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130 lines
2.8 KiB
130 lines
2.8 KiB
3 years ago
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 3.10 多层感知机的简洁实现"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.4.1\n"
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]
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}
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],
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"source": [
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"import torch\n",
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"from torch import nn\n",
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"from torch.nn import init\n",
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"import numpy as np\n",
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"import sys\n",
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"sys.path.append(\"..\") \n",
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"import d2lzh_pytorch as d2l\n",
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"\n",
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"print(torch.__version__)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 3.10.1 定义模型"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"num_inputs, num_outputs, num_hiddens = 784, 10, 256\n",
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" \n",
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"net = nn.Sequential(\n",
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" d2l.FlattenLayer(),\n",
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" nn.Linear(num_inputs, num_hiddens),\n",
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" nn.ReLU(),\n",
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" nn.Linear(num_hiddens, num_outputs), \n",
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" )\n",
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" \n",
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"for params in net.parameters():\n",
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" init.normal_(params, mean=0, std=0.01)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 3.10.2 读取数据并训练模型"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"epoch 1, loss 0.0031, train acc 0.703, test acc 0.757\n",
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"epoch 2, loss 0.0019, train acc 0.824, test acc 0.822\n",
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"epoch 3, loss 0.0016, train acc 0.845, test acc 0.825\n",
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"epoch 4, loss 0.0015, train acc 0.855, test acc 0.811\n",
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"epoch 5, loss 0.0014, train acc 0.865, test acc 0.846\n"
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]
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}
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],
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"source": [
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"batch_size = 256\n",
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"train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n",
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"loss = torch.nn.CrossEntropyLoss()\n",
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"\n",
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"optimizer = torch.optim.SGD(net.parameters(), lr=0.5)\n",
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"\n",
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"num_epochs = 5\n",
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"d2l.train_ch3(net, train_iter, test_iter, loss, num_epochs, batch_size, None, None, optimizer)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python [default]",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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