{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-06-17T02:29:56.329629Z",
     "start_time": "2025-06-17T02:29:53.851211Z"
    }
   },
   "source": [
    "import torch\n",
    "import torch.nn as nn"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-17T02:30:23.709542Z",
     "start_time": "2025-06-17T02:30:23.705090Z"
    }
   },
   "cell_type": "code",
   "source": [
    "x = torch.randn(3, 5, 5).unsqueeze(0)\n",
    "print(x.shape)"
   ],
   "id": "19a429395361b901",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 3, 5, 5])\n"
     ]
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-17T02:32:50.342968Z",
     "start_time": "2025-06-17T02:32:50.335771Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 请注意DW中，输入特征通道数与输出通道数是一样的\n",
    "in_channels_dw = x.shape[1]\n",
    "out_channels_dw = x.shape[1]\n",
    "# 一般来讲DW卷积的kernel size 为3\n",
    "kernel_size_dw = 3\n",
    "stride_dw = 1\n",
    "\n",
    "# DW 卷积groups参数与输入通道数一样\n",
    "dw = nn.Conv2d(in_channels_dw, out_channels_dw, kernel_size_dw, stride=stride_dw, groups=in_channels_dw)"
   ],
   "id": "23ca0000610f16a0",
   "outputs": [],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-17T02:34:22.427522Z",
     "start_time": "2025-06-17T02:34:22.369462Z"
    }
   },
   "cell_type": "code",
   "source": [
    "in_channels_pw = out_channels_dw\n",
    "out_channels_pw = 4\n",
    "kernel_size_pw = 1\n",
    "\n",
    "pw = nn.Conv2d(in_channels_pw, out_channels_pw, kernel_size_pw, stride=1)\n",
    "\n",
    "out = pw(dw(x))\n",
    "print(out.shape)"
   ],
   "id": "d0bb1304d1f98d2e",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 4, 3, 3])\n"
     ]
    }
   ],
   "execution_count": 5
  }
 ],
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