更新文档

doc/.gitignore

@@ -27,3 +27,4 @@ api/
 *.torchscript
 *.onnx
 tuning_logs/
+*.pb

doc/temp-tutorials/ai/pytorch-model.ipynb

@@ -0,0 +1,164 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# PyTorch 模型"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.extend([\"..\"])\n",
+    "import set_env"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from tvm_book.tools.frontends import Frontend, TrainInputConfig\n",
+    "from tvm_book.tools import display"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "pytorch 前端模型配置："
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(display.Tree(\"| \")(\"models/pytorch_demo\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "{icon}`fa-solid fa-folder-open` `pytorch_demo/` 文件夹下存在如下内容：\n",
+    "\n",
+    "- {icon}`fa-solid fa-file` `save.py` 存储 PyTorch 模型为 `resnet18.pth`\n",
+    "    ```{include} models/pytorch_demo/save.py\n",
+    "    :code: python\n",
+    "    ```\n",
+    "- {icon}`fa-solid fa-file` `resnet18.pth` 存储 PyTorch 模型结构与参数\n",
+    "- {icon}`fa-solid fa-file` `config.toml` 存储 PyTorch 模型配置信息\n",
+    "    ```{include} models/pytorch_demo/config.toml\n",
+    "    :code: toml\n",
+    "    ```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import toml\n",
+    "\n",
+    "config_path = \"models/pytorch_demo/config.toml\"\n",
+    "\n",
+    "config_path = Path(config_path) \n",
+    "config = toml.load(config_path)\n",
+    "model_type = config['model'][\"model_type\"]\n",
+    "if len(config['train_inputs']) == 1:\n",
+    "    input_config = config['train_inputs'][0]\n",
+    "if model_type == \"pytorch\":\n",
+    "    shape_dict = {input_config[\"name\"]: input_config[\"shape\"]}\n",
+    "    model = Frontend(model_type).load(f\"{config_path.parent}/{config['model']['path']}\", shape_dict=shape_dict)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import tvm\n",
+    "import tvm.relay as relay\n",
+    "from tvm.relay.build_module import bind_params_by_name\n",
+    "from tvm.ir.instrument import (\n",
+    "    PassTimingInstrument,\n",
+    "    pass_instrument,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "def get_calibration_dataset(mod, input_name):\n",
+    "    dataset = []\n",
+    "    input_shape = [int(x) for x in mod[\"main\"].checked_type.arg_types[0].shape]\n",
+    "    for i in range(5):\n",
+    "        data = np.random.uniform(size=input_shape)\n",
+    "        dataset.append({input_name: data})\n",
+    "    return dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset = get_calibration_dataset(model.mod, \"x\")\n",
+    "BASE_CFG = {\n",
+    "    \"skip_conv_layers\": [],\n",
+    "    \"skip_dense_layers\": False,\n",
+    "    \"dtype_input\": \"int8\",\n",
+    "    \"dtype_weight\": \"int8\",\n",
+    "    \"dtype_activation\": \"int32\",\n",
+    "}\n",
+    "with tvm.transform.PassContext(opt_level=3):\n",
+    "    with relay.quantize.qconfig(**BASE_CFG, calibrate_mode=\"percentile\"):\n",
+    "        qmod = relay.quantize.quantize(model.mod, params=model.params, dataset=dataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "xx",
+   "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": "3.12.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

doc/temp-tutorials/frontend/index.md

@@ -1,11 +1,9 @@
-# 前端模型
+# 前端模型(temp)
 
 ```{toctree}
 mxnet
-tensorflow-tvm/index
+tf-tvm/index
 pytorch-tvm/index
-onnx-tvm/index
-onnxscript/index
 caffe-tvm/index
 relax-fx
 ```