp,size,SEEK_CUR);
+// }
+// }
+//
+// fclose(fp);
+//
+// //if we get here, we haven't found the variable in the file
+// throw std::runtime_error("npz_load: Variable name "+varname+" not found
+// in "+fname);
+// }
cnpy::NpyArray cnpy::npy_load(std::string fname) {
- FILE* fp = fopen(fname.c_str(), "rb");
-
- if (!fp) {
- std::stringstream ss;
- ss << "npy_load: Unable to open file " << fname << ":\n"
- << std::strerror(errno) << std::endl;
-
- throw std::runtime_error(ss.str());
- }
+ FILE *fp = fopen(fname.c_str(), "rb");
- NpyArray arr = load_the_npy_file(fp);
-
- fclose(fp);
- return arr;
-}
+ if (!fp) {
+ std::stringstream ss;
+ ss << "npy_load: Unable to open file " << fname << ":\n"
+ << std::strerror(errno) << std::endl;
+ throw std::runtime_error(ss.str());
+ }
+ NpyArray arr = load_the_npy_file(fp);
+ fclose(fp);
+ return arr;
+}
diff --git a/NeuralAmpModeler/dsp/cnpy.h b/NeuralAmpModeler/dsp/cnpy.h
@@ -1,269 +1,295 @@
-//Copyright (C) 2011 Carl Rogers
-//Released under MIT License
-//license available in LICENSE file, or at http://www.opensource.org/licenses/mit-license.php
+// Copyright (C) 2011 Carl Rogers
+// Released under MIT License
+// license available in LICENSE file, or at
+// http://www.opensource.org/licenses/mit-license.php
#ifndef LIBCNPY_H_
#define LIBCNPY_H_
-#include<string>
-#include<stdexcept>
-#include<sstream>
-#include<vector>
-#include<cstdio>
-#include<typeinfo>
-#include<iostream>
-#include<cassert>
-#include<zlib.h>
-#include<map>
-#include<memory>
-#include<stdint.h>
-#include<numeric>
+#include <cassert>
+#include <cstdio>
+#include <iostream>
+#include <map>
+#include <memory>
+#include <numeric>
+#include <sstream>
+#include <stdexcept>
+#include <stdint.h>
+#include <string>
+#include <typeinfo>
+#include <vector>
+#include <zlib.h>
namespace cnpy {
- struct NpyArray {
- NpyArray(const std::vector<size_t>& _shape, size_t _word_size, bool _fortran_order) :
- shape(_shape), word_size(_word_size), fortran_order(_fortran_order)
- {
- num_vals = 1;
- for(size_t i = 0;i < shape.size();i++) num_vals *= shape[i];
- data_holder = std::shared_ptr<std::vector<char>>(
- new std::vector<char>(num_vals * word_size));
- }
-
- NpyArray() : shape(0), word_size(0), fortran_order(0), num_vals(0) { }
-
- template<typename T>
- T* data() {
- return reinterpret_cast<T*>(&(*data_holder)[0]);
- }
-
- template<typename T>
- const T* data() const {
- return reinterpret_cast<T*>(&(*data_holder)[0]);
- }
-
- template<typename T>
- std::vector<T> as_vec() const {
- const T* p = data<T>();
- return std::vector<T>(p, p+num_vals);
- }
-
- size_t num_bytes() const {
- return data_holder->size();
- }
-
- std::shared_ptr<std::vector<char>> data_holder;
- std::vector<size_t> shape;
- size_t word_size;
- bool fortran_order;
- size_t num_vals;
- };
-
- using npz_t = std::map<std::string, NpyArray>;
-
- char BigEndianTest();
- char map_type(const std::type_info& t);
- template<typename T> std::vector<char> create_npy_header(const std::vector<size_t>& shape);
- void parse_npy_header(FILE* fp,size_t& word_size, std::vector<size_t>& shape, bool& fortran_order);
- void parse_npy_header(unsigned char* buffer,size_t& word_size, std::vector<size_t>& shape, bool& fortran_order);
- //void parse_zip_footer(FILE* fp, uint16_t& nrecs, size_t& global_header_size, size_t& global_header_offset);
- //npz_t npz_load(std::string fname);
- //NpyArray npz_load(std::string fname, std::string varname);
- NpyArray npy_load(std::string fname);
-
- template<typename T> std::vector<char>& operator+=(std::vector<char>& lhs, const T rhs) {
- //write in little endian
- for(size_t byte = 0; byte < sizeof(T); byte++) {
- char val = *((char*)&rhs+byte);
- lhs.push_back(val);
- }
- return lhs;
- }
+struct NpyArray {
+ NpyArray(const std::vector<size_t> &_shape, size_t _word_size,
+ bool _fortran_order)
+ : shape(_shape), word_size(_word_size), fortran_order(_fortran_order) {
+ num_vals = 1;
+ for (size_t i = 0; i < shape.size(); i++)
+ num_vals *= shape[i];
+ data_holder = std::shared_ptr<std::vector<char>>(
+ new std::vector<char>(num_vals * word_size));
+ }
+
+ NpyArray() : shape(0), word_size(0), fortran_order(0), num_vals(0) {}
+
+ template <typename T> T *data() {
+ return reinterpret_cast<T *>(&(*data_holder)[0]);
+ }
+
+ template <typename T> const T *data() const {
+ return reinterpret_cast<T *>(&(*data_holder)[0]);
+ }
+
+ template <typename T> std::vector<T> as_vec() const {
+ const T *p = data<T>();
+ return std::vector<T>(p, p + num_vals);
+ }
+
+ size_t num_bytes() const { return data_holder->size(); }
+
+ std::shared_ptr<std::vector<char>> data_holder;
+ std::vector<size_t> shape;
+ size_t word_size;
+ bool fortran_order;
+ size_t num_vals;
+};
+
+using npz_t = std::map<std::string, NpyArray>;
+
+char BigEndianTest();
+char map_type(const std::type_info &t);
+template <typename T>
+std::vector<char> create_npy_header(const std::vector<size_t> &shape);
+void parse_npy_header(FILE *fp, size_t &word_size, std::vector<size_t> &shape,
+ bool &fortran_order);
+void parse_npy_header(unsigned char *buffer, size_t &word_size,
+ std::vector<size_t> &shape, bool &fortran_order);
+// void parse_zip_footer(FILE* fp, uint16_t& nrecs, size_t& global_header_size,
+// size_t& global_header_offset); npz_t npz_load(std::string fname); NpyArray
+// npz_load(std::string fname, std::string varname);
+NpyArray npy_load(std::string fname);
+
+template <typename T>
+std::vector<char> &operator+=(std::vector<char> &lhs, const T rhs) {
+ // write in little endian
+ for (size_t byte = 0; byte < sizeof(T); byte++) {
+ char val = *((char *)&rhs + byte);
+ lhs.push_back(val);
+ }
+ return lhs;
+}
- template<> std::vector<char>& operator+=(std::vector<char>& lhs, const std::string rhs);
- template<> std::vector<char>& operator+=(std::vector<char>& lhs, const char* rhs);
-
-
- template<typename T> void npy_save(std::string fname, const T* data, const std::vector<size_t> shape, std::string mode = "w") {
- FILE* fp = NULL;
- std::vector<size_t> true_data_shape; //if appending, the shape of existing + new data
-
- if(mode == "a") fp = fopen(fname.c_str(),"r+b");
-
- if(fp) {
- //file exists. we need to append to it. read the header, modify the array size
- size_t word_size;
- bool fortran_order;
- parse_npy_header(fp,word_size,true_data_shape,fortran_order);
- assert(!fortran_order);
-
- if(word_size != sizeof(T)) {
- std::cout<<"libnpy error: "<<fname<<" has word size "<<word_size<<" but npy_save appending data sized "<<sizeof(T)<<"\n";
- assert( word_size == sizeof(T) );
- }
- if(true_data_shape.size() != shape.size()) {
- std::cout<<"libnpy error: npy_save attempting to append misdimensioned data to "<<fname<<"\n";
- assert(true_data_shape.size() != shape.size());
- }
-
- for(size_t i = 1; i < shape.size(); i++) {
- if(shape[i] != true_data_shape[i]) {
- std::cout<<"libnpy error: npy_save attempting to append misshaped data to "<<fname<<"\n";
- assert(shape[i] == true_data_shape[i]);
- }
- }
- true_data_shape[0] += shape[0];
- }
- else {
- fp = fopen(fname.c_str(),"wb");
- true_data_shape = shape;
- }
-
- std::vector<char> header = create_npy_header<T>(true_data_shape);
- size_t nels = std::accumulate(shape.begin(),shape.end(),1,std::multiplies<size_t>());
-
- fseek(fp,0,SEEK_SET);
- fwrite(&header[0],sizeof(char),header.size(),fp);
- fseek(fp,0,SEEK_END);
- fwrite(data,sizeof(T),nels,fp);
- fclose(fp);
+template <>
+std::vector<char> &operator+=(std::vector<char> &lhs, const std::string rhs);
+template <>
+std::vector<char> &operator+=(std::vector<char> &lhs, const char *rhs);
+
+template <typename T>
+void npy_save(std::string fname, const T *data, const std::vector<size_t> shape,
+ std::string mode = "w") {
+ FILE *fp = NULL;
+ std::vector<size_t>
+ true_data_shape; // if appending, the shape of existing + new data
+
+ if (mode == "a")
+ fp = fopen(fname.c_str(), "r+b");
+
+ if (fp) {
+ // file exists. we need to append to it. read the header, modify the array
+ // size
+ size_t word_size;
+ bool fortran_order;
+ parse_npy_header(fp, word_size, true_data_shape, fortran_order);
+ assert(!fortran_order);
+
+ if (word_size != sizeof(T)) {
+ std::cout << "libnpy error: " << fname << " has word size " << word_size
+ << " but npy_save appending data sized " << sizeof(T) << "\n";
+ assert(word_size == sizeof(T));
}
-
- //template<typename T> void npz_save(std::string zipname, std::string fname, const T* data, const std::vector<size_t>& shape, std::string mode = "w")
- //{
- // //first, append a .npy to the fname
- // fname += ".npy";
-
- // //now, on with the show
- // FILE* fp = NULL;
- // uint16_t nrecs = 0;
- // size_t global_header_offset = 0;
- // std::vector<char> global_header;
-
- // if(mode == "a") fp = fopen(zipname.c_str(),"r+b");
-
- // if(fp) {
- // //zip file exists. we need to add a new npy file to it.
- // //first read the footer. this gives us the offset and size of the global header
- // //then read and store the global header.
- // //below, we will write the the new data at the start of the global header then append the global header and footer below it
- // size_t global_header_size;
- // parse_zip_footer(fp,nrecs,global_header_size,global_header_offset);
- // fseek(fp,global_header_offset,SEEK_SET);
- // global_header.resize(global_header_size);
- // size_t res = fread(&global_header[0],sizeof(char),global_header_size,fp);
- // if(res != global_header_size){
- // throw std::runtime_error("npz_save: header read error while adding to existing zip");
- // }
- // fseek(fp,global_header_offset,SEEK_SET);
- // }
- // else {
- // fp = fopen(zipname.c_str(),"wb");
- // }
-
- // std::vector<char> npy_header = create_npy_header<T>(shape);
-
- // size_t nels = std::accumulate(shape.begin(),shape.end(),1,std::multiplies<size_t>());
- // size_t nbytes = nels*sizeof(T) + npy_header.size();
-
- // //get the CRC of the data to be added
- // uint32_t crc = crc32(0L,(uint8_t*)&npy_header[0],npy_header.size());
- // crc = crc32(crc,(uint8_t*)data,nels*sizeof(T));
-
- // //build the local header
- // std::vector<char> local_header;
- // local_header += "PK"; //first part of sig
- // local_header += (uint16_t) 0x0403; //second part of sig
- // local_header += (uint16_t) 20; //min version to extract
- // local_header += (uint16_t) 0; //general purpose bit flag
- // local_header += (uint16_t) 0; //compression method
- // local_header += (uint16_t) 0; //file last mod time
- // local_header += (uint16_t) 0; //file last mod date
- // local_header += (uint32_t) crc; //crc
- // local_header += (uint32_t) nbytes; //compressed size
- // local_header += (uint32_t) nbytes; //uncompressed size
- // local_header += (uint16_t) fname.size(); //fname length
- // local_header += (uint16_t) 0; //extra field length
- // local_header += fname;
-
- // //build global header
- // global_header += "PK"; //first part of sig
- // global_header += (uint16_t) 0x0201; //second part of sig
- // global_header += (uint16_t) 20; //version made by
- // global_header.insert(global_header.end(),local_header.begin()+4,local_header.begin()+30);
- // global_header += (uint16_t) 0; //file comment length
- // global_header += (uint16_t) 0; //disk number where file starts
- // global_header += (uint16_t) 0; //internal file attributes
- // global_header += (uint32_t) 0; //external file attributes
- // global_header += (uint32_t) global_header_offset; //relative offset of local file header, since it begins where the global header used to begin
- // global_header += fname;
-
- // //build footer
- // std::vector<char> footer;
- // footer += "PK"; //first part of sig
- // footer += (uint16_t) 0x0605; //second part of sig
- // footer += (uint16_t) 0; //number of this disk
- // footer += (uint16_t) 0; //disk where footer starts
- // footer += (uint16_t) (nrecs+1); //number of records on this disk
- // footer += (uint16_t) (nrecs+1); //total number of records
- // footer += (uint32_t) global_header.size(); //nbytes of global headers
- // footer += (uint32_t) (global_header_offset + nbytes + local_header.size()); //offset of start of global headers, since global header now starts after newly written array
- // footer += (uint16_t) 0; //zip file comment length
-
- // //write everything
- // fwrite(&local_header[0],sizeof(char),local_header.size(),fp);
- // fwrite(&npy_header[0],sizeof(char),npy_header.size(),fp);
- // fwrite(data,sizeof(T),nels,fp);
- // fwrite(&global_header[0],sizeof(char),global_header.size(),fp);
- // fwrite(&footer[0],sizeof(char),footer.size(),fp);
- // fclose(fp);
- //}
-
- template<typename T> void npy_save(std::string fname, const std::vector<T> data, std::string mode = "w") {
- std::vector<size_t> shape;
- shape.push_back(data.size());
- npy_save(fname, &data[0], shape, mode);
+ if (true_data_shape.size() != shape.size()) {
+ std::cout << "libnpy error: npy_save attempting to append misdimensioned "
+ "data to "
+ << fname << "\n";
+ assert(true_data_shape.size() != shape.size());
}
- //template<typename T> void npz_save(std::string zipname, std::string fname, const std::vector<T> data, std::string mode = "w") {
- // std::vector<size_t> shape;
- // shape.push_back(data.size());
- // npz_save(zipname, fname, &data[0], shape, mode);
- //}
-
- template<typename T> std::vector<char> create_npy_header(const std::vector<size_t>& shape) {
-
- std::vector<char> dict;
- dict += "{'descr': '";
- dict += BigEndianTest();
- dict += map_type(typeid(T));
- dict += std::to_string(sizeof(T));
- dict += "', 'fortran_order': False, 'shape': (";
- dict += std::to_string(shape[0]);
- for(size_t i = 1;i < shape.size();i++) {
- dict += ", ";
- dict += std::to_string(shape[i]);
- }
- if(shape.size() == 1) dict += ",";
- dict += "), }";
- //pad with spaces so that preamble+dict is modulo 16 bytes. preamble is 10 bytes. dict needs to end with \n
- int remainder = 16 - (10 + dict.size()) % 16;
- dict.insert(dict.end(),remainder,' ');
- dict.back() = '\n';
-
- std::vector<char> header;
- header += (char) 0x93;
- header += "NUMPY";
- header += (char) 0x01; //major version of numpy format
- header += (char) 0x00; //minor version of numpy format
- header += (uint16_t) dict.size();
- header.insert(header.end(),dict.begin(),dict.end());
-
- return header;
+ for (size_t i = 1; i < shape.size(); i++) {
+ if (shape[i] != true_data_shape[i]) {
+ std::cout
+ << "libnpy error: npy_save attempting to append misshaped data to "
+ << fname << "\n";
+ assert(shape[i] == true_data_shape[i]);
+ }
}
+ true_data_shape[0] += shape[0];
+ } else {
+ fp = fopen(fname.c_str(), "wb");
+ true_data_shape = shape;
+ }
+
+ std::vector<char> header = create_npy_header<T>(true_data_shape);
+ size_t nels =
+ std::accumulate(shape.begin(), shape.end(), 1, std::multiplies<size_t>());
+
+ fseek(fp, 0, SEEK_SET);
+ fwrite(&header[0], sizeof(char), header.size(), fp);
+ fseek(fp, 0, SEEK_END);
+ fwrite(data, sizeof(T), nels, fp);
+ fclose(fp);
+}
+// template<typename T> void npz_save(std::string zipname, std::string fname,
+// const T* data, const std::vector<size_t>& shape, std::string mode = "w")
+//{
+// //first, append a .npy to the fname
+// fname += ".npy";
+
+// //now, on with the show
+// FILE* fp = NULL;
+// uint16_t nrecs = 0;
+// size_t global_header_offset = 0;
+// std::vector<char> global_header;
+
+// if(mode == "a") fp = fopen(zipname.c_str(),"r+b");
+
+// if(fp) {
+// //zip file exists. we need to add a new npy file to it.
+// //first read the footer. this gives us the offset and size of the
+// global header
+// //then read and store the global header.
+// //below, we will write the the new data at the start of the global
+// header then append the global header and footer below it size_t
+// global_header_size;
+// parse_zip_footer(fp,nrecs,global_header_size,global_header_offset);
+// fseek(fp,global_header_offset,SEEK_SET);
+// global_header.resize(global_header_size);
+// size_t res =
+// fread(&global_header[0],sizeof(char),global_header_size,fp); if(res !=
+// global_header_size){
+// throw std::runtime_error("npz_save: header read error while adding
+// to existing zip");
+// }
+// fseek(fp,global_header_offset,SEEK_SET);
+// }
+// else {
+// fp = fopen(zipname.c_str(),"wb");
+// }
+
+// std::vector<char> npy_header = create_npy_header<T>(shape);
+
+// size_t nels =
+// std::accumulate(shape.begin(),shape.end(),1,std::multiplies<size_t>());
+// size_t nbytes = nels*sizeof(T) + npy_header.size();
+
+// //get the CRC of the data to be added
+// uint32_t crc = crc32(0L,(uint8_t*)&npy_header[0],npy_header.size());
+// crc = crc32(crc,(uint8_t*)data,nels*sizeof(T));
+
+// //build the local header
+// std::vector<char> local_header;
+// local_header += "PK"; //first part of sig
+// local_header += (uint16_t) 0x0403; //second part of sig
+// local_header += (uint16_t) 20; //min version to extract
+// local_header += (uint16_t) 0; //general purpose bit flag
+// local_header += (uint16_t) 0; //compression method
+// local_header += (uint16_t) 0; //file last mod time
+// local_header += (uint16_t) 0; //file last mod date
+// local_header += (uint32_t) crc; //crc
+// local_header += (uint32_t) nbytes; //compressed size
+// local_header += (uint32_t) nbytes; //uncompressed size
+// local_header += (uint16_t) fname.size(); //fname length
+// local_header += (uint16_t) 0; //extra field length
+// local_header += fname;
+
+// //build global header
+// global_header += "PK"; //first part of sig
+// global_header += (uint16_t) 0x0201; //second part of sig
+// global_header += (uint16_t) 20; //version made by
+// global_header.insert(global_header.end(),local_header.begin()+4,local_header.begin()+30);
+// global_header += (uint16_t) 0; //file comment length
+// global_header += (uint16_t) 0; //disk number where file starts
+// global_header += (uint16_t) 0; //internal file attributes
+// global_header += (uint32_t) 0; //external file attributes
+// global_header += (uint32_t) global_header_offset; //relative offset of
+// local file header, since it begins where the global header used to begin
+// global_header += fname;
+
+// //build footer
+// std::vector<char> footer;
+// footer += "PK"; //first part of sig
+// footer += (uint16_t) 0x0605; //second part of sig
+// footer += (uint16_t) 0; //number of this disk
+// footer += (uint16_t) 0; //disk where footer starts
+// footer += (uint16_t) (nrecs+1); //number of records on this disk
+// footer += (uint16_t) (nrecs+1); //total number of records
+// footer += (uint32_t) global_header.size(); //nbytes of global headers
+// footer += (uint32_t) (global_header_offset + nbytes +
+// local_header.size()); //offset of start of global headers, since global
+// header now starts after newly written array footer += (uint16_t) 0; //zip
+// file comment length
+
+// //write everything
+// fwrite(&local_header[0],sizeof(char),local_header.size(),fp);
+// fwrite(&npy_header[0],sizeof(char),npy_header.size(),fp);
+// fwrite(data,sizeof(T),nels,fp);
+// fwrite(&global_header[0],sizeof(char),global_header.size(),fp);
+// fwrite(&footer[0],sizeof(char),footer.size(),fp);
+// fclose(fp);
+//}
+
+template <typename T>
+void npy_save(std::string fname, const std::vector<T> data,
+ std::string mode = "w") {
+ std::vector<size_t> shape;
+ shape.push_back(data.size());
+ npy_save(fname, &data[0], shape, mode);
+}
+// template<typename T> void npz_save(std::string zipname, std::string fname,
+// const std::vector<T> data, std::string mode = "w") {
+// std::vector<size_t> shape;
+// shape.push_back(data.size());
+// npz_save(zipname, fname, &data[0], shape, mode);
+// }
+
+template <typename T>
+std::vector<char> create_npy_header(const std::vector<size_t> &shape) {
+
+ std::vector<char> dict;
+ dict += "{'descr': '";
+ dict += BigEndianTest();
+ dict += map_type(typeid(T));
+ dict += std::to_string(sizeof(T));
+ dict += "', 'fortran_order': False, 'shape': (";
+ dict += std::to_string(shape[0]);
+ for (size_t i = 1; i < shape.size(); i++) {
+ dict += ", ";
+ dict += std::to_string(shape[i]);
+ }
+ if (shape.size() == 1)
+ dict += ",";
+ dict += "), }";
+ // pad with spaces so that preamble+dict is modulo 16 bytes. preamble is 10
+ // bytes. dict needs to end with \n
+ int remainder = 16 - (10 + dict.size()) % 16;
+ dict.insert(dict.end(), remainder, ' ');
+ dict.back() = '\n';
+
+ std::vector<char> header;
+ header += (char)0x93;
+ header += "NUMPY";
+ header += (char)0x01; // major version of numpy format
+ header += (char)0x00; // minor version of numpy format
+ header += (uint16_t)dict.size();
+ header.insert(header.end(), dict.begin(), dict.end());
+
+ return header;
}
+} // namespace cnpy
+
#endif
diff --git a/NeuralAmpModeler/dsp/dsp.cpp b/NeuralAmpModeler/dsp/dsp.cpp
@@ -1,32 +1,25 @@
-#include <algorithm> // std::max_element
-#include <cmath> // pow, tanh, expf
-#include <filesystem>
+#include <algorithm> // std::max_element
#include <algorithm>
+#include <cmath> // pow, tanh, expf
+#include <filesystem>
#include <fstream>
#include <string>
#include <unordered_map>
#include <unordered_set>
+#include "dsp.h"
#include "json.hpp"
#include "numpy_util.h"
-#include "dsp.h"
#include "util.h"
constexpr auto _INPUT_BUFFER_SAFETY_FACTOR = 32;
-DSP::DSP()
-{ this->_stale_params = true; }
-
-void DSP::process(
- iplug::sample** inputs,
- iplug::sample** outputs,
- const int num_channels,
- const int num_frames,
- const double input_gain,
- const double output_gain,
- const std::unordered_map<std::string,double>& params
-)
-{
+DSP::DSP() { this->_stale_params = true; }
+
+void DSP::process(iplug::sample **inputs, iplug::sample **outputs,
+ const int num_channels, const int num_frames,
+ const double input_gain, const double output_gain,
+ const std::unordered_map<std::string, double> ¶ms) {
this->_get_params_(params);
this->_apply_input_level_(inputs, num_channels, num_frames, input_gain);
this->_ensure_core_dsp_output_ready_();
@@ -34,30 +27,26 @@ void DSP::process(
this->_apply_output_level_(outputs, num_channels, num_frames, output_gain);
}
-void DSP::finalize_(const int num_frames)
-{}
+void DSP::finalize_(const int num_frames) {}
-void DSP::_get_params_(const std::unordered_map<std::string, double>& input_params)
-{
+void DSP::_get_params_(
+ const std::unordered_map<std::string, double> &input_params) {
this->_stale_params = false;
- for (auto it = input_params.begin(); it != input_params.end(); ++it)
- {
+ for (auto it = input_params.begin(); it != input_params.end(); ++it) {
const std::string key = util::lowercase(it->first);
const double value = it->second;
- if (this->_params.find(key) == this->_params.end()) // Not contained
+ if (this->_params.find(key) == this->_params.end()) // Not contained
this->_stale_params = true;
- else if (this->_params[key] != value) // Contained but new value
+ else if (this->_params[key] != value) // Contained but new value
this->_stale_params = true;
this->_params[key] = value;
}
}
-void DSP::_apply_input_level_(iplug::sample** inputs,
- const int num_channels,
- const int num_frames,
- const double gain)
-{
- // Must match exactly; we're going to use the size of _input_post_gain later for num_frames.
+void DSP::_apply_input_level_(iplug::sample **inputs, const int num_channels,
+ const int num_frames, const double gain) {
+ // Must match exactly; we're going to use the size of _input_post_gain later
+ // for num_frames.
if (this->_input_post_gain.size() != num_frames)
this->_input_post_gain.resize(num_frames);
// MONO ONLY
@@ -66,21 +55,19 @@ void DSP::_apply_input_level_(iplug::sample** inputs,
this->_input_post_gain[i] = float(gain * inputs[channel][i]);
}
-void DSP::_ensure_core_dsp_output_ready_()
-{
+void DSP::_ensure_core_dsp_output_ready_() {
if (this->_core_dsp_output.size() < this->_input_post_gain.size())
this->_core_dsp_output.resize(this->_input_post_gain.size());
}
-void DSP::_process_core_()
-{
+void DSP::_process_core_() {
// Default implementation is the null operation
for (int i = 0; i < this->_input_post_gain.size(); i++)
this->_core_dsp_output[i] = this->_input_post_gain[i];
}
-void DSP::_apply_output_level_(iplug::sample** outputs, const int num_channels, const int num_frames, const double gain)
-{
+void DSP::_apply_output_level_(iplug::sample **outputs, const int num_channels,
+ const int num_frames, const double gain) {
for (int c = 0; c < num_channels; c++)
for (int s = 0; s < num_frames; s++)
outputs[c][s] = double(gain * this->_core_dsp_output[s]);
@@ -88,43 +75,39 @@ void DSP::_apply_output_level_(iplug::sample** outputs, const int num_channels,
// Buffer =====================================================================
-Buffer::Buffer(const int receptive_field) : DSP()
-{
+Buffer::Buffer(const int receptive_field) : DSP() {
this->_set_receptive_field(receptive_field);
}
-void Buffer::_set_receptive_field(const int new_receptive_field)
-{
- this->_set_receptive_field(new_receptive_field, _INPUT_BUFFER_SAFETY_FACTOR * new_receptive_field);
+void Buffer::_set_receptive_field(const int new_receptive_field) {
+ this->_set_receptive_field(new_receptive_field,
+ _INPUT_BUFFER_SAFETY_FACTOR * new_receptive_field);
};
-void Buffer::_set_receptive_field(const int new_receptive_field, const int input_buffer_size)
-{
+void Buffer::_set_receptive_field(const int new_receptive_field,
+ const int input_buffer_size) {
this->_receptive_field = new_receptive_field;
this->_input_buffer.resize(input_buffer_size);
this->_reset_input_buffer();
}
-void Buffer::_update_buffers_()
-{
+void Buffer::_update_buffers_() {
const long int num_frames = this->_input_post_gain.size();
- //Make sure that the buffer is big enough for the receptive field and the
- //frames needed!
+ // Make sure that the buffer is big enough for the receptive field and the
+ // frames needed!
{
const long minimum_input_buffer_size =
- (long)this->_receptive_field
- + _INPUT_BUFFER_SAFETY_FACTOR * num_frames;
+ (long)this->_receptive_field + _INPUT_BUFFER_SAFETY_FACTOR * num_frames;
if (this->_input_buffer.size() < minimum_input_buffer_size) {
long new_buffer_size = 2;
while (new_buffer_size < minimum_input_buffer_size)
new_buffer_size *= 2;
this->_input_buffer.resize(new_buffer_size);
}
-
}
- // If we'd run off the end of the input buffer, then we need to move the data back to the start of the
- // buffer and start again.
+ // If we'd run off the end of the input buffer, then we need to move the data
+ // back to the start of the buffer and start again.
if (this->_input_buffer_offset + num_frames > this->_input_buffer.size())
this->_rewind_buffers_();
// Put the new samples into the input buffer
@@ -134,129 +117,94 @@ void Buffer::_update_buffers_()
this->_output_buffer.resize(num_frames);
}
-void Buffer::_rewind_buffers_()
-{
+void Buffer::_rewind_buffers_() {
// Copy the input buffer back
// RF-1 samples because we've got at least one new one inbound.
- for (long i = 0, j = this->_input_buffer_offset - this->_receptive_field; i < this->_receptive_field; i++, j++)
+ for (long i = 0, j = this->_input_buffer_offset - this->_receptive_field;
+ i < this->_receptive_field; i++, j++)
this->_input_buffer[i] = this->_input_buffer[j];
// And reset the offset.
// Even though we could be stingy about that one sample that we won't be using
- // (because a new set is incoming) it's probably not worth the hyper-optimization
- // and liable for bugs.
- // And the code looks way tidier this way.
+ // (because a new set is incoming) it's probably not worth the
+ // hyper-optimization and liable for bugs. And the code looks way tidier this
+ // way.
this->_input_buffer_offset = this->_receptive_field;
}
-void Buffer::_reset_input_buffer()
-{
+void Buffer::_reset_input_buffer() {
this->_input_buffer_offset = this->_receptive_field;
}
-void Buffer::finalize_(const int num_frames)
-{
+void Buffer::finalize_(const int num_frames) {
this->DSP::finalize_(num_frames);
this->_input_buffer_offset += num_frames;
}
// Linear =====================================================================
-Linear::Linear(
- const int receptive_field,
- const bool _bias,
- const std::vector<float> ¶ms
-) : Buffer(receptive_field)
-{
+Linear::Linear(const int receptive_field, const bool _bias,
+ const std::vector<float> ¶ms)
+ : Buffer(receptive_field) {
if (params.size() != (receptive_field + (_bias ? 1 : 0)))
- throw std::runtime_error("Params vector does not match expected size based on architecture parameters");
+ throw std::runtime_error("Params vector does not match expected size based "
+ "on architecture parameters");
this->_weight.resize(this->_receptive_field);
// Pass in in reverse order so that dot products work out of the box.
for (int i = 0; i < this->_receptive_field; i++)
this->_weight(i) = params[receptive_field - 1 - i];
- this->_bias = _bias ? params[receptive_field] : (float) 0.0;
+ this->_bias = _bias ? params[receptive_field] : (float)0.0;
}
-void Linear::_process_core_()
-{
+void Linear::_process_core_() {
this->Buffer::_update_buffers_();
// Main computation!
- for (long i = 0; i < this->_input_post_gain.size(); i++)
- {
- const long offset = this->_input_buffer_offset - this->_weight.size() + i + 1;
- auto input = Eigen::Map<const Eigen::VectorXf>(&this->_input_buffer[offset], this->_receptive_field);
+ for (long i = 0; i < this->_input_post_gain.size(); i++) {
+ const long offset =
+ this->_input_buffer_offset - this->_weight.size() + i + 1;
+ auto input = Eigen::Map<const Eigen::VectorXf>(&this->_input_buffer[offset],
+ this->_receptive_field);
this->_core_dsp_output[i] = this->_bias + this->_weight.dot(input);
}
}
// NN modules =================================================================
-void relu_(
- Eigen::MatrixXf& x,
- const long i_start,
- const long i_end,
- const long j_start,
- const long j_end
-)
-{
+void relu_(Eigen::MatrixXf &x, const long i_start, const long i_end,
+ const long j_start, const long j_end) {
for (long j = j_start; j < j_end; j++)
for (long i = 0; i < x.rows(); i++)
x(i, j) = x(i, j) < (float)0.0 ? (float)0.0 : x(i, j);
}
-void relu_(
- Eigen::MatrixXf& x,
- const long j_start,
- const long j_end
-)
-{
+void relu_(Eigen::MatrixXf &x, const long j_start, const long j_end) {
relu_(x, 0, x.rows(), j_start, j_end);
}
-void relu_(Eigen::MatrixXf& x) { relu_(x, 0, x.rows(), 0, x.cols()); }
+void relu_(Eigen::MatrixXf &x) { relu_(x, 0, x.rows(), 0, x.cols()); }
-void sigmoid_(
- Eigen::MatrixXf& x,
- const long i_start,
- const long i_end,
- const long j_start,
- const long j_end
-)
-{
+void sigmoid_(Eigen::MatrixXf &x, const long i_start, const long i_end,
+ const long j_start, const long j_end) {
for (long j = j_start; j < j_end; j++)
for (long i = i_start; i < i_end; i++)
x(i, j) = 1.0 / (1.0 + expf(-x(i, j)));
}
-void tanh_(
- Eigen::MatrixXf& x,
- const long i_start,
- const long i_end,
- const long j_start,
- const long j_end
-)
-{
+void tanh_(Eigen::MatrixXf &x, const long i_start, const long i_end,
+ const long j_start, const long j_end) {
for (long j = j_start; j < j_end; j++)
for (long i = i_start; i < i_end; i++)
x(i, j) = tanh(x(i, j));
}
-void tanh_(
- Eigen::MatrixXf& x,
- const long j_start,
- const long j_end
-)
-{
+void tanh_(Eigen::MatrixXf &x, const long j_start, const long j_end) {
tanh_(x, 0, x.rows(), j_start, j_end);
}
-void tanh_(Eigen::MatrixXf& x) { tanh_(x, 0, x.rows(), 0, x.cols()); }
+void tanh_(Eigen::MatrixXf &x) { tanh_(x, 0, x.rows(), 0, x.cols()); }
-
-
-void Conv1D::set_params_(std::vector<float>::iterator& params)
-{
+void Conv1D::set_params_(std::vector<float>::iterator ¶ms) {
if (this->_weight.size() > 0) {
const int out_channels = this->_weight[0].rows();
const int in_channels = this->_weight[0].cols();
@@ -270,17 +218,13 @@ void Conv1D::set_params_(std::vector<float>::iterator& params)
this->_bias(i) = *(params++);
}
-void Conv1D::set_size_(
- const int in_channels,
- const int out_channels,
- const int kernel_size,
- const bool do_bias,
- const int _dilation
-)
-{
+void Conv1D::set_size_(const int in_channels, const int out_channels,
+ const int kernel_size, const bool do_bias,
+ const int _dilation) {
this->_weight.resize(kernel_size);
for (int i = 0; i < this->_weight.size(); i++)
- this->_weight[i].resize(out_channels, in_channels); // y = Ax, input array (C,L)
+ this->_weight[i].resize(out_channels,
+ in_channels); // y = Ax, input array (C,L)
if (do_bias)
this->_bias.resize(out_channels);
else
@@ -288,61 +232,47 @@ void Conv1D::set_size_(
this->_dilation = _dilation;
}
-void Conv1D::set_size_and_params_(
- const int in_channels,
- const int out_channels,
- const int kernel_size,
- const int _dilation,
- const bool do_bias,
- std::vector<float>::iterator& params
-)
-{
+void Conv1D::set_size_and_params_(const int in_channels, const int out_channels,
+ const int kernel_size, const int _dilation,
+ const bool do_bias,
+ std::vector<float>::iterator ¶ms) {
this->set_size_(in_channels, out_channels, kernel_size, do_bias, _dilation);
this->set_params_(params);
}
-void Conv1D::process_(
- const Eigen::MatrixXf &input,
- Eigen::MatrixXf &output,
- const long i_start,
- const long ncols,
- const long j_start
-) const
-{
+void Conv1D::process_(const Eigen::MatrixXf &input, Eigen::MatrixXf &output,
+ const long i_start, const long ncols,
+ const long j_start) const {
// This is the clever part ;)
for (long k = 0; k < this->_weight.size(); k++) {
const long offset = this->_dilation * (k + 1 - this->_weight.size());
if (k == 0)
- output.middleCols(j_start, ncols) = this->_weight[k] * input.middleCols(i_start + offset, ncols);
+ output.middleCols(j_start, ncols) =
+ this->_weight[k] * input.middleCols(i_start + offset, ncols);
else
- output.middleCols(j_start, ncols) += this->_weight[k] * input.middleCols(i_start + offset, ncols);
+ output.middleCols(j_start, ncols) +=
+ this->_weight[k] * input.middleCols(i_start + offset, ncols);
}
if (this->_bias.size() > 0)
output.middleCols(j_start, ncols).colwise() += this->_bias;
}
-long Conv1D::get_num_params() const
-{
+long Conv1D::get_num_params() const {
long num_params = this->_bias.size();
for (long i = 0; i < this->_weight.size(); i++)
num_params += this->_weight[i].size();
return num_params;
}
-Conv1x1::Conv1x1(
- const int in_channels,
- const int out_channels,
- const bool _bias
-)
-{
+Conv1x1::Conv1x1(const int in_channels, const int out_channels,
+ const bool _bias) {
this->_weight.resize(out_channels, in_channels);
this->_do_bias = _bias;
if (_bias)
this->_bias.resize(out_channels);
}
-void Conv1x1::set_params_(std::vector<float>::iterator& params)
-{
+void Conv1x1::set_params_(std::vector<float>::iterator ¶ms) {
for (int i = 0; i < this->_weight.rows(); i++)
for (int j = 0; j < this->_weight.cols(); j++)
this->_weight(i, j) = *(params++);
@@ -351,8 +281,7 @@ void Conv1x1::set_params_(std::vector<float>::iterator& params)
this->_bias(i) = *(params++);
}
-Eigen::MatrixXf Conv1x1::process(const Eigen::MatrixXf& input) const
-{
+Eigen::MatrixXf Conv1x1::process(const Eigen::MatrixXf &input) const {
if (this->_do_bias)
return (this->_weight * input).colwise() + this->_bias;
else
@@ -361,8 +290,8 @@ Eigen::MatrixXf Conv1x1::process(const Eigen::MatrixXf& input) const
// ConvNet ====================================================================
-convnet::BatchNorm::BatchNorm(const int dim, std::vector<float>::iterator& params)
-{
+convnet::BatchNorm::BatchNorm(const int dim,
+ std::vector<float>::iterator ¶ms) {
// Extract from param buffer
Eigen::VectorXf running_mean(dim);
Eigen::VectorXf running_var(dim);
@@ -386,8 +315,8 @@ convnet::BatchNorm::BatchNorm(const int dim, std::vector<float>::iterator& param
this->loc = _bias - this->scale.cwiseProduct(running_mean);
}
-void convnet::BatchNorm::process_(Eigen::MatrixXf& x, const long i_start, const long i_end) const
-{
+void convnet::BatchNorm::process_(Eigen::MatrixXf &x, const long i_start,
+ const long i_end) const {
// todo using colwise?
// #speed but conv probably dominates
for (int i = i_start; i < i_end; i++) {
@@ -396,30 +325,25 @@ void convnet::BatchNorm::process_(Eigen::MatrixXf& x, const long i_start, const
}
}
-void convnet::ConvNetBlock::set_params_(
- const int in_channels,
- const int out_channels,
- const int _dilation,
- const bool batchnorm,
- const std::string activation,
- std::vector<float>::iterator ¶ms
-)
-{
+void convnet::ConvNetBlock::set_params_(const int in_channels,
+ const int out_channels,
+ const int _dilation,
+ const bool batchnorm,
+ const std::string activation,
+ std::vector<float>::iterator ¶ms) {
this->_batchnorm = batchnorm;
// HACK 2 kernel
- this->conv.set_size_and_params_(in_channels, out_channels, 2, _dilation, !batchnorm, params);
+ this->conv.set_size_and_params_(in_channels, out_channels, 2, _dilation,
+ !batchnorm, params);
if (this->_batchnorm)
this->batchnorm = BatchNorm(out_channels, params);
this->activation = activation;
}
-void convnet::ConvNetBlock::process_(
- const Eigen::MatrixXf& input,
- Eigen::MatrixXf &output,
- const long i_start,
- const long i_end
-) const
-{
+void convnet::ConvNetBlock::process_(const Eigen::MatrixXf &input,
+ Eigen::MatrixXf &output,
+ const long i_start,
+ const long i_end) const {
const long ncols = i_end - i_start;
this->conv.process_(input, output, i_start, ncols, i_start);
if (this->_batchnorm)
@@ -432,73 +356,61 @@ void convnet::ConvNetBlock::process_(
throw std::runtime_error("Unrecognized activation");
}
-int convnet::ConvNetBlock::get_out_channels() const
-{
+int convnet::ConvNetBlock::get_out_channels() const {
return this->conv.get_out_channels();
}
-convnet::_Head::_Head(const int channels, std::vector<float>::iterator& params)
-{
+convnet::_Head::_Head(const int channels,
+ std::vector<float>::iterator ¶ms) {
this->_weight.resize(channels);
for (int i = 0; i < channels; i++)
this->_weight[i] = *(params++);
this->_bias = *(params++);
}
-void convnet::_Head::process_(
- const Eigen::MatrixXf &input,
- Eigen::VectorXf &output,
- const long i_start,
- const long i_end
-) const
-{
+void convnet::_Head::process_(const Eigen::MatrixXf &input,
+ Eigen::VectorXf &output, const long i_start,
+ const long i_end) const {
const long length = i_end - i_start;
output.resize(length);
- for (long i = 0, j=i_start; i < length; i++, j++)
+ for (long i = 0, j = i_start; i < length; i++, j++)
output(i) = this->_bias + input.col(j).dot(this->_weight);
}
-convnet::ConvNet::ConvNet(
- const int channels,
- const std::vector<int> &dilations,
- const bool batchnorm,
- const std::string activation,
- std::vector<float> ¶ms
-) :
- Buffer(*std::max_element(dilations.begin(), dilations.end()))
-{
+convnet::ConvNet::ConvNet(const int channels, const std::vector<int> &dilations,
+ const bool batchnorm, const std::string activation,
+ std::vector<float> ¶ms)
+ : Buffer(*std::max_element(dilations.begin(), dilations.end())) {
this->_verify_params(channels, dilations, batchnorm, params.size());
this->_blocks.resize(dilations.size());
std::vector<float>::iterator it = params.begin();
int in_channels = 1;
for (int i = 0; i < dilations.size(); i++)
- this->_blocks[i].set_params_(i == 0 ? 1 : channels, channels, dilations[i], batchnorm, activation, it);
+ this->_blocks[i].set_params_(i == 0 ? 1 : channels, channels, dilations[i],
+ batchnorm, activation, it);
this->_block_vals.resize(this->_blocks.size() + 1);
this->_head = _Head(channels, it);
if (it != params.end())
- throw std::runtime_error("Didn't touch all the params when initializing wavenet");
+ throw std::runtime_error(
+ "Didn't touch all the params when initializing wavenet");
this->_reset_anti_pop_();
}
-void convnet::ConvNet::_process_core_()
-{
+void convnet::ConvNet::_process_core_() {
this->_update_buffers_();
// Main computation!
const int i_start = this->_input_buffer_offset;
const long num_frames = this->_input_post_gain.size();
const long i_end = i_start + num_frames;
- //TODO one unnecessary copy :/ #speed
+ // TODO one unnecessary copy :/ #speed
for (int i = i_start; i < i_end; i++)
this->_block_vals[0](0, i) = this->_input_buffer[i];
for (long i = 0; i < this->_blocks.size(); i++)
- this->_blocks[i].process_(this->_block_vals[i], this->_block_vals[i + 1], i_start, i_end);
+ this->_blocks[i].process_(this->_block_vals[i], this->_block_vals[i + 1],
+ i_start, i_end);
// TODO clean up this allocation
- this->_head.process_(
- this->_block_vals[this->_blocks.size()],
- this->_head_output,
- i_start,
- i_end
- );
+ this->_head.process_(this->_block_vals[this->_blocks.size()],
+ this->_head_output, i_start, i_end);
// Copy to required output array (TODO tighten this up)
for (int s = 0; s < num_frames; s++)
this->_core_dsp_output[s] = this->_head_output(s);
@@ -506,64 +418,56 @@ void convnet::ConvNet::_process_core_()
this->_anti_pop_();
}
-void convnet::ConvNet::_verify_params(
- const int channels,
- const std::vector<int> &dilations ,
- const bool batchnorm,
- const int actual_params
-)
-{
+void convnet::ConvNet::_verify_params(const int channels,
+ const std::vector<int> &dilations,
+ const bool batchnorm,
+ const int actual_params) {
// TODO
}
-void convnet::ConvNet::_update_buffers_()
-{
+void convnet::ConvNet::_update_buffers_() {
this->Buffer::_update_buffers_();
const long buffer_size = this->_input_buffer.size();
this->_block_vals[0].resize(1, buffer_size);
for (long i = 1; i < this->_block_vals.size(); i++)
- this->_block_vals[i].resize(this->_blocks[i-1].get_out_channels(), buffer_size);
-}
-
-void convnet::ConvNet::_rewind_buffers_()
-{
- //Need to rewind the block vals first because Buffer::rewind_buffers()
- //resets the offset index
- //The last _block_vals is the output of the last block and doesn't need to be
- //rewound.
- for (long k = 0; k < this->_block_vals.size()-1; k++) {
- //We actually don't need to pull back a lot...just as far as the first input sample would
- //grab from dilation
+ this->_block_vals[i].resize(this->_blocks[i - 1].get_out_channels(),
+ buffer_size);
+}
+
+void convnet::ConvNet::_rewind_buffers_() {
+ // Need to rewind the block vals first because Buffer::rewind_buffers()
+ // resets the offset index
+ // The last _block_vals is the output of the last block and doesn't need to be
+ // rewound.
+ for (long k = 0; k < this->_block_vals.size() - 1; k++) {
+ // We actually don't need to pull back a lot...just as far as the first
+ // input sample would grab from dilation
const long _dilation = this->_blocks[k].conv.get_dilation();
- for (
- long i = this->_receptive_field - _dilation, j = this->_input_buffer_offset - _dilation;
- j < this->_input_buffer_offset;
- i++, j++
- )
- for (long r=0; r<this->_block_vals[k].rows(); r++)
+ for (long i = this->_receptive_field - _dilation,
+ j = this->_input_buffer_offset - _dilation;
+ j < this->_input_buffer_offset; i++, j++)
+ for (long r = 0; r < this->_block_vals[k].rows(); r++)
this->_block_vals[k](r, i) = this->_block_vals[k](r, j);
}
// Now we can do the rest of the rewind
this->Buffer::_rewind_buffers_();
}
-void convnet::ConvNet::_anti_pop_()
-{
+void convnet::ConvNet::_anti_pop_() {
if (this->_anti_pop_countdown >= this->_anti_pop_ramp)
return;
const float slope = 1.0f / float(this->_anti_pop_ramp);
- for (int i = 0; i < this->_core_dsp_output.size(); i++)
- {
+ for (int i = 0; i < this->_core_dsp_output.size(); i++) {
if (this->_anti_pop_countdown >= this->_anti_pop_ramp)
break;
- const float gain = std::max(slope * float(this->_anti_pop_countdown), float(0.0));
+ const float gain =
+ std::max(slope * float(this->_anti_pop_countdown), float(0.0));
this->_core_dsp_output[i] *= gain;
this->_anti_pop_countdown++;
}
}
-void convnet::ConvNet::_reset_anti_pop_()
-{
+void convnet::ConvNet::_reset_anti_pop_() {
// You need the "real" receptive field, not the buffers.
long receptive_field = 1;
for (int i = 0; i < this->_blocks.size(); i++)
@@ -574,28 +478,21 @@ void convnet::ConvNet::_reset_anti_pop_()
// ============================================================================
// Implementation of Version 2 interface
-dsp::DSP::DSP() :
-mOutputPointers(nullptr),
-mOutputPointersSize(0)
-{}
+dsp::DSP::DSP() : mOutputPointers(nullptr), mOutputPointersSize(0) {}
-dsp::DSP::~DSP()
-{
- this->_DeallocateOutputPointers();
-};
+dsp::DSP::~DSP() { this->_DeallocateOutputPointers(); };
-void dsp::DSP::_AllocateOutputPointers(const size_t numChannels)
-{
+void dsp::DSP::_AllocateOutputPointers(const size_t numChannels) {
if (this->mOutputPointers != nullptr)
- throw std::runtime_error("Tried to re-allocate over non-null mOutputPointers");
- this->mOutputPointers = new iplug::sample*[numChannels];
+ throw std::runtime_error(
+ "Tried to re-allocate over non-null mOutputPointers");
+ this->mOutputPointers = new iplug::sample *[numChannels];
if (this->mOutputPointers == nullptr)
throw std::runtime_error("Failed to allocate pointer to output buffer!\n");
this->mOutputPointersSize = numChannels;
}
-void dsp::DSP::_DeallocateOutputPointers()
-{
+void dsp::DSP::_DeallocateOutputPointers() {
if (this->mOutputPointers != nullptr) {
delete[] this->mOutputPointers;
this->mOutputPointers = nullptr;
@@ -605,75 +502,66 @@ void dsp::DSP::_DeallocateOutputPointers()
this->mOutputPointersSize = 0;
}
-iplug::sample** dsp::DSP::_GetPointers()
-{
- for (auto c=0; c<this->_GetNumChannels(); c++)
+iplug::sample **dsp::DSP::_GetPointers() {
+ for (auto c = 0; c < this->_GetNumChannels(); c++)
this->mOutputPointers[c] = this->mOutputs[c].data();
return this->mOutputPointers;
}
-
-void dsp::DSP::_PrepareBuffers(const size_t numChannels, const size_t numFrames)
-{
+void dsp::DSP::_PrepareBuffers(const size_t numChannels,
+ const size_t numFrames) {
if (this->_GetNumChannels() != numChannels) {
this->mOutputs.resize(numChannels);
- for (auto c=0; c<numChannels; c++) {
+ for (auto c = 0; c < numChannels; c++) {
this->mOutputs[c].resize(numFrames);
}
this->_ResizePointers(numChannels);
}
}
-void dsp::DSP::_ResizePointers(const size_t numChannels)
-{
+void dsp::DSP::_ResizePointers(const size_t numChannels) {
if (this->mOutputPointersSize == numChannels)
return;
this->_DeallocateOutputPointers();
this->_AllocateOutputPointers(numChannels);
}
-dsp::History::History() :
-DSP(),
-mHistoryRequired(0),
-mHistoryIndex(0)
-{
-}
+dsp::History::History() : DSP(), mHistoryRequired(0), mHistoryIndex(0) {}
-void dsp::History::_AdvanceHistoryIndex(const size_t bufferSize)
-{
+void dsp::History::_AdvanceHistoryIndex(const size_t bufferSize) {
this->mHistoryIndex += bufferSize;
}
-void dsp::History::_EnsureHistorySize(const size_t bufferSize)
-{
+void dsp::History::_EnsureHistorySize(const size_t bufferSize) {
const size_t repeatSize = std::max(bufferSize, this->mHistoryRequired);
- const size_t requiredHistoryArraySize = 10 * repeatSize; // Just so we don't spend too much time copying back.
+ const size_t requiredHistoryArraySize =
+ 10 * repeatSize; // Just so we don't spend too much time copying back.
if (this->mHistory.size() < requiredHistoryArraySize) {
this->mHistory.resize(requiredHistoryArraySize);
std::fill(this->mHistory.begin(), this->mHistory.end(), 0.0f);
- this->mHistoryIndex = this->mHistoryRequired; // Guaranteed to be less than requiredHistoryArraySize
+ this->mHistoryIndex = this->mHistoryRequired; // Guaranteed to be less than
+ // requiredHistoryArraySize
}
}
-void dsp::History::_RewindHistory()
-{
+void dsp::History::_RewindHistory() {
// TODO memcpy? Should be fine w/ history array being >2x the history length.
- for (size_t i=0, j=this->mHistoryIndex - this->mHistoryRequired; i<this->mHistoryRequired; i++, j++)
+ for (size_t i = 0, j = this->mHistoryIndex - this->mHistoryRequired;
+ i < this->mHistoryRequired; i++, j++)
this->mHistory[i] = this->mHistory[j];
this->mHistoryIndex = this->mHistoryRequired;
}
void dsp::History::_UpdateHistory(iplug::sample **inputs,
const size_t numChannels,
- const size_t numFrames)
-{
+ const size_t numFrames) {
this->_EnsureHistorySize(numFrames);
if (numChannels < 1)
throw std::runtime_error("Zero channels?");
if (this->mHistoryIndex + numFrames >= this->mHistory.size())
this->_RewindHistory();
// Grabs channel 1, drops hannel 2.
- for (size_t i=0, j=this->mHistoryIndex; i<numFrames; i++, j++)
+ for (size_t i = 0, j = this->mHistoryIndex; i < numFrames; i++, j++)
// Convert down to float here.
- this->mHistory[j] = (float) inputs[0][i];
+ this->mHistory[j] = (float)inputs[0][i];
}
diff --git a/NeuralAmpModeler/dsp/dsp.h b/NeuralAmpModeler/dsp/dsp.h
@@ -6,14 +6,13 @@
#include <iterator>
#include <memory>
#include <string>
-#include <vector>
#include <unordered_map>
+#include <vector>
-#include <Eigen/Dense>
#include "IPlugConstants.h"
+#include <Eigen/Dense>
-enum EArchitectures
-{
+enum EArchitectures {
kLinear = 0,
kConvNet,
kLSTM,
@@ -25,16 +24,14 @@ enum EArchitectures
// Class for providing params from the plugin to the DSP module
// For now, we'll work with doubles. Later, we'll add other types.
-class DSPParam
-{
+class DSPParam {
public:
- const char* name;
+ const char *name;
const double val;
};
// And the params shall be provided as a std::vector<DSPParam>.
-class DSP
-{
+class DSP {
public:
DSP();
// process() does all of the processing requried to take `inputs` array and
@@ -46,15 +43,10 @@ public:
// 3. The core DSP algorithm is run (This is what should probably be
// overridden in subclasses).
// 4. The output level is applied and the result stored to `output`.
- virtual void process(
- iplug::sample** inputs,
- iplug::sample** outputs,
- const int num_channels,
- const int num_frames,
- const double input_gain,
- const double output_gain,
- const std::unordered_map<std::string, double>& params
- );
+ virtual void process(iplug::sample **inputs, iplug::sample **outputs,
+ const int num_channels, const int num_frames,
+ const double input_gain, const double output_gain,
+ const std::unordered_map<std::string, double> ¶ms);
// Anything to take care of before next buffer comes in.
// For example:
// * Move the buffer index forward
@@ -78,14 +70,13 @@ protected:
// Copy the parameters to the DSP module.
// If anything has changed, then set this->_stale_params to true.
// (TODO use "listener" approach)
- void _get_params_(const std::unordered_map<std::string, double>& input_params);
+ void
+ _get_params_(const std::unordered_map<std::string, double> &input_params);
// Apply the input gain
// Result populates this->_input_post_gain
- void _apply_input_level_(iplug::sample** inputs,
- const int num_channels,
- const int num_frames,
- const double gain);
+ void _apply_input_level_(iplug::sample **inputs, const int num_channels,
+ const int num_frames, const double gain);
// i.e. ensure the size is correct.
void _ensure_core_dsp_output_ready_();
@@ -96,30 +87,29 @@ protected:
virtual void _process_core_();
// Copy this->_core_dsp_output to output and apply the output volume
- void _apply_output_level_(iplug::sample** outputs,
- const int num_channels,
- const int num_frames,
- const double gain);
+ void _apply_output_level_(iplug::sample **outputs, const int num_channels,
+ const int num_frames, const double gain);
};
-// Class where an input buffer is kept so that long-time effects can be captured.
-// (e.g. conv nets or impulse responses, where we need history that's longer than the
-// sample buffer that's coming in.)
-class Buffer : public DSP
-{
+// Class where an input buffer is kept so that long-time effects can be
+// captured. (e.g. conv nets or impulse responses, where we need history that's
+// longer than the sample buffer that's coming in.)
+class Buffer : public DSP {
public:
Buffer(const int receptive_field);
void finalize_(const int num_frames);
+
protected:
// Input buffer
- const int _input_buffer_channels = 1; // Mono
+ const int _input_buffer_channels = 1; // Mono
int _receptive_field;
// First location where we add new samples from the input
long _input_buffer_offset;
std::vector<float> _input_buffer;
std::vector<float> _output_buffer;
- void _set_receptive_field(const int new_receptive_field, const int input_buffer_size);
+ void _set_receptive_field(const int new_receptive_field,
+ const int input_buffer_size);
void _set_receptive_field(const int new_receptive_field);
void _reset_input_buffer();
// Use this->_input_post_gain
@@ -128,11 +118,12 @@ protected:
};
// Basic linear model (an IR!)
-class Linear : public Buffer
-{
+class Linear : public Buffer {
public:
- Linear(const int receptive_field, const bool _bias, const std::vector<float> ¶ms);
+ Linear(const int receptive_field, const bool _bias,
+ const std::vector<float> ¶ms);
void _process_core_() override;
+
protected:
Eigen::VectorXf _weight;
float _bias;
@@ -143,83 +134,51 @@ protected:
// Activations
// In-place ReLU on (N,M) array
-void relu_(
- Eigen::MatrixXf& x,
- const long i_start,
- const long i_end,
- const long j_start,
- const long j_end
-);
+void relu_(Eigen::MatrixXf &x, const long i_start, const long i_end,
+ const long j_start, const long j_end);
// Subset of the columns
-void relu_(
- Eigen::MatrixXf& x,
- const long j_start,
- const long j_end
-);
-void relu_(Eigen::MatrixXf& x);
+void relu_(Eigen::MatrixXf &x, const long j_start, const long j_end);
+void relu_(Eigen::MatrixXf &x);
// In-place sigmoid
-void sigmoid_(
- Eigen::MatrixXf& x,
- const long i_start,
- const long i_end,
- const long j_start,
- const long j_end
-);
-void sigmoid_(Eigen::MatrixXf& x);
+void sigmoid_(Eigen::MatrixXf &x, const long i_start, const long i_end,
+ const long j_start, const long j_end);
+void sigmoid_(Eigen::MatrixXf &x);
// In-place Tanh on (N,M) array
-void tanh_(
- Eigen::MatrixXf& x,
- const long i_start,
- const long i_end,
- const long j_start,
- const long j_end
-);
+void tanh_(Eigen::MatrixXf &x, const long i_start, const long i_end,
+ const long j_start, const long j_end);
// Subset of the columns
-void tanh_(
- Eigen::MatrixXf& x,
- const long i_start,
- const long i_end
-);
+void tanh_(Eigen::MatrixXf &x, const long i_start, const long i_end);
-void tanh_(Eigen::MatrixXf& x);
+void tanh_(Eigen::MatrixXf &x);
-class Conv1D
-{
+class Conv1D {
public:
Conv1D() { this->_dilation = 1; };
- void set_params_(std::vector<float>::iterator& params);
- void set_size_(
- const int in_channels,
- const int out_channels,
- const int kernel_size,
- const bool do_bias,
- const int _dilation
- );
- void set_size_and_params_(
- const int in_channels,
- const int out_channels,
- const int kernel_size,
- const int _dilation,
- const bool do_bias,
- std::vector<float>::iterator& params
- );
- //Process from input to output
- // Rightmost indices of input go from i_start to i_end,
- // Indices on output for from j_start (to j_start + i_end - i_start)
- void process_(
- const Eigen::MatrixXf& input,
- Eigen::MatrixXf& output,
- const long i_start,
- const long i_end,
- const long j_start
- ) const;
- long get_in_channels() const { return this->_weight.size() > 0 ? this->_weight[0].cols() : 0; };
+ void set_params_(std::vector<float>::iterator ¶ms);
+ void set_size_(const int in_channels, const int out_channels,
+ const int kernel_size, const bool do_bias,
+ const int _dilation);
+ void set_size_and_params_(const int in_channels, const int out_channels,
+ const int kernel_size, const int _dilation,
+ const bool do_bias,
+ std::vector<float>::iterator ¶ms);
+ // Process from input to output
+ // Rightmost indices of input go from i_start to i_end,
+ // Indices on output for from j_start (to j_start + i_end - i_start)
+ void process_(const Eigen::MatrixXf &input, Eigen::MatrixXf &output,
+ const long i_start, const long i_end, const long j_start) const;
+ long get_in_channels() const {
+ return this->_weight.size() > 0 ? this->_weight[0].cols() : 0;
+ };
long get_kernel_size() const { return this->_weight.size(); };
long get_num_params() const;
- long get_out_channels() const {return this->_weight.size() > 0 ? this->_weight[0].rows() : 0;};
+ long get_out_channels() const {
+ return this->_weight.size() > 0 ? this->_weight[0].rows() : 0;
+ };
int get_dilation() const { return this->_dilation; };
+
private:
// Gonna wing this...
// conv[kernel](cout, cin)
@@ -231,17 +190,14 @@ private:
// Really just a linear layer
class Conv1x1 {
public:
- Conv1x1(
- const int in_channels,
- const int out_channels,
- const bool _bias
- );
- void set_params_(std::vector<float>::iterator& params);
+ Conv1x1(const int in_channels, const int out_channels, const bool _bias);
+ void set_params_(std::vector<float>::iterator ¶ms);
// :param input: (N,Cin) or (Cin,)
// :return: (N,Cout) or (Cout,), respectively
- Eigen::MatrixXf process(const Eigen::MatrixXf& input) const;
+ Eigen::MatrixXf process(const Eigen::MatrixXf &input) const;
int get_out_channels() const { return this->_weight.rows(); };
+
private:
Eigen::MatrixXf _weight;
Eigen::VectorXf _bias;
@@ -251,112 +207,87 @@ private:
// ConvNet ====================================================================
namespace convnet {
- // Custom Conv that avoids re-computing on pieces of the input and trusts
- // that the corresponding outputs are where they need to be.
- // Beware: this is clever!
-
-
- // Batch normalization
- // In prod mode, so really just an elementwise affine layer.
- class BatchNorm
- {
- public:
- BatchNorm() {};
- BatchNorm(const int dim, std::vector<float>::iterator& params);
- void process_(
- Eigen::MatrixXf& input,
- const long i_start,
- const long i_end
- ) const;
-
- private:
- // TODO simplify to just ax+b
- // y = (x-m)/sqrt(v+eps) * w + bias
- // y = ax+b
- // a = w / sqrt(v+eps)
- // b = a * m + bias
- Eigen::VectorXf scale;
- Eigen::VectorXf loc;
- };
+// Custom Conv that avoids re-computing on pieces of the input and trusts
+// that the corresponding outputs are where they need to be.
+// Beware: this is clever!
- class ConvNetBlock
- {
- public:
- ConvNetBlock() { this->_batchnorm = false; };
- void set_params_(
- const int in_channels,
- const int out_channels,
- const int _dilation,
- const bool batchnorm,
- const std::string activation,
- std::vector<float>::iterator& params
- );
- void process_(
- const Eigen::MatrixXf& input,
- Eigen::MatrixXf &output,
- const long i_start,
- const long i_end
- ) const;
- int get_out_channels() const;
- Conv1D conv;
- private:
- BatchNorm batchnorm;
- bool _batchnorm;
- std::string activation;
- };
+// Batch normalization
+// In prod mode, so really just an elementwise affine layer.
+class BatchNorm {
+public:
+ BatchNorm(){};
+ BatchNorm(const int dim, std::vector<float>::iterator ¶ms);
+ void process_(Eigen::MatrixXf &input, const long i_start,
+ const long i_end) const;
- class _Head
- {
- public:
- _Head() { this->_bias = (float)0.0; };
- _Head(const int channels, std::vector<float>::iterator& params);
- void process_(
- const Eigen::MatrixXf &input,
- Eigen::VectorXf &output,
- const long i_start,
- const long i_end
- ) const;
- private:
- Eigen::VectorXf _weight;
- float _bias;
- };
+private:
+ // TODO simplify to just ax+b
+ // y = (x-m)/sqrt(v+eps) * w + bias
+ // y = ax+b
+ // a = w / sqrt(v+eps)
+ // b = a * m + bias
+ Eigen::VectorXf scale;
+ Eigen::VectorXf loc;
+};
- class ConvNet : public Buffer
- {
- public:
- ConvNet(
- const int channels,
- const std::vector<int>& dilations,
- const bool batchnorm,
- const std::string activation,
- std::vector<float> ¶ms
- );
- protected:
- std::vector<ConvNetBlock> _blocks;
- std::vector<Eigen::MatrixXf> _block_vals;
- Eigen::VectorXf _head_output;
- _Head _head;
- void _verify_params(
- const int channels,
- const std::vector<int> &dilations,
- const bool batchnorm,
- const int actual_params
- );
- void _update_buffers_() override;
- void _rewind_buffers_() override;
-
- void _process_core_() override;
-
- // The net starts with random parameters inside; we need to wait for a full
- // receptive field to pass through before we can count on the output being
- // ok. This implements a gentle "ramp-up" so that there's no "pop" at the
- // start.
- long _anti_pop_countdown;
- const long _anti_pop_ramp = 100;
- void _anti_pop_();
- void _reset_anti_pop_();
- };
-}; // namespace convnet
+class ConvNetBlock {
+public:
+ ConvNetBlock() { this->_batchnorm = false; };
+ void set_params_(const int in_channels, const int out_channels,
+ const int _dilation, const bool batchnorm,
+ const std::string activation,
+ std::vector<float>::iterator ¶ms);
+ void process_(const Eigen::MatrixXf &input, Eigen::MatrixXf &output,
+ const long i_start, const long i_end) const;
+ int get_out_channels() const;
+ Conv1D conv;
+
+private:
+ BatchNorm batchnorm;
+ bool _batchnorm;
+ std::string activation;
+};
+
+class _Head {
+public:
+ _Head() { this->_bias = (float)0.0; };
+ _Head(const int channels, std::vector<float>::iterator ¶ms);
+ void process_(const Eigen::MatrixXf &input, Eigen::VectorXf &output,
+ const long i_start, const long i_end) const;
+
+private:
+ Eigen::VectorXf _weight;
+ float _bias;
+};
+
+class ConvNet : public Buffer {
+public:
+ ConvNet(const int channels, const std::vector<int> &dilations,
+ const bool batchnorm, const std::string activation,
+ std::vector<float> ¶ms);
+
+protected:
+ std::vector<ConvNetBlock> _blocks;
+ std::vector<Eigen::MatrixXf> _block_vals;
+ Eigen::VectorXf _head_output;
+ _Head _head;
+ void _verify_params(const int channels, const std::vector<int> &dilations,
+ const bool batchnorm, const int actual_params);
+ void _update_buffers_() override;
+ void _rewind_buffers_() override;
+
+ void _process_core_() override;
+
+ // The net starts with random parameters inside; we need to wait for a full
+ // receptive field to pass through before we can count on the output being
+ // ok. This implements a gentle "ramp-up" so that there's no "pop" at the
+ // start.
+ long _anti_pop_countdown;
+ const long _anti_pop_ramp = 100;
+ void _anti_pop_();
+ void _reset_anti_pop_();
+};
+}; // namespace convnet
// Utilities ==================================================================
// Implemented in get_dsp.cpp
@@ -376,92 +307,94 @@ std::unique_ptr<DSP> get_hard_dsp();
// Version 2 DSP abstraction ==================================================
namespace dsp {
- class Params {};
-
- class DSP {
- public:
- DSP();
- ~DSP();
- // The main interface for processing audio.
- // The incoming audio is given as a raw pointer-to-pointers.
- // The indexing is [channel][frame].
- // The output shall be a pointer-to-pointers of matching size.
- // This object instance will own the data referenced by the pointers and be
- // responsible for its allocation and deallocation.
- virtual iplug::sample** Process(iplug::sample** inputs, const size_t numChannels, const size_t numFrames) = 0;
- // Update the parameters of the DSP object according to the provided params.
- // Not declaring a pure virtual bc there's no concrete definition that can
- // use Params.
- // But, use this name :)
- // virtual void SetParams(Params* params) = 0;
-
- protected:
- // Methods
-
- // Allocate mOutputPointers.
- // Assumes it's already null (Use _DeallocateOutputPointers()).
- void _AllocateOutputPointers(const size_t numChannels);
- // Ensure mOutputPointers is freed.
- void _DeallocateOutputPointers();
-
- size_t _GetNumChannels() const {return this->mOutputs.size();};
- // Return a pointer-to-pointers for the DSP's output buffers (all channels)
- // Assumes that ._PrepareBuffers() was called recently enough.
- iplug::sample** _GetPointers();
- // Resize mOutputs to (numChannels, numFrames) and ensure that the raw
- // pointers are also keeping up.
- virtual void _PrepareBuffers(const size_t numChannels, const size_t numFrames);
- // Resize the pointer-to-pointers for the vector-of-vectors.
- void _ResizePointers(const size_t numChannels);
-
-
- // Attributes
-
- // The output array into which the DSP module's calculations will be written.
- // Pointers to this member's data will be returned by .Process(), and std
- // Will ensure proper allocation.
- std::vector<std::vector<iplug::sample>> mOutputs;
- // A pointer to pointers of which copies will be given out as the output of .Process().
- // This object will ensure proper allocation and deallocation of the first level;
- // The second level points to .data() from mOutputs.
- iplug::sample** mOutputPointers;
- size_t mOutputPointersSize;
- };
-
- // A class where a longer buffer of history is needed to correctly calculate
- // the DSP algorithm (e.g. algorithms involving convolution).
- //
- // Hacky stuff:
- // * Mono
- // * Single-precision floats.
- class History : public DSP {
- public:
- History();
- protected:
- // Called at the end of the DSP, advance the hsitory index to the next open
- // spot. Does not ensure that it's at a valid address.
- void _AdvanceHistoryIndex(const size_t bufferSize);
- // Drop the new samples into the history array.
- // Manages history array size
- void _UpdateHistory(iplug::sample** inputs,
- const size_t numChannels,
- const size_t numFrames);
-
- // The history array that's used for DSP calculations.
- std::vector<float> mHistory;
- // How many samples previous are required.
- // Zero means that no history is required--only the current sample.
- size_t mHistoryRequired;
- // Location of the first sample in the current buffer.
- // Shall always be in the range [mHistoryRequired, mHistory.size()).
- size_t mHistoryIndex;
-
- private:
- // Make sure that the history array is long enough.
- void _EnsureHistorySize(const size_t bufferSize);
- // Copy the end of the history back to the fron and reset mHistoryIndex
- void _RewindHistory();
- };
+class Params {};
+
+class DSP {
+public:
+ DSP();
+ ~DSP();
+ // The main interface for processing audio.
+ // The incoming audio is given as a raw pointer-to-pointers.
+ // The indexing is [channel][frame].
+ // The output shall be a pointer-to-pointers of matching size.
+ // This object instance will own the data referenced by the pointers and be
+ // responsible for its allocation and deallocation.
+ virtual iplug::sample **Process(iplug::sample **inputs,
+ const size_t numChannels,
+ const size_t numFrames) = 0;
+ // Update the parameters of the DSP object according to the provided params.
+ // Not declaring a pure virtual bc there's no concrete definition that can
+ // use Params.
+ // But, use this name :)
+ // virtual void SetParams(Params* params) = 0;
+
+protected:
+ // Methods
+
+ // Allocate mOutputPointers.
+ // Assumes it's already null (Use _DeallocateOutputPointers()).
+ void _AllocateOutputPointers(const size_t numChannels);
+ // Ensure mOutputPointers is freed.
+ void _DeallocateOutputPointers();
+
+ size_t _GetNumChannels() const { return this->mOutputs.size(); };
+ // Return a pointer-to-pointers for the DSP's output buffers (all channels)
+ // Assumes that ._PrepareBuffers() was called recently enough.
+ iplug::sample **_GetPointers();
+ // Resize mOutputs to (numChannels, numFrames) and ensure that the raw
+ // pointers are also keeping up.
+ virtual void _PrepareBuffers(const size_t numChannels,
+ const size_t numFrames);
+ // Resize the pointer-to-pointers for the vector-of-vectors.
+ void _ResizePointers(const size_t numChannels);
+
+ // Attributes
+
+ // The output array into which the DSP module's calculations will be written.
+ // Pointers to this member's data will be returned by .Process(), and std
+ // Will ensure proper allocation.
+ std::vector<std::vector<iplug::sample>> mOutputs;
+ // A pointer to pointers of which copies will be given out as the output of
+ // .Process(). This object will ensure proper allocation and deallocation of
+ // the first level; The second level points to .data() from mOutputs.
+ iplug::sample **mOutputPointers;
+ size_t mOutputPointersSize;
+};
+
+// A class where a longer buffer of history is needed to correctly calculate
+// the DSP algorithm (e.g. algorithms involving convolution).
+//
+// Hacky stuff:
+// * Mono
+// * Single-precision floats.
+class History : public DSP {
+public:
+ History();
+
+protected:
+ // Called at the end of the DSP, advance the hsitory index to the next open
+ // spot. Does not ensure that it's at a valid address.
+ void _AdvanceHistoryIndex(const size_t bufferSize);
+ // Drop the new samples into the history array.
+ // Manages history array size
+ void _UpdateHistory(iplug::sample **inputs, const size_t numChannels,
+ const size_t numFrames);
+
+ // The history array that's used for DSP calculations.
+ std::vector<float> mHistory;
+ // How many samples previous are required.
+ // Zero means that no history is required--only the current sample.
+ size_t mHistoryRequired;
+ // Location of the first sample in the current buffer.
+ // Shall always be in the range [mHistoryRequired, mHistory.size()).
+ size_t mHistoryIndex;
+
+private:
+ // Make sure that the history array is long enough.
+ void _EnsureHistorySize(const size_t bufferSize);
+ // Copy the end of the history back to the fron and reset mHistoryIndex
+ void _RewindHistory();
};
+}; // namespace dsp
-#endif // IPLUG_DSP
+#endif // IPLUG_DSP
diff --git a/NeuralAmpModeler/dsp/get_dsp.cpp b/NeuralAmpModeler/dsp/get_dsp.cpp
@@ -1,51 +1,48 @@
#include <fstream>
#include <unordered_set>
+#include "HardCodedModel.h"
#include "dsp.h"
#include "json.hpp"
#include "lstm.h"
-#include "wavenet.h"
#include "numpy_util.h"
-#include "HardCodedModel.h"
-
+#include "wavenet.h"
-void verify_config_version(const std::string version)
-{
- const std::unordered_set<std::string> supported_versions({"0.2.0", "0.2.1", "0.3.0", "0.3.1", "0.4.0", "0.5.0"});
+void verify_config_version(const std::string version) {
+ const std::unordered_set<std::string> supported_versions(
+ {"0.2.0", "0.2.1", "0.3.0", "0.3.1", "0.4.0", "0.5.0"});
if (supported_versions.find(version) == supported_versions.end())
throw std::runtime_error("Unsupported config version");
}
-std::vector<float> _get_weights(
- nlohmann::json const& j,
- const std::filesystem::path config_path)
-{
- if (j.find("weights") != j.end()) { // New-style model
- auto weight_list = j["weights"];
- std::vector<float> weights;
- for (auto it = weight_list.begin(); it != weight_list.end(); ++it)
- weights.push_back(*it);
- return weights;
- }
- else { // Old-style config.json + weights.npy
- std::filesystem::path weights_path = config_path.parent_path() / std::filesystem::path("weights.npy");
- if (!std::filesystem::exists(weights_path)) {
- std::stringstream s;
- s << "No weights in model file, and could not find accompanying weights at expected location " << weights_path;
- throw std::runtime_error(s.str());
- }
- return numpy_util::load_to_vector(weights_path);
+std::vector<float> _get_weights(nlohmann::json const &j,
+ const std::filesystem::path config_path) {
+ if (j.find("weights") != j.end()) { // New-style model
+ auto weight_list = j["weights"];
+ std::vector<float> weights;
+ for (auto it = weight_list.begin(); it != weight_list.end(); ++it)
+ weights.push_back(*it);
+ return weights;
+ } else { // Old-style config.json + weights.npy
+ std::filesystem::path weights_path =
+ config_path.parent_path() / std::filesystem::path("weights.npy");
+ if (!std::filesystem::exists(weights_path)) {
+ std::stringstream s;
+ s << "No weights in model file, and could not find accompanying weights "
+ "at expected location "
+ << weights_path;
+ throw std::runtime_error(s.str());
}
+ return numpy_util::load_to_vector(weights_path);
+ }
}
-std::unique_ptr<DSP> get_dsp_legacy(const std::filesystem::path model_dir)
-{
+std::unique_ptr<DSP> get_dsp_legacy(const std::filesystem::path model_dir) {
auto config_filename = model_dir / std::filesystem::path("config.json");
return get_dsp(config_filename);
}
-std::unique_ptr<DSP> get_dsp(const std::filesystem::path config_filename)
-{
+std::unique_ptr<DSP> get_dsp(const std::filesystem::path config_filename) {
if (!std::filesystem::exists(config_filename))
throw std::runtime_error("Config JSON doesn't exist!\n");
std::ifstream i(config_filename);
@@ -57,86 +54,69 @@ std::unique_ptr<DSP> get_dsp(const std::filesystem::path config_filename)
nlohmann::json config = j["config"];
std::vector<float> params = _get_weights(j, config_filename);
- if (architecture == "Linear")
- {
+ if (architecture == "Linear") {
const int receptive_field = config["receptive_field"];
const bool _bias = config["bias"];
return std::make_unique<Linear>(receptive_field, _bias, params);
- }
- else if (architecture == "ConvNet")
- {
+ } else if (architecture == "ConvNet") {
const int channels = config["channels"];
const bool batchnorm = config["batchnorm"];
std::vector<int> dilations;
for (int i = 0; i < config["dilations"].size(); i++)
dilations.push_back(config["dilations"][i]);
const std::string activation = config["activation"];
- return std::make_unique<convnet::ConvNet>(channels, dilations, batchnorm, activation, params);
- }
- else if (architecture == "LSTM")
- {
+ return std::make_unique<convnet::ConvNet>(channels, dilations, batchnorm,
+ activation, params);
+ } else if (architecture == "LSTM") {
const int num_layers = config["num_layers"];
const int input_size = config["input_size"];
const int hidden_size = config["hidden_size"];
- auto json = nlohmann::json {};
- return std::make_unique<lstm::LSTM>(num_layers, input_size, hidden_size, params, json);
- }
- else if (architecture == "CatLSTM")
- {
+ auto json = nlohmann::json{};
+ return std::make_unique<lstm::LSTM>(num_layers, input_size, hidden_size,
+ params, json);
+ } else if (architecture == "CatLSTM") {
const int num_layers = config["num_layers"];
const int input_size = config["input_size"];
const int hidden_size = config["hidden_size"];
- return std::make_unique<lstm::LSTM>(num_layers, input_size, hidden_size, params, config["parametric"]);
- }
- else if (architecture == "WaveNet" || architecture == "CatWaveNet")
- {
+ return std::make_unique<lstm::LSTM>(num_layers, input_size, hidden_size,
+ params, config["parametric"]);
+ } else if (architecture == "WaveNet" || architecture == "CatWaveNet") {
std::vector<wavenet::LayerArrayParams> layer_array_params;
for (int i = 0; i < config["layers"].size(); i++) {
nlohmann::json layer_config = config["layers"][i];
std::vector<int> dilations;
for (int j = 0; j < layer_config["dilations"].size(); j++)
dilations.push_back(layer_config["dilations"][j]);
- layer_array_params.push_back(
- wavenet::LayerArrayParams(
- layer_config["input_size"],
- layer_config["condition_size"],
- layer_config["head_size"],
- layer_config["channels"],
- layer_config["kernel_size"],
- dilations,
- layer_config["activation"],
- layer_config["gated"],
- layer_config["head_bias"]
- )
- );
+ layer_array_params.push_back(wavenet::LayerArrayParams(
+ layer_config["input_size"], layer_config["condition_size"],
+ layer_config["head_size"], layer_config["channels"],
+ layer_config["kernel_size"], dilations, layer_config["activation"],
+ layer_config["gated"], layer_config["head_bias"]));
}
const bool with_head = config["head"] == NULL;
const float head_scale = config["head_scale"];
- // Solves compilation issue on macOS Error: No matching constructor for initialization of 'wavenet::WaveNet'
- // Solution from https://stackoverflow.com/a/73956681/3768284
- auto parametric_json = architecture == "CatWaveNet" ? config["parametric"] : nlohmann::json{};
+ // Solves compilation issue on macOS Error: No matching constructor for
+ // initialization of 'wavenet::WaveNet' Solution from
+ // https://stackoverflow.com/a/73956681/3768284
+ auto parametric_json =
+ architecture == "CatWaveNet" ? config["parametric"] : nlohmann::json{};
return std::make_unique<wavenet::WaveNet>(
- layer_array_params,
- head_scale,
- with_head,
- parametric_json,
- params
- );
- }
- else
- {
+ layer_array_params, head_scale, with_head, parametric_json, params);
+ } else {
throw std::runtime_error("Unrecognized architecture");
}
}
-std::unique_ptr<DSP> get_hard_dsp()
-{
+std::unique_ptr<DSP> get_hard_dsp() {
// Values are defined in HardCodedModel.h
verify_config_version(std::string(PYTHON_MODEL_VERSION));
// Uncomment the line that corresponds to the model type that you're using.
-
- //return std::make_unique<convnet::ConvNet>(CHANNELS, DILATIONS, BATCHNORM, ACTIVATION, PARAMS);
- //return std::make_unique<wavenet::WaveNet>(LAYER_ARRAY_PARAMS, HEAD_SCALE, WITH_HEAD, PARAMETRIC, PARAMS);
- return std::make_unique<lstm::LSTM>(NUM_LAYERS, INPUT_SIZE, HIDDEN_SIZE, PARAMS, PARAMETRIC);
+
+ // return std::make_unique<convnet::ConvNet>(CHANNELS, DILATIONS, BATCHNORM,
+ // ACTIVATION, PARAMS); return
+ // std::make_unique<wavenet::WaveNet>(LAYER_ARRAY_PARAMS, HEAD_SCALE,
+ // WITH_HEAD, PARAMETRIC, PARAMS);
+ return std::make_unique<lstm::LSTM>(NUM_LAYERS, INPUT_SIZE, HIDDEN_SIZE,
+ PARAMS, PARAMETRIC);
}
diff --git a/NeuralAmpModeler/dsp/lstm.cpp b/NeuralAmpModeler/dsp/lstm.cpp
@@ -5,8 +5,8 @@
#include "activations.h"
#include "lstm.h"
-lstm::LSTMCell::LSTMCell(const int input_size, const int hidden_size, std::vector<float>::iterator& params)
-{
+lstm::LSTMCell::LSTMCell(const int input_size, const int hidden_size,
+ std::vector<float>::iterator ¶ms) {
// Resize arrays
this->_w.resize(4 * hidden_size, input_size + hidden_size);
this->_b.resize(4 * hidden_size);
@@ -28,8 +28,7 @@ lstm::LSTMCell::LSTMCell(const int input_size, const int hidden_size, std::vecto
this->_c[i] = *(params++);
}
-void lstm::LSTMCell::process_(const Eigen::VectorXf& x)
-{
+void lstm::LSTMCell::process_(const Eigen::VectorXf &x) {
const int hidden_size = this->_get_hidden_size();
const int input_size = this->_get_input_size();
// Assign inputs
@@ -42,18 +41,24 @@ void lstm::LSTMCell::process_(const Eigen::VectorXf& x)
const int g_offset = 2 * hidden_size;
const int o_offset = 3 * hidden_size;
for (int i = 0; i < hidden_size; i++)
- this->_c[i] = activations::sigmoid(this->_ifgo[i + f_offset]) * this->_c[i] + activations::sigmoid(this->_ifgo[i + i_offset]) * tanhf(this->_ifgo[i + g_offset]);
+ this->_c[i] =
+ activations::sigmoid(this->_ifgo[i + f_offset]) * this->_c[i] +
+ activations::sigmoid(this->_ifgo[i + i_offset]) *
+ tanhf(this->_ifgo[i + g_offset]);
const int h_offset = input_size;
for (int i = 0; i < hidden_size; i++)
- this->_xh[i + h_offset] = activations::sigmoid(this->_ifgo[i + o_offset]) * tanhf(this->_c[i]);
+ this->_xh[i + h_offset] =
+ activations::sigmoid(this->_ifgo[i + o_offset]) * tanhf(this->_c[i]);
}
-lstm::LSTM::LSTM(const int num_layers, const int input_size, const int hidden_size, std::vector<float>& params, nlohmann::json& parametric)
-{
+lstm::LSTM::LSTM(const int num_layers, const int input_size,
+ const int hidden_size, std::vector<float> ¶ms,
+ nlohmann::json ¶metric) {
this->_init_parametric(parametric);
std::vector<float>::iterator it = params.begin();
for (int i = 0; i < num_layers; i++)
- this->_layers.push_back(LSTMCell(i == 0 ? input_size : hidden_size, hidden_size, it));
+ this->_layers.push_back(
+ LSTMCell(i == 0 ? input_size : hidden_size, hidden_size, it));
this->_head_weight.resize(hidden_size);
for (int i = 0; i < hidden_size; i++)
this->_head_weight[i] = *(it++);
@@ -61,43 +66,46 @@ lstm::LSTM::LSTM(const int num_layers, const int input_size, const int hidden_si
assert(it == params.end());
}
-void lstm::LSTM::_init_parametric(nlohmann::json& parametric)
-{
+void lstm::LSTM::_init_parametric(nlohmann::json ¶metric) {
std::vector<std::string> parametric_names;
- for (nlohmann::json::iterator it = parametric.begin(); it != parametric.end(); ++it) {
+ for (nlohmann::json::iterator it = parametric.begin(); it != parametric.end();
+ ++it) {
parametric_names.push_back(it.key());
}
std::sort(parametric_names.begin(), parametric_names.end());
{
int i = 1;
- for (std::vector<std::string>::iterator it = parametric_names.begin(); it != parametric_names.end(); ++it, i++)
+ for (std::vector<std::string>::iterator it = parametric_names.begin();
+ it != parametric_names.end(); ++it, i++)
this->_parametric_map[*it] = i;
}
this->_input_and_params.resize(1 + parametric.size()); // TODO amp parameters
}
-void lstm::LSTM::_process_core_()
-{
+void lstm::LSTM::_process_core_() {
// Get params into the input vector before starting
- if (this->_stale_params)
- {
- for (std::unordered_map<std::string, double>::iterator it = this->_params.begin(); it != this->_params.end(); ++it)
+ if (this->_stale_params) {
+ for (std::unordered_map<std::string, double>::iterator it =
+ this->_params.begin();
+ it != this->_params.end(); ++it)
this->_input_and_params[this->_parametric_map[it->first]] = it->second;
this->_stale_params = false;
}
// Process samples, placing results in the required output location
for (int i = 0; i < this->_input_post_gain.size(); i++)
- this->_core_dsp_output[i] = this->_process_sample(this->_input_post_gain[i]);
+ this->_core_dsp_output[i] =
+ this->_process_sample(this->_input_post_gain[i]);
}
-float lstm::LSTM::_process_sample(const float x)
-{
+float lstm::LSTM::_process_sample(const float x) {
if (this->_layers.size() == 0)
return x;
this->_input_and_params(0) = x;
this->_layers[0].process_(this->_input_and_params);
for (int i = 1; i < this->_layers.size(); i++)
this->_layers[i].process_(this->_layers[i - 1].get_hidden_state());
- return this->_head_weight.dot(this->_layers[this->_layers.size() - 1].get_hidden_state()) + this->_head_bias;
+ return this->_head_weight.dot(
+ this->_layers[this->_layers.size() - 1].get_hidden_state()) +
+ this->_head_bias;
}
\ No newline at end of file
diff --git a/NeuralAmpModeler/dsp/lstm.h b/NeuralAmpModeler/dsp/lstm.h
@@ -9,65 +9,65 @@
#include "dsp.h"
#include "json.hpp"
-namespace lstm
-{
- // A Single LSTM cell
- // i input
- // f forget
- // g cell
- // o output
- // c cell state
- // h hidden state
- class LSTMCell
- {
- public:
- LSTMCell(const int input_size, const int hidden_size, std::vector<float>::iterator& params);
- Eigen::VectorXf get_hidden_state() const { return this->_xh(Eigen::placeholders::lastN(this->_get_hidden_size())); };
- void process_(const Eigen::VectorXf& x);
- private:
- // Parameters
- // xh -> ifgo
- // (dx+dh) -> (4*dh)
- Eigen::MatrixXf _w;
- Eigen::VectorXf _b;
+namespace lstm {
+// A Single LSTM cell
+// i input
+// f forget
+// g cell
+// o output
+// c cell state
+// h hidden state
+class LSTMCell {
+public:
+ LSTMCell(const int input_size, const int hidden_size,
+ std::vector<float>::iterator ¶ms);
+ Eigen::VectorXf get_hidden_state() const {
+ return this->_xh(Eigen::placeholders::lastN(this->_get_hidden_size()));
+ };
+ void process_(const Eigen::VectorXf &x);
+
+private:
+ // Parameters
+ // xh -> ifgo
+ // (dx+dh) -> (4*dh)
+ Eigen::MatrixXf _w;
+ Eigen::VectorXf _b;
- // State
- // Concatenated input and hidden state
- Eigen::VectorXf _xh;
- // Input, Forget, Cell, Output gates
- Eigen::VectorXf _ifgo;
-
- // Cell state
- Eigen::VectorXf _c;
+ // State
+ // Concatenated input and hidden state
+ Eigen::VectorXf _xh;
+ // Input, Forget, Cell, Output gates
+ Eigen::VectorXf _ifgo;
- int _get_hidden_size() const { return this->_b.size() / 4; };
- int _get_input_size() const
- {
- return this->_xh.size() - this->_get_hidden_size();
- };
+ // Cell state
+ Eigen::VectorXf _c;
+
+ int _get_hidden_size() const { return this->_b.size() / 4; };
+ int _get_input_size() const {
+ return this->_xh.size() - this->_get_hidden_size();
};
+};
- // The multi-layer LSTM model
- class LSTM : public DSP
- {
- public:
- LSTM(const int num_layers, const int input_size, const int hidden_size, std::vector<float>& params,
- nlohmann::json& parametric);
+// The multi-layer LSTM model
+class LSTM : public DSP {
+public:
+ LSTM(const int num_layers, const int input_size, const int hidden_size,
+ std::vector<float> ¶ms, nlohmann::json ¶metric);
- protected:
- Eigen::VectorXf _head_weight;
- float _head_bias;
- void _process_core_() override;
- std::vector<LSTMCell> _layers;
+protected:
+ Eigen::VectorXf _head_weight;
+ float _head_bias;
+ void _process_core_() override;
+ std::vector<LSTMCell> _layers;
- float _process_sample(const float x);
+ float _process_sample(const float x);
- // Initialize the parametric map
- void _init_parametric(nlohmann::json& parametric);
+ // Initialize the parametric map
+ void _init_parametric(nlohmann::json ¶metric);
- // Mapping from param name to index in _input_and_params:
- std::map<std::string, int> _parametric_map;
- // Input sample first, params second
- Eigen::VectorXf _input_and_params;
- };
-}; // namespace lstm
+ // Mapping from param name to index in _input_and_params:
+ std::map<std::string, int> _parametric_map;
+ // Input sample first, params second
+ Eigen::VectorXf _input_and_params;
+};
+}; // namespace lstm
diff --git a/NeuralAmpModeler/dsp/numpy_util.cpp b/NeuralAmpModeler/dsp/numpy_util.cpp
@@ -6,8 +6,7 @@
#include "cnpy.h"
#include "numpy_util.h"
-std::vector<float> numpy_util::load_to_vector(std::filesystem::path path)
-{
+std::vector<float> numpy_util::load_to_vector(std::filesystem::path path) {
cnpy::NpyArray x = cnpy::npy_load(path.string());
if (x.shape.size() != 1)
throw std::runtime_error("Expected 1D array.\n");
diff --git a/NeuralAmpModeler/dsp/numpy_util.h b/NeuralAmpModeler/dsp/numpy_util.h
@@ -4,7 +4,7 @@
#include <vector>
namespace numpy_util {
- // Get data from a file to a flat array.
- // Don't worry; I flattened everythign when exporting from Python :)
- std::vector<float> load_to_vector(std::filesystem::path path);
-};
-\ No newline at end of file
+// Get data from a file to a flat array.
+// Don't worry; I flattened everythign when exporting from Python :)
+std::vector<float> load_to_vector(std::filesystem::path path);
+}; // namespace numpy_util
+\ No newline at end of file
diff --git a/NeuralAmpModeler/dsp/util.cpp b/NeuralAmpModeler/dsp/util.cpp
@@ -3,9 +3,9 @@
#include "util.h"
-std::string util::lowercase(const std::string& s)
-{
+std::string util::lowercase(const std::string &s) {
std::string out(s);
- std::transform(s.begin(), s.end(), out.begin(), [](unsigned char c) {return std::tolower(c); });
+ std::transform(s.begin(), s.end(), out.begin(),
+ [](unsigned char c) { return std::tolower(c); });
return out;
}
\ No newline at end of file
diff --git a/NeuralAmpModeler/dsp/util.h b/NeuralAmpModeler/dsp/util.h
@@ -5,6 +5,5 @@
#include <string>
namespace util {
- std::string lowercase(const std::string& s);
+std::string lowercase(const std::string &s);
}; // namespace util
-
diff --git a/NeuralAmpModeler/dsp/wav.cpp b/NeuralAmpModeler/dsp/wav.cpp
@@ -5,24 +5,22 @@
// Created by Steven Atkinson on 12/31/22.
//
-#include <cmath> // pow
-#include <iostream>
+#include <cmath> // pow
#include <fstream>
+#include <iostream>
#include <vector>
#include "wav.h"
-bool idIsJunk(char* id)
-{
+bool idIsJunk(char *id) {
return (strncmp(id, "junk", 4) == 0) || (strncmp(id, "JUNK", 4) == 0);
}
-void ReadChunkAndSkipJunk(std::ifstream& file, char* chunkID)
-{
+void ReadChunkAndSkipJunk(std::ifstream &file, char *chunkID) {
file.read(chunkID, 4);
if (idIsJunk(chunkID)) {
int junkSize;
- file.read(reinterpret_cast<char*>(&junkSize), 4);
+ file.read(reinterpret_cast<char *>(&junkSize), 4);
file.ignore(junkSize);
// Unused byte if junkSize is odd
if ((junkSize % 2) == 1)
@@ -34,94 +32,97 @@ void ReadChunkAndSkipJunk(std::ifstream& file, char* chunkID)
throw std::runtime_error("Found more than 1 junk chunk");
}
-dsp::wav::LoadReturnCode dsp::wav::Load(const WDL_String &fileName, std::vector<float> &audio, double &sampleRate)
-{
+dsp::wav::LoadReturnCode dsp::wav::Load(const WDL_String &fileName,
+ std::vector<float> &audio,
+ double &sampleRate) {
// FYI: https://www.mmsp.ece.mcgill.ca/Documents/AudioFormats/WAVE/WAVE.html
// Open the WAV file for reading
std::ifstream wavFile(fileName.Get(), std::ios::binary);
-
+
// Check if the file was opened successfully
if (!wavFile.is_open()) {
std::cerr << "Error opening WAV file" << std::endl;
return dsp::wav::LoadReturnCode::ERROR_OPENING;
}
-
+
// WAV file has 3 "chunks": RIFF ("RIFF"), format ("fmt ") and data ("data").
// Read the WAV file header
char chunkId[4];
ReadChunkAndSkipJunk(wavFile, chunkId);
if (strncmp(chunkId, "RIFF", 4) != 0) {
- std::cerr << "Error: File does not start with expected RIFF chunk. Got" << chunkId << " instead." << std::endl;
+ std::cerr << "Error: File does not start with expected RIFF chunk. Got"
+ << chunkId << " instead." << std::endl;
return dsp::wav::LoadReturnCode::ERROR_NOT_RIFF;
}
-
+
int chunkSize;
- wavFile.read(reinterpret_cast<char*>(&chunkSize), 4);
-
+ wavFile.read(reinterpret_cast<char *>(&chunkSize), 4);
+
char format[4];
wavFile.read(format, 4);
if (strncmp(format, "WAVE", 4) != 0) {
- std::cerr << "Error: Files' second chunk (format) is not expected WAV. Got" << format << " instead." << std::endl;
+ std::cerr << "Error: Files' second chunk (format) is not expected WAV. Got"
+ << format << " instead." << std::endl;
return dsp::wav::LoadReturnCode::ERROR_NOT_WAVE;
}
-
+
// Read the format chunk
char subchunk1Id[4];
ReadChunkAndSkipJunk(wavFile, subchunk1Id);
if (strncmp(subchunk1Id, "fmt ", 4) != 0) {
- std::cerr << "Error: Invalid WAV file missing expected fmt section; got " << subchunk1Id << " instead." << std::endl;
+ std::cerr << "Error: Invalid WAV file missing expected fmt section; got "
+ << subchunk1Id << " instead." << std::endl;
return dsp::wav::LoadReturnCode::ERROR_MISSING_FMT;
}
-
+
int subchunk1Size;
- wavFile.read(reinterpret_cast<char*>(&subchunk1Size), 4);
-
+ wavFile.read(reinterpret_cast<char *>(&subchunk1Size), 4);
+
unsigned short audioFormat;
- wavFile.read(reinterpret_cast<char*>(&audioFormat), 2);
+ wavFile.read(reinterpret_cast<char *>(&audioFormat), 2);
if (audioFormat != 1) {
- std::cerr << "Error: Only PCM format is supported.";
- switch (audioFormat)
- {
+ std::cerr << "Error: Only PCM format is supported.";
+ switch (audioFormat) {
case 3:
- std::cerr << "(Got: IEEE float)" << std::endl;
- return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_IEEE_FLOAT;
+ std::cerr << "(Got: IEEE float)" << std::endl;
+ return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_IEEE_FLOAT;
case 6:
- std::cerr << "(Got: A-law)" << std::endl;
- return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_ALAW;
+ std::cerr << "(Got: A-law)" << std::endl;
+ return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_ALAW;
case 7:
- std::cerr << "(Got: mu-law)" << std::endl;
- return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_MULAW;
+ std::cerr << "(Got: mu-law)" << std::endl;
+ return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_MULAW;
case 65534:
- std::cerr << "(Got: Extensible)" << std::endl;
- return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_EXTENSIBLE;
+ std::cerr << "(Got: Extensible)" << std::endl;
+ return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_FORMAT_EXTENSIBLE;
default:
- std::cerr << "(Got unknown format " << audioFormat << ")" << std::endl;
- return dsp::wav::LoadReturnCode::ERROR_INVALID_FILE;
+ std::cerr << "(Got unknown format " << audioFormat << ")" << std::endl;
+ return dsp::wav::LoadReturnCode::ERROR_INVALID_FILE;
}
}
-
+
short numChannels;
- wavFile.read(reinterpret_cast<char*>(&numChannels), 2);
+ wavFile.read(reinterpret_cast<char *>(&numChannels), 2);
// HACK
if (numChannels != 1) {
std::cerr << "Require mono (using for IR loading)" << std::endl;
return dsp::wav::LoadReturnCode::ERROR_NOT_MONO;
}
-
+
int iSampleRate;
- wavFile.read(reinterpret_cast<char*>(&iSampleRate), 4);
+ wavFile.read(reinterpret_cast<char *>(&iSampleRate), 4);
// Store in format we assume (SR is double)
- sampleRate = (double) iSampleRate;
-
+ sampleRate = (double)iSampleRate;
+
int byteRate;
- wavFile.read(reinterpret_cast<char*>(&byteRate), 4);
-
+ wavFile.read(reinterpret_cast<char *>(&byteRate), 4);
+
short blockAlign;
- wavFile.read(reinterpret_cast<char*>(&blockAlign), 2);
-
+ wavFile.read(reinterpret_cast<char *>(&blockAlign), 2);
+
short bitsPerSample;
- wavFile.read(reinterpret_cast<char*>(&bitsPerSample), 2);
-
+ wavFile.read(reinterpret_cast<char *>(&bitsPerSample), 2);
+
// Read the data chunk
char subchunk2Id[4];
ReadChunkAndSkipJunk(wavFile, subchunk2Id);
@@ -129,11 +130,11 @@ dsp::wav::LoadReturnCode dsp::wav::Load(const WDL_String &fileName, std::vector<
std::cerr << "Error: Invalid WAV file" << std::endl;
return dsp::wav::LoadReturnCode::ERROR_INVALID_FILE;
}
-
+
// Size of the data chunk, in bits.
int subchunk2Size;
- wavFile.read(reinterpret_cast<char*>(&subchunk2Size), 4);
-
+ wavFile.read(reinterpret_cast<char *>(&subchunk2Size), 4);
+
if (bitsPerSample == 16)
dsp::wav::_LoadSamples16(wavFile, subchunk2Size, audio);
else if (bitsPerSample == 24)
@@ -141,81 +142,75 @@ dsp::wav::LoadReturnCode dsp::wav::Load(const WDL_String &fileName, std::vector<
else if (bitsPerSample == 32)
dsp::wav::_LoadSamples32(wavFile, subchunk2Size, audio);
else {
- std::cerr << "Error: Unsupported bits per sample: " << bitsPerSample << std::endl;
+ std::cerr << "Error: Unsupported bits per sample: " << bitsPerSample
+ << std::endl;
return dsp::wav::LoadReturnCode::ERROR_UNSUPPORTED_BITS_PER_SAMPLE;
}
-
+
// Close the WAV file
wavFile.close();
-
+
// Print the number of samples
// std::cout << "Number of samples: " << samples.size() << std::endl;
-
+
return dsp::wav::LoadReturnCode::SUCCESS;
}
-void dsp::wav::_LoadSamples16(std::ifstream &wavFile,
- const int chunkSize,
- std::vector<float>& samples)
-{
+void dsp::wav::_LoadSamples16(std::ifstream &wavFile, const int chunkSize,
+ std::vector<float> &samples) {
// Allocate an array to hold the samples
- std::vector<short> tmp(chunkSize / 2); // 16 bits (2 bytes) per sample
-
+ std::vector<short> tmp(chunkSize / 2); // 16 bits (2 bytes) per sample
+
// Read the samples from the file into the array
- wavFile.read(reinterpret_cast<char*>(tmp.data()), chunkSize);
-
+ wavFile.read(reinterpret_cast<char *>(tmp.data()), chunkSize);
+
// Copy into the return array
- const float scale = 1.0 / ((double) (1 << 15));
+ const float scale = 1.0 / ((double)(1 << 15));
samples.resize(tmp.size());
- for (auto i=0; i<samples.size(); i++)
- samples[i] = scale * ((float) tmp[i]); // 2^16
+ for (auto i = 0; i < samples.size(); i++)
+ samples[i] = scale * ((float)tmp[i]); // 2^16
}
-void dsp::wav::_LoadSamples24(std::ifstream &wavFile,
- const int chunkSize,
- std::vector<float>& samples)
-{
+void dsp::wav::_LoadSamples24(std::ifstream &wavFile, const int chunkSize,
+ std::vector<float> &samples) {
// Allocate an array to hold the samples
- std::vector<int> tmp(chunkSize / 3); // 24 bits (3 bytes) per sample
+ std::vector<int> tmp(chunkSize / 3); // 24 bits (3 bytes) per sample
// Read in and convert the samples
- for (int& x : tmp) {
+ for (int &x : tmp) {
x = dsp::wav::_ReadSigned24BitInt(wavFile);
}
-
+
// Copy into the return array
- const float scale = 1.0 / ((double) (1 << 23));
+ const float scale = 1.0 / ((double)(1 << 23));
samples.resize(tmp.size());
- for (auto i=0; i<samples.size(); i++)
- samples[i] = scale * ((float) tmp[i]);
+ for (auto i = 0; i < samples.size(); i++)
+ samples[i] = scale * ((float)tmp[i]);
}
-int dsp::wav::_ReadSigned24BitInt(std::ifstream& stream) {
+int dsp::wav::_ReadSigned24BitInt(std::ifstream &stream) {
// Read the three bytes of the 24-bit integer.
std::uint8_t bytes[3];
- stream.read(reinterpret_cast<char*>(bytes), 3);
-
- // Combine the three bytes into a single integer using bit shifting and masking.
- // This works by isolating each byte using a bit mask (0xff) and then shifting
- // the byte to the correct position in the final integer.
- int value = bytes[0] | (bytes[1] << 8) | (bytes[2]<<16);
-
+ stream.read(reinterpret_cast<char *>(bytes), 3);
+
+ // Combine the three bytes into a single integer using bit shifting and
+ // masking. This works by isolating each byte using a bit mask (0xff) and then
+ // shifting the byte to the correct position in the final integer.
+ int value = bytes[0] | (bytes[1] << 8) | (bytes[2] << 16);
+
// The value is stored in two's complement format, so if the most significant
// bit (the 24th bit) is set, then the value is negative. In this case, we
// need to extend the sign bit to get the correct negative value.
if (value & (1 << 23)) {
value |= ~((1 << 24) - 1);
}
-
+
return value;
}
-
-void dsp::wav::_LoadSamples32(std::ifstream &wavFile,
- const int chunkSize,
- std::vector<float>& samples)
-{
+void dsp::wav::_LoadSamples32(std::ifstream &wavFile, const int chunkSize,
+ std::vector<float> &samples) {
// NOTE: 32-bit is float.
- samples.resize(chunkSize / 4); // 32 bits (4 bytes) per sample
+ samples.resize(chunkSize / 4); // 32 bits (4 bytes) per sample
// Read the samples from the file into the array
- wavFile.read(reinterpret_cast<char*>(samples.data()), chunkSize);
+ wavFile.read(reinterpret_cast<char *>(samples.data()), chunkSize);
}
diff --git a/NeuralAmpModeler/dsp/wav.h b/NeuralAmpModeler/dsp/wav.h
@@ -8,41 +8,45 @@
#ifndef wav_h
#define wav_h
-#include "wdlstring.h" // WDL_String
+#include "wdlstring.h" // WDL_String
namespace dsp {
- namespace wav {
- enum class LoadReturnCode {
- SUCCESS = 0,
- ERROR_OPENING,
- ERROR_NOT_RIFF,
- ERROR_NOT_WAVE,
- ERROR_MISSING_FMT,
- ERROR_INVALID_FILE,
- ERROR_UNSUPPORTED_FORMAT_IEEE_FLOAT,
- ERROR_UNSUPPORTED_FORMAT_ALAW,
- ERROR_UNSUPPORTED_FORMAT_MULAW,
- ERROR_UNSUPPORTED_FORMAT_EXTENSIBLE,
- ERROR_UNSUPPORTED_BITS_PER_SAMPLE,
- ERROR_NOT_MONO,
- ERROR_OTHER
- };
- // Load a WAV file into a provided array of doubles,
- // And note the sample rate.
- //
- // Returns: as per return cases above
- LoadReturnCode Load(const WDL_String& fileName, std::vector<float> &audio, double& sampleRate);
-
- // Load samples, 16-bit
- void _LoadSamples16(std::ifstream &wavFile, const int chunkSize, std::vector<float>& samples);
- // Load samples, 24-bit
- void _LoadSamples24(std::ifstream &wavFile, const int chunkSize, std::vector<float>& samples);
- // Load samples, 32-bit
- void _LoadSamples32(std::ifstream &wavFile, const int chunkSize, std::vector<float>& samples);
-
- // Read in a 24-bit sample and convert it to an int
- int _ReadSigned24BitInt(std::ifstream& stream);
- };
+namespace wav {
+enum class LoadReturnCode {
+ SUCCESS = 0,
+ ERROR_OPENING,
+ ERROR_NOT_RIFF,
+ ERROR_NOT_WAVE,
+ ERROR_MISSING_FMT,
+ ERROR_INVALID_FILE,
+ ERROR_UNSUPPORTED_FORMAT_IEEE_FLOAT,
+ ERROR_UNSUPPORTED_FORMAT_ALAW,
+ ERROR_UNSUPPORTED_FORMAT_MULAW,
+ ERROR_UNSUPPORTED_FORMAT_EXTENSIBLE,
+ ERROR_UNSUPPORTED_BITS_PER_SAMPLE,
+ ERROR_NOT_MONO,
+ ERROR_OTHER
};
+// Load a WAV file into a provided array of doubles,
+// And note the sample rate.
+//
+// Returns: as per return cases above
+LoadReturnCode Load(const WDL_String &fileName, std::vector<float> &audio,
+ double &sampleRate);
+
+// Load samples, 16-bit
+void _LoadSamples16(std::ifstream &wavFile, const int chunkSize,
+ std::vector<float> &samples);
+// Load samples, 24-bit
+void _LoadSamples24(std::ifstream &wavFile, const int chunkSize,
+ std::vector<float> &samples);
+// Load samples, 32-bit
+void _LoadSamples32(std::ifstream &wavFile, const int chunkSize,
+ std::vector<float> &samples);
+
+// Read in a 24-bit sample and convert it to an int
+int _ReadSigned24BitInt(std::ifstream &stream);
+}; // namespace wav
+}; // namespace dsp
#endif /* wav_h */
diff --git a/NeuralAmpModeler/dsp/wavenet.cpp b/NeuralAmpModeler/dsp/wavenet.cpp
@@ -5,33 +5,24 @@
#include "wavenet.h"
-wavenet::_DilatedConv::_DilatedConv(
- const int in_channels,
- const int out_channels,
- const int kernel_size,
- const int bias,
- const int dilation
-)
-{
+wavenet::_DilatedConv::_DilatedConv(const int in_channels,
+ const int out_channels,
+ const int kernel_size, const int bias,
+ const int dilation) {
this->set_size_(in_channels, out_channels, kernel_size, bias, dilation);
}
-void wavenet::_Layer::set_params_(std::vector<float>::iterator& params)
-{
+void wavenet::_Layer::set_params_(std::vector<float>::iterator ¶ms) {
this->_conv.set_params_(params);
this->_input_mixin.set_params_(params);
this->_1x1.set_params_(params);
}
-void wavenet::_Layer::process_(
- const Eigen::MatrixXf& input,
- const Eigen::MatrixXf& condition,
- Eigen::MatrixXf& head_input,
- Eigen::MatrixXf& output,
- const long i_start,
- const long j_start
-)
-{
+void wavenet::_Layer::process_(const Eigen::MatrixXf &input,
+ const Eigen::MatrixXf &condition,
+ Eigen::MatrixXf &head_input,
+ Eigen::MatrixXf &output, const long i_start,
+ const long j_start) {
const long ncols = condition.cols();
const long channels = this->get_channels();
// Input dilated conv
@@ -46,19 +37,19 @@ void wavenet::_Layer::process_(
throw std::runtime_error("Unrecognized activation.");
if (this->_gated) {
sigmoid_(this->_z, channels, 2 * channels, 0, this->_z.cols());
- this->_z.topRows(channels).array() *= this->_z.bottomRows(channels).array();
+ this->_z.topRows(channels).array() *= this->_z.bottomRows(channels).array();
// this->_z.topRows(channels) = this->_z.topRows(channels).cwiseProduct(
// this->_z.bottomRows(channels)
// );
}
head_input += this->_z.topRows(channels);
- output.middleCols(j_start, ncols) = input.middleCols(i_start, ncols)
- + this->_1x1.process(this->_z.topRows(channels));
+ output.middleCols(j_start, ncols) =
+ input.middleCols(i_start, ncols) +
+ this->_1x1.process(this->_z.topRows(channels));
}
-void wavenet::_Layer::set_num_frames_(const int num_frames)
-{
+void wavenet::_Layer::set_num_frames_(const int num_frames) {
this->_z.resize(this->_conv.get_out_channels(), num_frames);
}
@@ -66,110 +57,89 @@ void wavenet::_Layer::set_num_frames_(const int num_frames)
#define LAYER_ARRAY_BUFFER_SIZE 65536
-wavenet::_LayerArray::_LayerArray(
- const int input_size,
- const int condition_size,
- const int head_size,
- const int channels,
- const int kernel_size,
- const std::vector<int>& dilations,
- const std::string activation,
- const bool gated,
- const bool head_bias
-) :
- _rechannel(input_size, channels, false),
- _head_rechannel(channels, head_size, head_bias)
-{
+wavenet::_LayerArray::_LayerArray(const int input_size,
+ const int condition_size, const int head_size,
+ const int channels, const int kernel_size,
+ const std::vector<int> &dilations,
+ const std::string activation,
+ const bool gated, const bool head_bias)
+ : _rechannel(input_size, channels, false),
+ _head_rechannel(channels, head_size, head_bias) {
for (int i = 0; i < dilations.size(); i++)
- this->_layers.push_back(_Layer(condition_size, channels, kernel_size, dilations[i], activation, gated));
+ this->_layers.push_back(_Layer(condition_size, channels, kernel_size,
+ dilations[i], activation, gated));
const long receptive_field = this->_get_receptive_field();
for (int i = 0; i < dilations.size(); i++)
- this->_layer_buffers.push_back(
- Eigen::MatrixXf(channels, LAYER_ARRAY_BUFFER_SIZE + receptive_field - 1)
- );
+ this->_layer_buffers.push_back(Eigen::MatrixXf(
+ channels, LAYER_ARRAY_BUFFER_SIZE + receptive_field - 1));
this->_buffer_start = this->_get_receptive_field() - 1;
}
-void wavenet::_LayerArray::advance_buffers_(const int num_frames)
-{
+void wavenet::_LayerArray::advance_buffers_(const int num_frames) {
this->_buffer_start += num_frames;
}
-long wavenet::_LayerArray::get_receptive_field() const
-{
- long result = 0;
- for (int i = 0; i < this->_layers.size(); i++)
- result += this->_layers[i].get_dilation() * (this->_layers[i].get_kernel_size() - 1);
- return result;
+long wavenet::_LayerArray::get_receptive_field() const {
+ long result = 0;
+ for (int i = 0; i < this->_layers.size(); i++)
+ result += this->_layers[i].get_dilation() *
+ (this->_layers[i].get_kernel_size() - 1);
+ return result;
}
-void wavenet::_LayerArray::prepare_for_frames_(const int num_frames)
-{
+void wavenet::_LayerArray::prepare_for_frames_(const int num_frames) {
if (this->_buffer_start + num_frames > this->_get_buffer_size())
this->_rewind_buffers_();
}
-void wavenet::_LayerArray::process_(
- const Eigen::MatrixXf& layer_inputs,
- const Eigen::MatrixXf& condition,
- Eigen::MatrixXf& head_inputs,
- Eigen::MatrixXf& layer_outputs,
- Eigen::MatrixXf& head_outputs
-)
-{
+void wavenet::_LayerArray::process_(const Eigen::MatrixXf &layer_inputs,
+ const Eigen::MatrixXf &condition,
+ Eigen::MatrixXf &head_inputs,
+ Eigen::MatrixXf &layer_outputs,
+ Eigen::MatrixXf &head_outputs) {
this->_layer_buffers[0].middleCols(this->_buffer_start, layer_inputs.cols()) =
- this->_rechannel.process(layer_inputs);
+ this->_rechannel.process(layer_inputs);
const int last_layer = this->_layers.size() - 1;
for (int i = 0; i < this->_layers.size(); i++) {
this->_layers[i].process_(
- this->_layer_buffers[i],
- condition,
- head_inputs,
- i == last_layer ? layer_outputs : this->_layer_buffers[i + 1],
- this->_buffer_start,
- i == last_layer ? 0 : this->_buffer_start
- );
+ this->_layer_buffers[i], condition, head_inputs,
+ i == last_layer ? layer_outputs : this->_layer_buffers[i + 1],
+ this->_buffer_start, i == last_layer ? 0 : this->_buffer_start);
}
head_outputs = this->_head_rechannel.process(head_inputs);
}
-void wavenet::_LayerArray::set_num_frames_(const int num_frames)
-{
+void wavenet::_LayerArray::set_num_frames_(const int num_frames) {
// Wavenet checks for unchanged num_frames; if we made it here, there's
// something to do.
if (LAYER_ARRAY_BUFFER_SIZE - num_frames < this->_get_receptive_field()) {
std::stringstream ss;
- ss << "Asked to accept a buffer of "
- << num_frames
- << " samples, but the buffer is too short ("
- << LAYER_ARRAY_BUFFER_SIZE
- << ") to get out of the recptive field ("
- << this->_get_receptive_field()
- << "); copy errors could occur!\n";
+ ss << "Asked to accept a buffer of " << num_frames
+ << " samples, but the buffer is too short (" << LAYER_ARRAY_BUFFER_SIZE
+ << ") to get out of the recptive field (" << this->_get_receptive_field()
+ << "); copy errors could occur!\n";
throw std::runtime_error(ss.str().c_str());
}
for (int i = 0; i < this->_layers.size(); i++)
this->_layers[i].set_num_frames_(num_frames);
}
-void wavenet::_LayerArray::set_params_(std::vector<float>::iterator& params)
-{
+void wavenet::_LayerArray::set_params_(std::vector<float>::iterator ¶ms) {
this->_rechannel.set_params_(params);
for (int i = 0; i < this->_layers.size(); i++)
this->_layers[i].set_params_(params);
this->_head_rechannel.set_params_(params);
}
-int wavenet::_LayerArray::_get_channels() const
-{
+int wavenet::_LayerArray::_get_channels() const {
return this->_layers.size() > 0 ? this->_layers[0].get_channels() : 0;
}
-long wavenet::_LayerArray::_get_receptive_field() const
-{
+long wavenet::_LayerArray::_get_receptive_field() const {
long res = 1;
for (int i = 0; i < this->_layers.size(); i++)
- res += (this->_layers[i].get_kernel_size() - 1) * this->_layers[i].get_dilation();
+ res += (this->_layers[i].get_kernel_size() - 1) *
+ this->_layers[i].get_dilation();
return res;
}
@@ -179,54 +149,45 @@ void wavenet::_LayerArray::_rewind_buffers_()
{
const long start = this->_get_receptive_field() - 1;
for (int i = 0; i < this->_layer_buffers.size(); i++) {
- const long d = (this->_layers[i].get_kernel_size()-1) * this->_layers[i].get_dilation();
- this->_layer_buffers[i].middleCols(start - d, d) = this->_layer_buffers[i].middleCols(
- this->_buffer_start - d, d
- );
+ const long d = (this->_layers[i].get_kernel_size() - 1) *
+ this->_layers[i].get_dilation();
+ this->_layer_buffers[i].middleCols(start - d, d) =
+ this->_layer_buffers[i].middleCols(this->_buffer_start - d, d);
}
this->_buffer_start = start;
}
// Head =======================================================================
-wavenet::_Head::_Head(
- const int input_size,
- const int num_layers,
- const int channels,
- const std::string activation
-) :
- _channels(channels),
- _activation(activation),
- _head(num_layers > 0 ? channels : input_size, 1, true)
-{
+wavenet::_Head::_Head(const int input_size, const int num_layers,
+ const int channels, const std::string activation)
+ : _channels(channels), _activation(activation),
+ _head(num_layers > 0 ? channels : input_size, 1, true) {
assert(num_layers > 0);
int dx = input_size;
for (int i = 0; i < num_layers; i++) {
- this->_layers.push_back(Conv1x1(dx, i == num_layers-1 ? 1 : channels, true));
+ this->_layers.push_back(
+ Conv1x1(dx, i == num_layers - 1 ? 1 : channels, true));
dx = channels;
- if (i < num_layers-1)
+ if (i < num_layers - 1)
this->_buffers.push_back(Eigen::MatrixXf());
}
}
-void wavenet::_Head::set_params_(std::vector<float>::iterator& params)
-{
+void wavenet::_Head::set_params_(std::vector<float>::iterator ¶ms) {
for (int i = 0; i < this->_layers.size(); i++)
this->_layers[i].set_params_(params);
}
-void wavenet::_Head::process_(
- Eigen::MatrixXf& inputs,
- Eigen::MatrixXf& outputs
-)
-{
+void wavenet::_Head::process_(Eigen::MatrixXf &inputs,
+ Eigen::MatrixXf &outputs) {
const int num_layers = this->_layers.size();
this->_apply_activation_(inputs);
if (num_layers == 1)
outputs = this->_layers[0].process(inputs);
else {
this->_buffers[0] = this->_layers[0].process(inputs);
- for (int i = 1; i < num_layers; i++) {//Asserted > 0 layers
+ for (int i = 1; i < num_layers; i++) { // Asserted > 0 layers
this->_apply_activation_(this->_buffers[i - 1]);
if (i < num_layers - 1)
this->_buffers[i] = this->_layers[i].process(this->_buffers[i - 1]);
@@ -236,14 +197,12 @@ void wavenet::_Head::process_(
}
}
-void wavenet::_Head::set_num_frames_(const int num_frames)
-{
+void wavenet::_Head::set_num_frames_(const int num_frames) {
for (int i = 0; i < this->_buffers.size(); i++)
this->_buffers[i].resize(this->_channels, num_frames);
}
-void wavenet::_Head::_apply_activation_(Eigen::MatrixXf& x)
-{
+void wavenet::_Head::_apply_activation_(Eigen::MatrixXf &x) {
if (this->_activation == "Tanh")
tanh_(x);
else if (this->_activation == "ReLU")
@@ -255,99 +214,88 @@ void wavenet::_Head::_apply_activation_(Eigen::MatrixXf& x)
// WaveNet ====================================================================
wavenet::WaveNet::WaveNet(
- const std::vector<wavenet::LayerArrayParams>& layer_array_params,
- const float head_scale,
- const bool with_head,
- nlohmann::json parametric,
- std::vector<float> params
-) :
- //_head(channels, head_layers, head_channels, head_activation),
- _num_frames(0),
- _head_scale(head_scale)
-{
+ const std::vector<wavenet::LayerArrayParams> &layer_array_params,
+ const float head_scale, const bool with_head, nlohmann::json parametric,
+ std::vector<float> params)
+ : //_head(channels, head_layers, head_channels, head_activation),
+ _num_frames(0), _head_scale(head_scale) {
if (with_head)
throw std::runtime_error("Head not implemented!");
this->_init_parametric_(parametric);
for (int i = 0; i < layer_array_params.size(); i++) {
- this->_layer_arrays.push_back(
- wavenet::_LayerArray(
- layer_array_params[i].input_size,
- layer_array_params[i].condition_size,
- layer_array_params[i].head_size,
- layer_array_params[i].channels,
- layer_array_params[i].kernel_size,
- layer_array_params[i].dilations,
- layer_array_params[i].activation,
- layer_array_params[i].gated,
- layer_array_params[i].head_bias
- )
- );
- this->_layer_array_outputs.push_back(Eigen::MatrixXf(layer_array_params[i].channels, 0));
+ this->_layer_arrays.push_back(wavenet::_LayerArray(
+ layer_array_params[i].input_size, layer_array_params[i].condition_size,
+ layer_array_params[i].head_size, layer_array_params[i].channels,
+ layer_array_params[i].kernel_size, layer_array_params[i].dilations,
+ layer_array_params[i].activation, layer_array_params[i].gated,
+ layer_array_params[i].head_bias));
+ this->_layer_array_outputs.push_back(
+ Eigen::MatrixXf(layer_array_params[i].channels, 0));
if (i == 0)
- this->_head_arrays.push_back(Eigen::MatrixXf(layer_array_params[i].channels, 0));
+ this->_head_arrays.push_back(
+ Eigen::MatrixXf(layer_array_params[i].channels, 0));
if (i > 0)
- if (layer_array_params[i].channels != layer_array_params[i - 1].head_size) {
+ if (layer_array_params[i].channels !=
+ layer_array_params[i - 1].head_size) {
std::stringstream ss;
- ss << "channels of layer " << i << " (" << layer_array_params[i].channels
- << ") doesn't match head_size of preceding layer ("
- << layer_array_params[i - 1].head_size
- << "!\n";
+ ss << "channels of layer " << i << " ("
+ << layer_array_params[i].channels
+ << ") doesn't match head_size of preceding layer ("
+ << layer_array_params[i - 1].head_size << "!\n";
throw std::runtime_error(ss.str().c_str());
}
- this->_head_arrays.push_back(Eigen::MatrixXf(layer_array_params[i].head_size, 0));
+ this->_head_arrays.push_back(
+ Eigen::MatrixXf(layer_array_params[i].head_size, 0));
}
- this->_head_output.resize(1, 0); // Mono output!
+ this->_head_output.resize(1, 0); // Mono output!
this->set_params_(params);
this->_reset_anti_pop_();
}
-void wavenet::WaveNet::finalize_(const int num_frames)
-{
+void wavenet::WaveNet::finalize_(const int num_frames) {
this->DSP::finalize_(num_frames);
this->_advance_buffers_(num_frames);
}
-void wavenet::WaveNet::set_params_(std::vector<float>& params)
-{
+void wavenet::WaveNet::set_params_(std::vector<float> ¶ms) {
std::vector<float>::iterator it = params.begin();
for (int i = 0; i < this->_layer_arrays.size(); i++)
this->_layer_arrays[i].set_params_(it);
- //this->_head.set_params_(it);
+ // this->_head.set_params_(it);
this->_head_scale = *(it++);
if (it != params.end()) {
std::stringstream ss;
for (int i = 0; i < params.size(); i++)
if (params[i] == *it) {
- ss << "Parameter mismatch: assigned " << i+1 << " parameters, but " << params.size() << " were provided.";
+ ss << "Parameter mismatch: assigned " << i + 1 << " parameters, but "
+ << params.size() << " were provided.";
throw std::runtime_error(ss.str().c_str());
}
- ss << "Parameter mismatch: provided " << params.size() << " weights, but the model expects more.";
+ ss << "Parameter mismatch: provided " << params.size()
+ << " weights, but the model expects more.";
throw std::runtime_error(ss.str().c_str());
}
}
-void wavenet::WaveNet::_advance_buffers_(const int num_frames)
-{
+void wavenet::WaveNet::_advance_buffers_(const int num_frames) {
for (int i = 0; i < this->_layer_arrays.size(); i++)
this->_layer_arrays[i].advance_buffers_(num_frames);
}
-void wavenet::WaveNet::_init_parametric_(nlohmann::json& parametric)
-{
- for (nlohmann::json::iterator it = parametric.begin(); it != parametric.end(); ++it)
+void wavenet::WaveNet::_init_parametric_(nlohmann::json ¶metric) {
+ for (nlohmann::json::iterator it = parametric.begin(); it != parametric.end();
+ ++it)
this->_param_names.push_back(it.key());
- // TODO assert continuous 0 to 1
+ // TODO assert continuous 0 to 1
std::sort(this->_param_names.begin(), this->_param_names.end());
}
-void wavenet::WaveNet::_prepare_for_frames_(const int num_frames)
-{
+void wavenet::WaveNet::_prepare_for_frames_(const int num_frames) {
for (int i = 0; i < this->_layer_arrays.size(); i++)
this->_layer_arrays[i].prepare_for_frames_(num_frames);
}
-void wavenet::WaveNet::_process_core_()
-{
+void wavenet::WaveNet::_process_core_() {
const long num_frames = this->_input_post_gain.size();
this->_set_num_frames_(num_frames);
this->_prepare_for_frames_(num_frames);
@@ -356,9 +304,11 @@ void wavenet::WaveNet::_process_core_()
// Clumsy...
for (int j = 0; j < num_frames; j++) {
this->_condition(0, j) = this->_input_post_gain[j];
- if (this->_stale_params) // Column-major assignment; good for Eigen. Let the compiler optimize this.
+ if (this->_stale_params) // Column-major assignment; good for Eigen. Let the
+ // compiler optimize this.
for (int i = 0; i < this->_param_names.size(); i++)
- this->_condition(i + 1, j) = (float) this->_params[this->_param_names[i]];
+ this->_condition(i + 1, j) =
+ (float)this->_params[this->_param_names[i]];
}
// Main layer arrays:
@@ -367,30 +317,27 @@ void wavenet::WaveNet::_process_core_()
this->_head_arrays[0].setZero();
for (int i = 0; i < this->_layer_arrays.size(); i++)
this->_layer_arrays[i].process_(
- i == 0 ? this->_condition : this->_layer_array_outputs[i-1],
- this->_condition,
- this->_head_arrays[i],
- this->_layer_array_outputs[i],
- this->_head_arrays[i+1]
- );
- //this->_head.process_(
- // this->_head_input,
- // this->_head_output
+ i == 0 ? this->_condition : this->_layer_array_outputs[i - 1],
+ this->_condition, this->_head_arrays[i], this->_layer_array_outputs[i],
+ this->_head_arrays[i + 1]);
+ // this->_head.process_(
+ // this->_head_input,
+ // this->_head_output
//);
- // Copy to required output array
- // Hack: apply head scale here; revisit when/if I activate the head.
- // assert(this->_head_output.rows() == 1);
+ // Copy to required output array
+ // Hack: apply head scale here; revisit when/if I activate the head.
+ // assert(this->_head_output.rows() == 1);
const int final_head_array = this->_head_arrays.size() - 1;
assert(this->_head_arrays[final_head_array].rows() == 1);
for (int s = 0; s < num_frames; s++)
- this->_core_dsp_output[s] = this->_head_scale * this->_head_arrays[final_head_array](0, s);
+ this->_core_dsp_output[s] =
+ this->_head_scale * this->_head_arrays[final_head_array](0, s);
// Apply anti-pop
this->_anti_pop_();
}
-void wavenet::WaveNet::_set_num_frames_(const int num_frames)
-{
+void wavenet::WaveNet::_set_num_frames_(const int num_frames) {
if (num_frames == this->_num_frames)
return;
@@ -398,35 +345,33 @@ void wavenet::WaveNet::_set_num_frames_(const int num_frames)
for (int i = 0; i < this->_head_arrays.size(); i++)
this->_head_arrays[i].resize(this->_head_arrays[i].rows(), num_frames);
for (int i = 0; i < this->_layer_array_outputs.size(); i++)
- this->_layer_array_outputs[i].resize(this->_layer_array_outputs[i].rows(), num_frames);
+ this->_layer_array_outputs[i].resize(this->_layer_array_outputs[i].rows(),
+ num_frames);
this->_head_output.resize(this->_head_output.rows(), num_frames);
-
+
for (int i = 0; i < this->_layer_arrays.size(); i++)
this->_layer_arrays[i].set_num_frames_(num_frames);
- //this->_head.set_num_frames_(num_frames);
+ // this->_head.set_num_frames_(num_frames);
this->_num_frames = num_frames;
}
-void wavenet::WaveNet::_anti_pop_()
-{
+void wavenet::WaveNet::_anti_pop_() {
+ if (this->_anti_pop_countdown >= this->_anti_pop_ramp)
+ return;
+ const float slope = 1.0f / float(this->_anti_pop_ramp);
+ for (int i = 0; i < this->_core_dsp_output.size(); i++) {
if (this->_anti_pop_countdown >= this->_anti_pop_ramp)
- return;
- const float slope = 1.0f / float(this->_anti_pop_ramp);
- for (int i = 0; i < this->_core_dsp_output.size(); i++)
- {
- if (this->_anti_pop_countdown >= this->_anti_pop_ramp)
- break;
- const float gain = std::max(slope * float(this->_anti_pop_countdown), 0.0f);
- this->_core_dsp_output[i] *= gain;
- this->_anti_pop_countdown++;
- }
+ break;
+ const float gain = std::max(slope * float(this->_anti_pop_countdown), 0.0f);
+ this->_core_dsp_output[i] *= gain;
+ this->_anti_pop_countdown++;
+ }
}
-void wavenet::WaveNet::_reset_anti_pop_()
-{
- // You need the "real" receptive field, not the buffers.
- long receptive_field = 1;
- for (int i = 0; i < this->_layer_arrays.size(); i++)
- receptive_field += this->_layer_arrays[i].get_receptive_field();
- this->_anti_pop_countdown = -receptive_field;
+void wavenet::WaveNet::_reset_anti_pop_() {
+ // You need the "real" receptive field, not the buffers.
+ long receptive_field = 1;
+ for (int i = 0; i < this->_layer_arrays.size(); i++)
+ receptive_field += this->_layer_arrays[i].get_receptive_field();
+ this->_anti_pop_countdown = -receptive_field;
}
diff --git a/NeuralAmpModeler/dsp/wavenet.h b/NeuralAmpModeler/dsp/wavenet.h
@@ -3,253 +3,205 @@
#include <string>
#include <vector>
-#include <Eigen/Dense>
#include "json.hpp"
+#include <Eigen/Dense>
#include "dsp.h"
-
namespace wavenet {
- // Rework the initialization API slightly. Merge w/ dsp.h later.
- class _DilatedConv : public Conv1D {
- public:
- _DilatedConv(
- const int in_channels,
- const int out_channels,
- const int kernel_size,
- const int bias,
- const int dilation
- );
- };
-
- class _Layer {
- public:
- _Layer(
- const int condition_size,
- const int channels,
- const int kernel_size,
- const int dilation,
- const std::string activation,
- const bool gated
- ) :
- _activation(activation),
- _gated(gated),
- _conv(channels, gated ? 2 * channels : channels, kernel_size, true, dilation),
- _input_mixin(condition_size, gated ? 2 * channels : channels, false),
- _1x1(channels, channels, true)
- {};
- void set_params_(
- std::vector<float>::iterator& params
- );
- // :param `input`: from previous layer
- // :param `output`: to next layer
- void process_(
- const Eigen::MatrixXf& input,
- const Eigen::MatrixXf& condition,
- Eigen::MatrixXf& head_input,
- Eigen::MatrixXf& output,
- const long i_start,
- const long j_start
- );
- void set_num_frames_(const int num_frames);
- int get_channels() const { return this->_conv.get_in_channels(); };
- int get_dilation() const { return this->_conv.get_dilation(); };
- int get_kernel_size() const { return this->_conv.get_kernel_size(); };
- private:
- // The dilated convolution at the front of the block
- _DilatedConv _conv;
- // Input mixin
- Conv1x1 _input_mixin;
- // The post-activation 1x1 convolution
- Conv1x1 _1x1;
- // The internal state
- Eigen::MatrixXf _z;
-
- const std::string _activation;
- const bool _gated;
- };
-
- class LayerArrayParams {
- public:
- LayerArrayParams(
- const int input_size_,
- const int condition_size_,
- const int head_size_,
- const int channels_,
- const int kernel_size_,
- const std::vector<int>& dilations_,
- const std::string activation_,
- const bool gated_,
- const bool head_bias_
- ) :
- input_size(input_size_),
- condition_size(condition_size_),
- head_size(head_size_),
- channels(channels_),
- kernel_size(kernel_size_),
- activation(activation_),
- gated(gated_),
- head_bias(head_bias_)
- {
- for (int i = 0; i < dilations_.size(); i++)
- this->dilations.push_back(dilations_[i]);
- };
-
- const int input_size;
- const int condition_size;
- const int head_size;
- const int channels;
- const int kernel_size;
- std::vector<int> dilations;
- const std::string activation;
- const bool gated;
- const bool head_bias;
- };
-
- // An array of layers with the same channels, kernel sizes, activations.
- class _LayerArray {
- public:
- _LayerArray(
- const int input_size,
- const int condition_size,
- const int head_size,
- const int channels,
- const int kernel_size,
- const std::vector<int>& dilations,
- const std::string activation,
- const bool gated,
- const bool head_bias
- );
-
- void advance_buffers_(const int num_frames);
-
- // Preparing for frames:
- // Rewind buffers if needed
- // Shift index to prepare
- //
- void prepare_for_frames_(const int num_frames);
-
- // All arrays are "short".
- void process_(
- const Eigen::MatrixXf& layer_inputs, // Short
- const Eigen::MatrixXf& condition, // Short
- Eigen::MatrixXf& layer_outputs, // Short
- Eigen::MatrixXf& head_inputs, // Sum up on this.
- Eigen::MatrixXf& head_outputs // post head-rechannel
- );
- void set_num_frames_(const int num_frames);
- void set_params_(std::vector<float>::iterator& it);
-
- long get_receptive_field() const;
-
- private:
- long _buffer_start;
- // The rechannel before the layers
- Conv1x1 _rechannel;
-
- // Buffers in between layers.
- // buffer [i] is the input to layer [i].
- // the last layer outputs to a short array provided by outside.
- std::vector<Eigen::MatrixXf> _layer_buffers;
- // The layer objects
- std::vector<_Layer> _layers;
-
- // Rechannel for the head
- Conv1x1 _head_rechannel;
-
- long _get_buffer_size() const {
- return this->_layer_buffers.size() > 0 ? this->_layer_buffers[0].cols() : 0;
- };
- int _get_channels() const;
- long _get_receptive_field() const;
- void _rewind_buffers_();
- };
-
- // The head module
- // [Act->Conv] x L
- class _Head {
- public:
- _Head(
- const int input_size,
- const int num_layers,
- const int channels,
- const std::string activation
- );
- void set_params_(std::vector<float>::iterator& params);
- // NOTE: the head transforms the provided input by applying a nonlinearity
- // to it in-place!
- void process_(
- Eigen::MatrixXf& inputs,
- Eigen::MatrixXf& outputs
- );
- void set_num_frames_(const int num_frames);
- private:
- int _channels;
- std::vector<Conv1x1> _layers;
- Conv1x1 _head;
- std::string _activation;
-
- // Stores the outputs of the convs *except* the last one, which goes in
- // The array `outputs` provided to .process_()
- std::vector<Eigen::MatrixXf> _buffers;
-
- // Apply the activation to the provided array, in-place
- void _apply_activation_(Eigen::MatrixXf& x);
+// Rework the initialization API slightly. Merge w/ dsp.h later.
+class _DilatedConv : public Conv1D {
+public:
+ _DilatedConv(const int in_channels, const int out_channels,
+ const int kernel_size, const int bias, const int dilation);
+};
+
+class _Layer {
+public:
+ _Layer(const int condition_size, const int channels, const int kernel_size,
+ const int dilation, const std::string activation, const bool gated)
+ : _activation(activation), _gated(gated),
+ _conv(channels, gated ? 2 * channels : channels, kernel_size, true,
+ dilation),
+ _input_mixin(condition_size, gated ? 2 * channels : channels, false),
+ _1x1(channels, channels, true){};
+ void set_params_(std::vector<float>::iterator ¶ms);
+ // :param `input`: from previous layer
+ // :param `output`: to next layer
+ void process_(const Eigen::MatrixXf &input, const Eigen::MatrixXf &condition,
+ Eigen::MatrixXf &head_input, Eigen::MatrixXf &output,
+ const long i_start, const long j_start);
+ void set_num_frames_(const int num_frames);
+ int get_channels() const { return this->_conv.get_in_channels(); };
+ int get_dilation() const { return this->_conv.get_dilation(); };
+ int get_kernel_size() const { return this->_conv.get_kernel_size(); };
+
+private:
+ // The dilated convolution at the front of the block
+ _DilatedConv _conv;
+ // Input mixin
+ Conv1x1 _input_mixin;
+ // The post-activation 1x1 convolution
+ Conv1x1 _1x1;
+ // The internal state
+ Eigen::MatrixXf _z;
+
+ const std::string _activation;
+ const bool _gated;
+};
+
+class LayerArrayParams {
+public:
+ LayerArrayParams(const int input_size_, const int condition_size_,
+ const int head_size_, const int channels_,
+ const int kernel_size_, const std::vector<int> &dilations_,
+ const std::string activation_, const bool gated_,
+ const bool head_bias_)
+ : input_size(input_size_), condition_size(condition_size_),
+ head_size(head_size_), channels(channels_), kernel_size(kernel_size_),
+ activation(activation_), gated(gated_), head_bias(head_bias_) {
+ for (int i = 0; i < dilations_.size(); i++)
+ this->dilations.push_back(dilations_[i]);
};
- // The main WaveNet model
- // Both parametric and not; difference is handled at param read-in.
- class WaveNet : public DSP {
- public:
- WaveNet(
- const std::vector<LayerArrayParams>& layer_array_params,
- const float head_scale,
- const bool with_head,
- nlohmann::json parametric,
- std::vector<float> params
- );
-
-// WaveNet(WaveNet&&) = default;
-// WaveNet& operator=(WaveNet&&) = default;
-// ~WaveNet() = default;
-
- void finalize_(const int num_frames) override;
- void set_params_(std::vector<float>& params);
- private:
- int _num_frames;
- std::vector<_LayerArray> _layer_arrays;
- // Their outputs
- std::vector<Eigen::MatrixXf> _layer_array_outputs;
- //Head _head;
-
- // Element-wise arrays:
- Eigen::MatrixXf _condition;
- // One more than total layer arrays
- std::vector<Eigen::MatrixXf> _head_arrays;
- float _head_scale;
- Eigen::MatrixXf _head_output;
-
- // Names of the params, sorted.
- // TODO move this up, ugh.
- std::vector<std::string> _param_names;
-
- void _advance_buffers_(const int num_frames);
- // Get the info from the parametric config
- void _init_parametric_(nlohmann::json& parametric);
- void _prepare_for_frames_(const int num_frames);
- // Reminder: From ._input_post_gain to ._core_dsp_output
- void _process_core_() override;
-
- // Ensure that all buffer arrays are the right size for this num_frames
- void _set_num_frames_(const int num_frames);
-
- // The net starts with random parameters inside; we need to wait for a full
- // receptive field to pass through before we can count on the output being
- // ok. This implements a gentle "ramp-up" so that there's no "pop" at the
- // start.
- long _anti_pop_countdown;
- const long _anti_pop_ramp = 4000;
- void _anti_pop_();
- void _reset_anti_pop_();
+ const int input_size;
+ const int condition_size;
+ const int head_size;
+ const int channels;
+ const int kernel_size;
+ std::vector<int> dilations;
+ const std::string activation;
+ const bool gated;
+ const bool head_bias;
+};
+
+// An array of layers with the same channels, kernel sizes, activations.
+class _LayerArray {
+public:
+ _LayerArray(const int input_size, const int condition_size,
+ const int head_size, const int channels, const int kernel_size,
+ const std::vector<int> &dilations, const std::string activation,
+ const bool gated, const bool head_bias);
+
+ void advance_buffers_(const int num_frames);
+
+ // Preparing for frames:
+ // Rewind buffers if needed
+ // Shift index to prepare
+ //
+ void prepare_for_frames_(const int num_frames);
+
+ // All arrays are "short".
+ void process_(const Eigen::MatrixXf &layer_inputs, // Short
+ const Eigen::MatrixXf &condition, // Short
+ Eigen::MatrixXf &layer_outputs, // Short
+ Eigen::MatrixXf &head_inputs, // Sum up on this.
+ Eigen::MatrixXf &head_outputs // post head-rechannel
+ );
+ void set_num_frames_(const int num_frames);
+ void set_params_(std::vector<float>::iterator &it);
+
+ long get_receptive_field() const;
+
+private:
+ long _buffer_start;
+ // The rechannel before the layers
+ Conv1x1 _rechannel;
+
+ // Buffers in between layers.
+ // buffer [i] is the input to layer [i].
+ // the last layer outputs to a short array provided by outside.
+ std::vector<Eigen::MatrixXf> _layer_buffers;
+ // The layer objects
+ std::vector<_Layer> _layers;
+
+ // Rechannel for the head
+ Conv1x1 _head_rechannel;
+
+ long _get_buffer_size() const {
+ return this->_layer_buffers.size() > 0 ? this->_layer_buffers[0].cols() : 0;
};
+ int _get_channels() const;
+ long _get_receptive_field() const;
+ void _rewind_buffers_();
+};
+
+// The head module
+// [Act->Conv] x L
+class _Head {
+public:
+ _Head(const int input_size, const int num_layers, const int channels,
+ const std::string activation);
+ void set_params_(std::vector<float>::iterator ¶ms);
+ // NOTE: the head transforms the provided input by applying a nonlinearity
+ // to it in-place!
+ void process_(Eigen::MatrixXf &inputs, Eigen::MatrixXf &outputs);
+ void set_num_frames_(const int num_frames);
+
+private:
+ int _channels;
+ std::vector<Conv1x1> _layers;
+ Conv1x1 _head;
+ std::string _activation;
+
+ // Stores the outputs of the convs *except* the last one, which goes in
+ // The array `outputs` provided to .process_()
+ std::vector<Eigen::MatrixXf> _buffers;
+
+ // Apply the activation to the provided array, in-place
+ void _apply_activation_(Eigen::MatrixXf &x);
+};
+
+// The main WaveNet model
+// Both parametric and not; difference is handled at param read-in.
+class WaveNet : public DSP {
+public:
+ WaveNet(const std::vector<LayerArrayParams> &layer_array_params,
+ const float head_scale, const bool with_head,
+ nlohmann::json parametric, std::vector<float> params);
+
+ // WaveNet(WaveNet&&) = default;
+ // WaveNet& operator=(WaveNet&&) = default;
+ // ~WaveNet() = default;
+
+ void finalize_(const int num_frames) override;
+ void set_params_(std::vector<float> ¶ms);
+
+private:
+ int _num_frames;
+ std::vector<_LayerArray> _layer_arrays;
+ // Their outputs
+ std::vector<Eigen::MatrixXf> _layer_array_outputs;
+ // Head _head;
+
+ // Element-wise arrays:
+ Eigen::MatrixXf _condition;
+ // One more than total layer arrays
+ std::vector<Eigen::MatrixXf> _head_arrays;
+ float _head_scale;
+ Eigen::MatrixXf _head_output;
+
+ // Names of the params, sorted.
+ // TODO move this up, ugh.
+ std::vector<std::string> _param_names;
+
+ void _advance_buffers_(const int num_frames);
+ // Get the info from the parametric config
+ void _init_parametric_(nlohmann::json ¶metric);
+ void _prepare_for_frames_(const int num_frames);
+ // Reminder: From ._input_post_gain to ._core_dsp_output
+ void _process_core_() override;
+
+ // Ensure that all buffer arrays are the right size for this num_frames
+ void _set_num_frames_(const int num_frames);
+
+ // The net starts with random parameters inside; we need to wait for a full
+ // receptive field to pass through before we can count on the output being
+ // ok. This implements a gentle "ramp-up" so that there's no "pop" at the
+ // start.
+ long _anti_pop_countdown;
+ const long _anti_pop_ramp = 4000;
+ void _anti_pop_();
+ void _reset_anti_pop_();
+};
}; // namespace wavenet
diff --git a/NeuralAmpModeler/resources/NeuralAmpModelerAU.h b/NeuralAmpModeler/resources/NeuralAmpModelerAU.h
@@ -8,8 +8,8 @@
#define IPLUG_AUVIEWCONTROLLER IPlugAUViewController_vNeuralAmpModeler
#define IPLUG_AUAUDIOUNIT IPlugAUAudioUnit_vNeuralAmpModeler
-#import <NeuralAmpModelerAU/IPlugAUViewController.h>
#import <NeuralAmpModelerAU/IPlugAUAudioUnit.h>
+#import <NeuralAmpModelerAU/IPlugAUViewController.h>
//! Project version number for NeuralAmpModelerAU.
FOUNDATION_EXPORT double NeuralAmpModelerAUVersionNumber;
diff --git a/NeuralAmpModeler/resources/resource.h b/NeuralAmpModeler/resources/resource.h
@@ -2,43 +2,43 @@
// Microsoft Visual C++ generated include file.
// Used by main.rc
-#define IDR_ACCELERATOR1 40000
-#define IDD_DIALOG_MAIN 40001
-#define IDD_DIALOG_PREF 40002
-#define IDI_ICON1 40003
-#define IDR_MENU1 40004
-#define ID_ABOUT 40005
-#define ID_PREFERENCES 40006
-#define ID_QUIT 40007
-#define ID_HELP 40008
-#define IDC_COMBO_AUDIO_DRIVER 40009
-#define IDC_COMBO_AUDIO_IN_DEV 40010
-#define IDC_COMBO_AUDIO_OUT_DEV 40011
-#define IDC_COMBO_AUDIO_BUF_SIZE 40012
-#define IDC_COMBO_AUDIO_SR 40013
-#define IDC_COMBO_AUDIO_IN_L 40014
-#define IDC_COMBO_AUDIO_IN_R 40015
-#define IDC_COMBO_AUDIO_OUT_R 40016
-#define IDC_COMBO_AUDIO_OUT_L 40017
-#define IDC_COMBO_MIDI_IN_DEV 40018
-#define IDC_COMBO_MIDI_OUT_DEV 40019
-#define IDC_COMBO_MIDI_IN_CHAN 40020
-#define IDC_COMBO_MIDI_OUT_CHAN 40021
-#define IDC_BUTTON_OS_DEV_SETTINGS 40022
-#define IDC_CB_MONO_INPUT 40023
-#define IDAPPLY 40024
-#define ID_LIVE_EDIT 40025
-#define ID_SHOW_DRAWN 40026
-#define ID_SHOW_FPS 40027
-#define ID_SHOW_BOUNDS 40028
+#define IDR_ACCELERATOR1 40000
+#define IDD_DIALOG_MAIN 40001
+#define IDD_DIALOG_PREF 40002
+#define IDI_ICON1 40003
+#define IDR_MENU1 40004
+#define ID_ABOUT 40005
+#define ID_PREFERENCES 40006
+#define ID_QUIT 40007
+#define ID_HELP 40008
+#define IDC_COMBO_AUDIO_DRIVER 40009
+#define IDC_COMBO_AUDIO_IN_DEV 40010
+#define IDC_COMBO_AUDIO_OUT_DEV 40011
+#define IDC_COMBO_AUDIO_BUF_SIZE 40012
+#define IDC_COMBO_AUDIO_SR 40013
+#define IDC_COMBO_AUDIO_IN_L 40014
+#define IDC_COMBO_AUDIO_IN_R 40015
+#define IDC_COMBO_AUDIO_OUT_R 40016
+#define IDC_COMBO_AUDIO_OUT_L 40017
+#define IDC_COMBO_MIDI_IN_DEV 40018
+#define IDC_COMBO_MIDI_OUT_DEV 40019
+#define IDC_COMBO_MIDI_IN_CHAN 40020
+#define IDC_COMBO_MIDI_OUT_CHAN 40021
+#define IDC_BUTTON_OS_DEV_SETTINGS 40022
+#define IDC_CB_MONO_INPUT 40023
+#define IDAPPLY 40024
+#define ID_LIVE_EDIT 40025
+#define ID_SHOW_DRAWN 40026
+#define ID_SHOW_FPS 40027
+#define ID_SHOW_BOUNDS 40028
// Next default values for new objects
//
#ifdef APSTUDIO_INVOKED
#ifndef APSTUDIO_READONLY_SYMBOLS
-#define _APS_NEXT_RESOURCE_VALUE 105
-#define _APS_NEXT_COMMAND_VALUE 40001
-#define _APS_NEXT_CONTROL_VALUE 1011
-#define _APS_NEXT_SYMED_VALUE 101
+#define _APS_NEXT_RESOURCE_VALUE 105
+#define _APS_NEXT_COMMAND_VALUE 40001
+#define _APS_NEXT_CONTROL_VALUE 1011
+#define _APS_NEXT_SYMED_VALUE 101
#endif
#endif
diff --git a/TemplateProject/TemplateProject.cpp b/TemplateProject/TemplateProject.cpp
@@ -1,21 +1,23 @@
+// clang-format off
+// Need to import these two in this order.
#include "TemplateProject.h"
#include "IPlug_include_in_plug_src.h"
+// clang-format on
#if IPLUG_EDITOR
#include "IControls.h"
#endif
-TemplateProject::TemplateProject(const InstanceInfo& info)
-: Plugin(info, MakeConfig(kNumParams, kNumPresets))
-{
+TemplateProject::TemplateProject(const InstanceInfo &info)
+ : Plugin(info, MakeConfig(kNumParams, kNumPresets)) {
GetParam(kParamGain)->InitDouble("Gain", 0., 0., 100.0, 0.01, "%");
#if IPLUG_EDITOR // http://bit.ly/2S64BDd
mMakeGraphicsFunc = [&]() {
return MakeGraphics(*this, PLUG_WIDTH, PLUG_HEIGHT, PLUG_FPS);
};
-
- mLayoutFunc = [&](IGraphics* pGraphics) {
+
+ mLayoutFunc = [&](IGraphics *pGraphics) {
const IRECT bounds = pGraphics->GetBounds();
const IRECT innerBounds = bounds.GetPadded(-10.f);
const IRECT sliderBounds = innerBounds.GetFromLeft(150).GetMidVPadded(100);
@@ -24,9 +26,12 @@ TemplateProject::TemplateProject(const InstanceInfo& info)
if (pGraphics->NControls()) {
pGraphics->GetBackgroundControl()->SetTargetAndDrawRECTs(bounds);
- pGraphics->GetControlWithTag(kCtrlTagSlider)->SetTargetAndDrawRECTs(sliderBounds);
- pGraphics->GetControlWithTag(kCtrlTagTitle)->SetTargetAndDrawRECTs(titleBounds);
- pGraphics->GetControlWithTag(kCtrlTagVersionNumber)->SetTargetAndDrawRECTs(versionBounds);
+ pGraphics->GetControlWithTag(kCtrlTagSlider)
+ ->SetTargetAndDrawRECTs(sliderBounds);
+ pGraphics->GetControlWithTag(kCtrlTagTitle)
+ ->SetTargetAndDrawRECTs(titleBounds);
+ pGraphics->GetControlWithTag(kCtrlTagVersionNumber)
+ ->SetTargetAndDrawRECTs(versionBounds);
return;
}
@@ -34,29 +39,34 @@ TemplateProject::TemplateProject(const InstanceInfo& info)
pGraphics->AttachCornerResizer(EUIResizerMode::Size, true);
pGraphics->LoadFont("Roboto-Regular", ROBOTO_FN);
pGraphics->AttachPanelBackground(COLOR_LIGHT_GRAY);
- pGraphics->AttachControl(new IVSliderControl(sliderBounds, kParamGain), kCtrlTagSlider);
- pGraphics->AttachControl(new ITextControl(titleBounds, "TemplateProject", IText(30)), kCtrlTagTitle);
+ pGraphics->AttachControl(new IVSliderControl(sliderBounds, kParamGain),
+ kCtrlTagSlider);
+ pGraphics->AttachControl(
+ new ITextControl(titleBounds, "TemplateProject", IText(30)),
+ kCtrlTagTitle);
WDL_String buildInfoStr;
GetBuildInfoStr(buildInfoStr, __DATE__, __TIME__);
- pGraphics->AttachControl(new ITextControl(versionBounds, buildInfoStr.Get(), DEFAULT_TEXT.WithAlign(EAlign::Far)), kCtrlTagVersionNumber);
+ pGraphics->AttachControl(
+ new ITextControl(versionBounds, buildInfoStr.Get(),
+ DEFAULT_TEXT.WithAlign(EAlign::Far)),
+ kCtrlTagVersionNumber);
};
#endif
}
#if IPLUG_EDITOR
-void TemplateProject::OnParentWindowResize(int width, int height)
-{
- if(GetUI())
+void TemplateProject::OnParentWindowResize(int width, int height) {
+ if (GetUI())
GetUI()->Resize(width, height, 1.f, false);
}
#endif
#if IPLUG_DSP
-void TemplateProject::ProcessBlock(sample** inputs, sample** outputs, int nFrames)
-{
+void TemplateProject::ProcessBlock(sample **inputs, sample **outputs,
+ int nFrames) {
const int nChans = NOutChansConnected();
const double gain = GetParam(kParamGain)->Value() / 100.;
-
+
for (int s = 0; s < nFrames; s++) {
for (int c = 0; c < nChans; c++) {
outputs[c][s] = inputs[c][s] * gain;
diff --git a/TemplateProject/TemplateProject.h b/TemplateProject/TemplateProject.h
@@ -4,33 +4,26 @@
const int kNumPresets = 1;
-enum EParams
-{
- kParamGain = 0,
- kNumParams
-};
+enum EParams { kParamGain = 0, kNumParams };
-enum ECtrlTags
-{
- kCtrlTagVersionNumber = 0,
- kCtrlTagSlider,
- kCtrlTagTitle
-};
+enum ECtrlTags { kCtrlTagVersionNumber = 0, kCtrlTagSlider, kCtrlTagTitle };
using namespace iplug;
using namespace igraphics;
-class TemplateProject final : public Plugin
-{
+class TemplateProject final : public Plugin {
public:
- TemplateProject(const InstanceInfo& info);
+ TemplateProject(const InstanceInfo &info);
#if IPLUG_EDITOR
void OnParentWindowResize(int width, int height) override;
- bool OnHostRequestingSupportedViewConfiguration(int width, int height) override { return true; }
+ bool OnHostRequestingSupportedViewConfiguration(int width,
+ int height) override {
+ return true;
+ }
#endif
-
+
#if IPLUG_DSP // http://bit.ly/2S64BDd
- void ProcessBlock(sample** inputs, sample** outputs, int nFrames) override;
+ void ProcessBlock(sample **inputs, sample **outputs, int nFrames) override;
#endif
};
diff --git a/TemplateProject/resources/TemplateProjectAU.h b/TemplateProject/resources/TemplateProjectAU.h
@@ -8,8 +8,8 @@
#define IPLUG_AUVIEWCONTROLLER IPlugAUViewController_vTemplateProject
#define IPLUG_AUAUDIOUNIT IPlugAUAudioUnit_vTemplateProject
-#import <TemplateProjectAU/IPlugAUViewController.h>
#import <TemplateProjectAU/IPlugAUAudioUnit.h>
+#import <TemplateProjectAU/IPlugAUViewController.h>
//! Project version number for TemplateProjectAU.
FOUNDATION_EXPORT double TemplateProjectAUVersionNumber;
diff --git a/TemplateProject/resources/resource.h b/TemplateProject/resources/resource.h
@@ -2,43 +2,43 @@
// Microsoft Visual C++ generated include file.
// Used by main.rc
-#define IDR_ACCELERATOR1 40000
-#define IDD_DIALOG_MAIN 40001
-#define IDD_DIALOG_PREF 40002
-#define IDI_ICON1 40003
-#define IDR_MENU1 40004
-#define ID_ABOUT 40005
-#define ID_PREFERENCES 40006
-#define ID_QUIT 40007
-#define ID_HELP 40008
-#define IDC_COMBO_AUDIO_DRIVER 40009
-#define IDC_COMBO_AUDIO_IN_DEV 40010
-#define IDC_COMBO_AUDIO_OUT_DEV 40011
-#define IDC_COMBO_AUDIO_BUF_SIZE 40012
-#define IDC_COMBO_AUDIO_SR 40013
-#define IDC_COMBO_AUDIO_IN_L 40014
-#define IDC_COMBO_AUDIO_IN_R 40015
-#define IDC_COMBO_AUDIO_OUT_R 40016
-#define IDC_COMBO_AUDIO_OUT_L 40017
-#define IDC_COMBO_MIDI_IN_DEV 40018
-#define IDC_COMBO_MIDI_OUT_DEV 40019
-#define IDC_COMBO_MIDI_IN_CHAN 40020
-#define IDC_COMBO_MIDI_OUT_CHAN 40021
-#define IDC_BUTTON_OS_DEV_SETTINGS 40022
-#define IDC_CB_MONO_INPUT 40023
-#define IDAPPLY 40024
-#define ID_LIVE_EDIT 40025
-#define ID_SHOW_DRAWN 40026
-#define ID_SHOW_FPS 40027
-#define ID_SHOW_BOUNDS 40028
+#define IDR_ACCELERATOR1 40000
+#define IDD_DIALOG_MAIN 40001
+#define IDD_DIALOG_PREF 40002
+#define IDI_ICON1 40003
+#define IDR_MENU1 40004
+#define ID_ABOUT 40005
+#define ID_PREFERENCES 40006
+#define ID_QUIT 40007
+#define ID_HELP 40008
+#define IDC_COMBO_AUDIO_DRIVER 40009
+#define IDC_COMBO_AUDIO_IN_DEV 40010
+#define IDC_COMBO_AUDIO_OUT_DEV 40011
+#define IDC_COMBO_AUDIO_BUF_SIZE 40012
+#define IDC_COMBO_AUDIO_SR 40013
+#define IDC_COMBO_AUDIO_IN_L 40014
+#define IDC_COMBO_AUDIO_IN_R 40015
+#define IDC_COMBO_AUDIO_OUT_R 40016
+#define IDC_COMBO_AUDIO_OUT_L 40017
+#define IDC_COMBO_MIDI_IN_DEV 40018
+#define IDC_COMBO_MIDI_OUT_DEV 40019
+#define IDC_COMBO_MIDI_IN_CHAN 40020
+#define IDC_COMBO_MIDI_OUT_CHAN 40021
+#define IDC_BUTTON_OS_DEV_SETTINGS 40022
+#define IDC_CB_MONO_INPUT 40023
+#define IDAPPLY 40024
+#define ID_LIVE_EDIT 40025
+#define ID_SHOW_DRAWN 40026
+#define ID_SHOW_FPS 40027
+#define ID_SHOW_BOUNDS 40028
// Next default values for new objects
//
#ifdef APSTUDIO_INVOKED
#ifndef APSTUDIO_READONLY_SYMBOLS
-#define _APS_NEXT_RESOURCE_VALUE 105
-#define _APS_NEXT_COMMAND_VALUE 40001
-#define _APS_NEXT_CONTROL_VALUE 1011
-#define _APS_NEXT_SYMED_VALUE 101
+#define _APS_NEXT_RESOURCE_VALUE 105
+#define _APS_NEXT_COMMAND_VALUE 40001
+#define _APS_NEXT_CONTROL_VALUE 1011
+#define _APS_NEXT_SYMED_VALUE 101
#endif
#endif
diff --git a/format.bash b/format.bash
@@ -0,0 +1,15 @@
+#!/bin/bash
+# Apply project formatting (i.e. clang-format with LLVM style)
+#
+# Usage:
+# $ bash format.bash
+
+echo "Formatting..."
+
+git ls-files "*.h" "*.cpp" | xargs clang-format --style=llvm -i
+
+echo "Formatting complete!"
+echo "You can stage all of the files using:"
+echo ""
+echo ' git ls-files "*.h" "*.cpp" | xargs git add'
+echo ""
+\ No newline at end of file
