commit b5568563c55d3e736c7e2a353214e32304068307
parent ff5cf5387fcf774b07ba8d486f653829d38a012f
Author: Steven Atkinson <[email protected]>
Date: Sun, 7 May 2023 12:59:11 -0700
Update colab.ipynb
Fix CPU bug
Put deprecation notice
Report ESR instead of NRMSE
Diffstat:
| M | bin/train/colab.ipynb | | | 35173 | +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++-- |
1 file changed, 34705 insertions(+), 468 deletions(-)
diff --git a/bin/train/colab.ipynb b/bin/train/colab.ipynb
@@ -6,8 +6,11 @@
"id": "TC3XkMetGWtK"
},
"source": [
- "# Neural Amp Modeler (Trainer)\n",
- "This notebook allows you to train a neural amp model based on a pair of input/output WAV files that you have of the amp you want to model.\n",
+ "# Neural Amp Modeler (Trainer) [DEPRECATED]\n",
+ "\n",
+ "**This trainer is deprecated and will be removed after version 0.5.3. Instead use either `easy_colab.ipynb` or the local GUI trainer.**\n",
+ "\n",
+ "This notebook allows you to train a neural amp model based on two pairs of input/output WAV files that you have of the amp you want to model.\n",
"\n",
"**To use this notebook**:\n",
"Go to [colab.research.google.com](https://colab.research.google.com/), select the \"GitHub\" tab, and select this notebook. Or, if you've cloned the repo, you can upload it from your computer.\n",
@@ -92,11 +95,11 @@
"base_uri": "https://localhost:8080/"
},
"id": "vYQIpWr5EYRb",
- "outputId": "9099af59-62ae-45b2-8cb6-415db054a73a"
+ "outputId": "d1eb39b8-a071-474a-b4d9-876e06417cd7"
},
"outputs": [],
"source": [
- "!pip install git+https://github.com/sdatkinson/neural-amp-modeler.git@main"
+ "!pip install \"neural-amp-modeler<=0.5.3\""
]
},
{
@@ -117,7 +120,8 @@
"from torch.utils.data import DataLoader\n",
"\n",
"from nam.data import Split, init_dataset\n",
- "from nam.models import Model"
+ "from nam.models import Model\n",
+ "from nam.models.losses import esr"
]
},
{
@@ -138,7 +142,7 @@
"base_uri": "https://localhost:8080/"
},
"id": "Y6gl6RoNJ_6I",
- "outputId": "1f6166d6-87eb-4dfb-9619-3c4a4a7e5147"
+ "outputId": "6a897c88-35fa-42ef-d406-3388ae9aa85b"
},
"outputs": [],
"source": [
@@ -272,7 +276,7 @@
"base_uri": "https://localhost:8080/"
},
"id": "vyhMf0ZyM4kt",
- "outputId": "b367dbe3-624a-4e37-ce29-87b70f07424e"
+ "outputId": "0dfe094a-a278-441f-d062-ef9d1edf05b7"
},
"outputs": [],
"source": [
@@ -313,67 +317,1134 @@
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
- "height": 301,
+ "height": 269,
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},
"id": "a8WLIx33M7c6",
- "outputId": "bd57b7ae-5831-4900-c578-b4070f6a6d1a"
+ "outputId": "59d3efd1-c9d1-490b-bb53-6d22a2448027"
},
"outputs": [],
"source": [
@@ -392,7 +1463,7 @@
"base_uri": "https://localhost:8080/"
},
"id": "JzGltwwJNAkI",
- "outputId": "4e2651d1-0048-4c17-9073-b3180240b9aa"
+ "outputId": "d85bbcc6-19a6-4f82-dbdf-b801f0d9b825"
},
"outputs": [],
"source": [
@@ -403,6 +1474,7 @@
" trainer.checkpoint_callback.best_model_path,\n",
" **Model.parse_config(model_config),\n",
" )\n",
+ "model.cpu()\n",
"model.eval()"
]
},
@@ -424,14 +1496,6 @@
},
"outputs": [],
"source": [
- "def _rms(x: Union[np.ndarray, torch.Tensor]) -> float:\n",
- " if isinstance(x, np.ndarray):\n",
- " return np.sqrt(np.mean(np.square(x)))\n",
- " elif isinstance(x, torch.Tensor):\n",
- " return torch.sqrt(torch.mean(torch.square(x))).item()\n",
- " else:\n",
- " raise TypeError(type(x))\n",
- "\n",
"def plot(\n",
" model,\n",
" ds,\n",
@@ -451,7 +1515,7 @@
" plt.figure(figsize=(16, 5))\n",
" plt.plot(output[window_start:window_end], label=\"Prediction\")\n",
" plt.plot(ds.y[window_start:window_end], linestyle=\"--\", label=\"Target\")\n",
- " plt.title(f\"NRMSE={100.0 * _rms(torch.Tensor(output) - ds.y) / _rms(ds.y):2.1f}%\")\n",
+ " plt.title(f\"ESR={esr(torch.Tensor(output), ds.y):.4f}\")\n",
" plt.legend()\n",
" if savefig is not None:\n",
" plt.savefig(savefig)\n",
@@ -465,10 +1529,10 @@
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
- "height": 372
+ "height": 446
},
"id": "C_NsBdp5NQMC",
- "outputId": "3e3c1812-4520-4943-bd31-d6de579decec"
+ "outputId": "7f3020c9-62d0-4d01-9015-c018418731f8"
},
"outputs": [],
"source": [
@@ -503,7 +1567,6 @@
]
},
{
- "attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "823KJ_L0Rchp"
@@ -551,53 +1614,7 @@
},
"widgets": {
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- "06d6093b2de54471b6d8ed706a3ec134": {
- "model_module": "@jupyter-widgets/controls",
- "model_module_version": "1.5.0",
- "model_name": "DescriptionStyleModel",
- "state": {
- "_model_module": "@jupyter-widgets/controls",
- "_model_module_version": "1.5.0",
- "_model_name": "DescriptionStyleModel",
- "_view_count": null,
- "_view_module": "@jupyter-widgets/base",
- "_view_module_version": "1.2.0",
- "_view_name": "StyleView",
- "description_width": ""
- }
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- "0ca1b22f10094010b1de29208e9dc446": {
- "model_module": "@jupyter-widgets/controls",
- "model_module_version": "1.5.0",
- "model_name": "ProgressStyleModel",
- "state": {
- "_model_module": "@jupyter-widgets/controls",
- "_model_module_version": "1.5.0",
- "_model_name": "ProgressStyleModel",
- "_view_count": null,
- "_view_module": "@jupyter-widgets/base",
- "_view_module_version": "1.2.0",
- "_view_name": "StyleView",
- "bar_color": null,
- "description_width": ""
- }
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- "1b99071c17b24eb38edc8156e6ce5c82": {
- "model_module": "@jupyter-widgets/controls",
- "model_module_version": "1.5.0",
- "model_name": "DescriptionStyleModel",
- "state": {
- "_model_module": "@jupyter-widgets/controls",
- "_model_module_version": "1.5.0",
- "_model_name": "DescriptionStyleModel",
- "_view_count": null,
- "_view_module": "@jupyter-widgets/base",
- "_view_module_version": "1.2.0",
- "_view_name": "StyleView",
- "description_width": ""
- }
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- "22ddf8419783483c8f028e7864f70a01": {
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"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
@@ -649,7 +1666,22 @@
"width": "100%"
}
},
- "267c776505af4500a78055da11d048c3": {
+ "00409965d45841f78bd8a1c2e6ea0b1d": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "DescriptionStyleModel",
+ "state": {
+ "_model_module": "@jupyter-widgets/controls",
+ "_model_module_version": "1.5.0",
+ "_model_name": "DescriptionStyleModel",
+ "_view_count": null,
+ "_view_module": "@jupyter-widgets/base",
+ "_view_module_version": "1.2.0",
+ "_view_name": "StyleView",
+ "description_width": ""
+ }
+ },
+ "004aa1b753ea46469522356f33313635": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
@@ -665,52 +1697,36 @@
"bar_style": "",
"description": "",
"description_tooltip": null,
- "layout": "IPY_MODEL_c8cbf6d2083c482ca05956b1cca62d8f",
+ "layout": "IPY_MODEL_f09333fc911a455b964ae8d5e4cd87d0",
"max": 1,
"min": 0,
"orientation": "horizontal",
- "style": "IPY_MODEL_0ca1b22f10094010b1de29208e9dc446",
+ "style": "IPY_MODEL_54fb2b7d13364025bd2a4273c95edd6f",
"value": 1
}
},
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- "_model_module_version": "1.5.0",
- "_model_name": "DescriptionStyleModel",
- "_view_count": null,
- "_view_module": "@jupyter-widgets/base",
- "_view_module_version": "1.2.0",
- "_view_name": "StyleView",
- "description_width": ""
- }
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- "35a2785ec34841faa4a42740859a1787": {
+ "00910d3e7ff44819b6d3867a328e87b4": {
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"model_module_version": "1.5.0",
- "model_name": "HBoxModel",
+ "model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
- "_model_name": "HBoxModel",
+ "_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
- "_view_name": "HBoxView",
- "box_style": "",
- "children": [
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- "IPY_MODEL_bb9f87963c094647aba5a9fe9f658a7c",
- "IPY_MODEL_99d70d6c342241208b9e82b077e7992a"
- ],
- "layout": "IPY_MODEL_e8210bfbf84248c8ba908837a8d991a9"
+ "_view_name": "HTMLView",
+ "description": "",
+ "description_tooltip": null,
+ "layout": "IPY_MODEL_799ea085684b452387fe3bae7ad5f63b",
+ "placeholder": "",
+ "style": "IPY_MODEL_7c15a57de52148a891d5eaf1da4b3ddd",
+ "value": "Validation DataLoader 0: 100%"
}
},
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