commit c39a273e022b12c561b15049c3f29d76c78400b6
parent 5c16c76c7bdbced07633d7d988e348ff17033e97
Author: Steven Atkinson <steven@atkinson.mn>
Date: Sat, 22 Apr 2023 18:09:36 -0700
Metadata in easy_colab.ipynb (#203)
* STart on metadata for GUI
* Add pydantic
* Pin auraloss to 0.3.0
* Metadata in GUI trainer
* User metadata
* Metadata into easy-colab.ipynb
* Update easy_colab.ipynb
Diffstat:
2 files changed, 78 insertions(+), 1736 deletions(-)
diff --git a/bin/train/easy_colab.ipynb b/bin/train/easy_colab.ipynb
@@ -24,12 +24,12 @@
"## Steps:\n",
"1. Get your data\n",
"2. Installation\n",
- "3. Train!\n",
- "4. Check the results and download your model"
+ "3. Enter metadata\n",
+ "4. Train!\n",
+ "5. Check the results and download your model"
]
},
{
- "attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "5CQleTk7GJV8"
@@ -64,25 +64,82 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "vYQIpWr5EYRb",
- "outputId": "9099af59-62ae-45b2-8cb6-415db054a73a"
+ "id": "vYQIpWr5EYRb"
},
"outputs": [],
"source": [
"!pip install git+https://github.com/sdatkinson/neural-amp-modeler.git@main\n",
"\n",
- "from nam.train.colab import run\n",
+ "from nam.train.colab import run as _run\n",
+ "run = _run\n",
"%load_ext tensorboard"
]
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "id": "7tRCyI_YjZjj"
+ },
+ "source": [
+ "## Step 3: Enter metadata\n",
+ "Tell us about what you're modeling!"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "cellView": "form",
+ "id": "zrXbQY7vjZjk"
+ },
+ "outputs": [],
+ "source": [
+ "from functools import partial\n",
+ "\n",
+ "import ipywidgets as widgets\n",
+ "from nam.models.metadata import GearType, ToneType, UserMetadata\n",
+ "#@markdown NAM name\n",
+ "name = \"My model\" #@param {type:\"string\"}\n",
+ "#@markdown Modeled by:\n",
+ "modeled_by = \"Your name\" #@param {type:\"string\"}\n",
+ "#@markdown Gear make:\n",
+ "gear_make = \"GearCo\" #@param {type:\"string\"}\n",
+ "#@markdown Gear model:\n",
+ "gear_model = \"GearAmp\" #@param {type:\"string\"}\n",
+ "#@markdown Gear type:\n",
+ "# This needs to be a literal. You need to change it by hand if you change the enum!\n",
+ "gear_type = \"Pick from: amp, pedal, amp_cab, amp_pedal_cab, preamp, studio\" #@param {type:\"string\"}\n",
+ "#@markdown Tone type:\n",
+ "tone_type = \"Pick from: clean, overdrive, crunch, hi_gain, fuzz\" #@param {type:\"string\"}\n",
+ "\n",
+ "def _verbose_enum(E, val):\n",
+ " try:\n",
+ " return E(val)\n",
+ " except ValueError as e:\n",
+ " raise ValueError(\n",
+ " str(e) \n",
+ " + \"\\nValid choices are: \" \n",
+ " + \", \".join(list(x.value for x in E))\n",
+ " )\n",
+ "\n",
+ "user_metadata = UserMetadata(\n",
+ " name=name, \n",
+ " modeled_by=modeled_by, \n",
+ " gear_make=gear_make, \n",
+ " gear_model=gear_model, \n",
+ " gear_type=_verbose_enum(GearType, gear_type.lower()), \n",
+ " tone_type=_verbose_enum(ToneType, tone_type.lower())\n",
+ ")\n",
+ "run = partial(_run, user_metadata=user_metadata)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "WVkBZg3-jZjl"
+ },
"source": [
- "## Step 3: Train!\n",
+ "## Step 4: Train!\n",
"Here we go!\n",
"\n",
"🕙Training will go through 100 epochs and take just over 10 minutes.🕙\n",
@@ -101,28 +158,25 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {},
+ "metadata": {
+ "id": "xOzo3NxqjZjl"
+ },
"outputs": [],
"source": [
"%tensorboard --logdir /content/lightning_logs\n",
"run(\n",
" epochs=100,\n",
" architecture=\"standard\" # standard, lite, feather\n",
- ")\n",
- "# Psst! Curious how it's going?\n",
- "# You can look under lightning_logs/version_0/checkpoints to see it saving its progress.\n",
- "# Look for the number after \"ESR\" to go down. It will start around 1.0. 0.1 is ok, and \n",
- "# 0.01 is really good. Anything higher than 0.1 is probably not great."
+ ")"
]
},
{
- "attachments": {},
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"metadata": {
"id": "823KJ_L0Rchp"
},
"source": [
- "## Step 4: Check the results and download your model\n",
+ "## Step 5: Check the results and download your model\n",
"We're done!\n",
"\n",
"Have a look at the plot above to see how your model compares to the real gear you're modeling.\n",
@@ -138,7 +192,6 @@
"metadata": {
"accelerator": "GPU",
"colab": {
- "name": "colab.ipynb",
"provenance": []
},
"gpuClass": "standard",
@@ -164,1722 +217,8 @@
"interpreter": {
"hash": "920df60c69944ba95f8c12adb41fedfdc8090c370a20d39253c7705973dd37db"
}
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diff --git a/nam/train/colab.py b/nam/train/colab.py
@@ -10,6 +10,7 @@ Hide the mess in Colab to make things look pretty for users.
from pathlib import Path
from typing import Optional, Tuple
+from ..models.metadata import UserMetadata
from ._version import Version
from .core import train
@@ -66,6 +67,7 @@ def run(
lr: float = 0.004,
lr_decay: float = 0.007,
seed: Optional[int] = 0,
+ user_metadata: Optional[UserMetadata] = None,
):
"""
:param epochs: How amny epochs we'll train for.
@@ -96,5 +98,5 @@ def run(
print("Exporting your model...")
model_export_outdir = _get_valid_export_directory()
model_export_outdir.mkdir(parents=True, exist_ok=False)
- model.net.export(model_export_outdir)
+ model.net.export(model_export_outdir, user_metadata=user_metadata)
print(f"Model exported to {model_export_outdir}. Enjoy!")
