cleanup

.gitignore

@@ -1,3 +1,4 @@
 /.ipynb_checkpoints/
 /__pycache__/
 /data/
+/music.safetensors

train.ipynb

@@ -1,163 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%load_ext autoreload\n",
-    "%autoreload 2\n",
-    "\n",
-    "import data\n",
-    "import show\n",
-    "import model"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "x,y = data.detaset(data.load())\n",
-    "len(x)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2",
-   "metadata": {
-    "editable": true,
-    "slideshow": {
-     "slide_type": ""
-    },
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "sample=x[420]\n",
-    "show.showSpec(sample)\n",
-    "show.playSpec(sample)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from tinygrad import nn\n",
-    "gen = model.Gen()\n",
-    "optimizer = nn.optim.AdamW(nn.state.get_parameters(gen), lr=1e-4)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "@TinyJit\n",
-    "def jit_step(X: Tensor, Y: Tensor,epoch) -> Tensor:\n",
-    "    Tensor.training = True\n",
-    "    optimizer.zero_grad()\n",
-    "    _, loss = gen.__Lcall__(X,Y,epoch)\n",
-    "    loss.backward()\n",
-    "    optimizer.step()\n",
-    "    return loss.realize()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "x_np, y_np = np.stack(x), np.stack(y)\n",
-    "x_np = np.expand_dims(x_np, axis=1)\n",
-    "y_np = np.expand_dims(y_np, axis=1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6",
-   "metadata": {
-    "editable": true,
-    "slideshow": {
-     "slide_type": ""
-    },
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "size=len(x)\n",
-    "BACH_SIZE=32\n",
-    "eshape = (BACH_SIZE, 1, 128, 216)\n",
-    "\n",
-    "for e in range(0,12):\n",
-    "    print(f\"\\n--- Starting Epoch {e} ---\\n\")\n",
-    "    l=0\n",
-    "    \n",
-    "    permutation = np.random.permutation(size)\n",
-    "    x_np = x_np[permutation]\n",
-    "    y_np = y_np[permutation]\n",
-    "    \n",
-    "    for i in range(0,size,BACH_SIZE):\n",
-    "        tx,ty=Tensor(x_np[i:i+BACH_SIZE]),Tensor(y_np[i:i+BACH_SIZE])\n",
-    "        if(tx.shape != eshape or ty.shape != eshape):\n",
-    "            continue\n",
-    "        l+=jit_step(tx,ty,e).numpy()\n",
-    "        \n",
-    "    l /= (size/BACH_SIZE)\n",
-    "    print(f\"loss of {l}\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7",
-   "metadata": {
-    "editable": true,
-    "slideshow": {
-     "slide_type": ""
-    },
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from tinygrad.nn.state import safe_save, get_state_dict\n",
-    "safe_save(get_state_dict(gen),\"music.safetensors\")"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.11"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}