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42 lines
1.2 KiB
42 lines
1.2 KiB
5 months ago
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import torch
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import torch.nn as nn
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import torch.optim as optim
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import torch.nn.functional as F
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import torchvision
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import matplotlib.pyplot as plt
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import numpy as np
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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class CNN(nn.Module):
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def __init__(self):
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super(CNN, self).__init__()
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self.conv1 = nn.Sequential(
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nn.Conv2d(1, 16, 5, 1, 2),
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nn.ReLU(),
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nn.MaxPool2d(2)
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)
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self.conv2 = nn.Sequential(
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nn.Conv2d(16, 32, 5, 1, 2),
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nn.ReLU(),
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nn.MaxPool2d(2)
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)
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self.conv3 = nn.Sequential(
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nn.Conv2d(32, 64, 5, 1, 2),
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nn.ReLU(),
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nn.MaxPool2d(2)
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)
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self.conv4 = nn.Sequential(
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nn.Conv2d(64, 32, 5, 1, 2),
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nn.ReLU(),
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nn.MaxPool2d(2)
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)
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self.out = nn.Linear(32, 10) # 确保输出类别数正确
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def forward(self, x):
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x = self.conv1(x).to(device) # 将数据迁移到GPU
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x = self.conv2(x).to(device)
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x=self.conv3(x).to(device)
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x = self.conv4(x).to(device)
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x = x.view(x.size(0), -1).to(device)
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x = self.out(x).to(device)
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return x
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