commit 790d7de6bdfcb1de60a27b87125ea525fe17b22e
parent d8dd701eebbbf9dc7e2f36be0a6907529f4515ed
Author: Steven Atkinson <[email protected]>
Date: Fri, 27 Jan 2023 08:28:52 -0800
Revert "added a secondary method get_dsp(...) and a struct to handle the data (#32)" (#41)
This reverts commit d8dd701eebbbf9dc7e2f36be0a6907529f4515ed.
Diffstat:
3 files changed, 17 insertions(+), 51 deletions(-)
diff --git a/NeuralAmpModeler/.editorconfig b/NeuralAmpModeler/.editorconfig
@@ -1,9 +0,0 @@
-# EditorConfig is awesome: https://EditorConfig.org
-
-# top-most EditorConfig file
-root = true
-
-# Unix-style newlines with a newline ending every file
-[*]
-indent_style = space
-indent_size = 2
-\ No newline at end of file
diff --git a/NeuralAmpModeler/dsp/dsp.h b/NeuralAmpModeler/dsp/dsp.h
@@ -11,7 +11,6 @@
#include <Eigen/Dense>
#include "IPlugConstants.h"
-#include "json.hpp"
enum EArchitectures
{
@@ -362,23 +361,13 @@ namespace convnet {
// Utilities ==================================================================
// Implemented in get_dsp.cpp
-struct dspData {
- std::string version;
- std::string architecture;
- nlohmann::json config;
- std::vector<float> params;
-};
-
// Verify that the config that we are building our model from is supported by
// this plugin version.
void verify_config_version(const std::string version);
// Takes the directory, finds the required files, and uses them to instantiate
-// an instance of DSP. Also returns an dspData struct that holds the data of the model.
-std::unique_ptr<DSP> get_dsp(const std::filesystem::path dirname, dspData& returnedConfig);
-
-//Instantiates a DSP object from dsp_config struct.
-std::unique_ptr<DSP> get_dsp(dspData& conf);
+// an instance of DSP.
+std::unique_ptr<DSP> get_dsp(const std::filesystem::path dirname);
// Hard-coded model:
std::unique_ptr<DSP> get_hard_dsp();
diff --git a/NeuralAmpModeler/dsp/get_dsp.cpp b/NeuralAmpModeler/dsp/get_dsp.cpp
@@ -16,7 +16,7 @@ void verify_config_version(const std::string version)
throw std::runtime_error("Unsupported config version");
}
-std::unique_ptr<DSP> get_dsp(const std::filesystem::path dirname, dspData& returnedConfig)
+std::unique_ptr<DSP> get_dsp(const std::filesystem::path dirname)
{
const std::filesystem::path config_filename = dirname / std::filesystem::path("config.json");
if (!std::filesystem::exists(config_filename))
@@ -26,32 +26,15 @@ std::unique_ptr<DSP> get_dsp(const std::filesystem::path dirname, dspData& retur
i >> j;
verify_config_version(j["version"]);
- returnedConfig.version = j["version"];
- returnedConfig.architecture = j["architecture"];
- returnedConfig.config = j["config"];
- returnedConfig.params = numpy_util::load_to_vector(dirname / std::filesystem::path("weights.npy"));
-
- /*Copy to a new dsp_config object for get_dsp below,
- since not sure if params actually get modified as being non-const references on some
- model constructors inside get_dsp(dsp_config& conf).
- We need to return unmodified version of dsp_config via returnedConfig.*/
- dspData conf = returnedConfig;
-
- return get_dsp(conf);
-}
-
-std::unique_ptr<DSP> get_dsp(dspData& conf) {
-
- verify_config_version(conf.version);
-
- auto architecture = conf.architecture;
- nlohmann::json config = conf.config;
+ auto architecture = j["architecture"];
+ nlohmann::json config = j["config"];
if (architecture == "Linear")
{
const int receptive_field = config["receptive_field"];
const bool _bias = config["bias"];
- return std::make_unique<Linear>(receptive_field, _bias, conf.params);
+ std::vector<float> params = numpy_util::load_to_vector(dirname / std::filesystem::path("weights.npy"));
+ return std::make_unique<Linear>(receptive_field, _bias, params);
}
else if (architecture == "ConvNet")
{
@@ -61,22 +44,25 @@ std::unique_ptr<DSP> get_dsp(dspData& conf) {
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, conf.params);
+ std::vector<float> params = numpy_util::load_to_vector(dirname / std::filesystem::path("weights.npy"));
+ 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, conf.params, json);
+ std::vector<float> params = numpy_util::load_to_vector(dirname / std::filesystem::path("weights.npy"));
+ 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, conf.params, config["parametric"]);
+ std::vector<float> params = numpy_util::load_to_vector(dirname / std::filesystem::path("weights.npy"));
+ return std::make_unique<lstm::LSTM>(num_layers, input_size, hidden_size, params, config["parametric"]);
}
else if (architecture == "WaveNet" || architecture == "CatWaveNet")
{
@@ -102,6 +88,7 @@ std::unique_ptr<DSP> get_dsp(dspData& conf) {
}
const bool with_head = config["head"] == NULL;
const float head_scale = config["head_scale"];
+ std::vector<float> params = numpy_util::load_to_vector(dirname / std::filesystem::path("weights.npy"));
// 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{};
@@ -110,8 +97,8 @@ std::unique_ptr<DSP> get_dsp(dspData& conf) {
head_scale,
with_head,
parametric_json,
- conf.params
- );
+ params
+ );
}
else
{
