fix bug
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8
train.py
8
train.py
@@ -16,9 +16,9 @@ test_csv = pd.read_csv(test_csv_path, header=None)
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# 提取dx, dy和标签
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dx_dy_train = train_csv.iloc[:, 0].apply(lambda x: list(map(int, x.split(','))))
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dx_dy_labels_train = train_csv.apply(lambda row: [list(map(int, row[i].split(','))) for i in range(1,10)], axis=1)
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dx_dy_labels_train = train_csv.apply(lambda row: [list(map(int, row[i].split(','))) for i in range(1,11)], axis=1)
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dx_dy_test = test_csv.iloc[:, 0].apply(lambda x: list(map(int, x.split(','))))
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dx_dy_labels_test = test_csv.apply(lambda row: [list(map(int, row[i].split(','))) for i in range(1,10)], axis=1)
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dx_dy_labels_test = test_csv.apply(lambda row: [list(map(int, row[i].split(','))) for i in range(1,11)], axis=1)
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# 转换为PyTorch Tensor
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dx_dy_train_tensor = torch.Tensor(dx_dy_train.tolist())
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@@ -53,7 +53,7 @@ class SimpleNet(nn.Module):
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super(SimpleNet, self).__init__()
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self.fc1 = nn.Linear(2, 64)
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self.fc2 = nn.Linear(64, 32)
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self.fc3 = nn.Linear(32, 18)
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self.fc3 = nn.Linear(32, 20)
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def forward(self, input_data):
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x = torch.flatten(input_data, start_dim=1)
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@@ -62,7 +62,7 @@ class SimpleNet(nn.Module):
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x = self.fc2(x)
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x = nn.ReLU()(x)
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x = self.fc3(x)
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return x.view(-1, 9, 2)
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return x.view(-1, 10, 2)
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# 初始化模型、损失函数和优化器
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model = SimpleNet()
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