質問編集履歴
4
補足追記
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RuntimeError: Input type (torch.cuda.FloatTensor) and weight type (torch.FloatTensor) should be the same
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```
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modelはGPUに乗せており、printでも確認できました。このエラーの理由も教えていただきたいです。
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modelはGPUに乗せており、printでも確認できました。このエラーの理由も教えていただきたいです。
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-----------補足追加----------------
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以下が全体のコードです。
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ModuleListからリストに変え、ZFnetを使ったものです。
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```Python
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import 同様
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class AlexNet(nn.Module):
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//最初のコードと同様。文字数制限にて省略
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//self.layersをModuleListからListに変更
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self.layers = [
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self.layer1,
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self.layer2,
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self.layer3,
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self.layer4,
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self.layer5,
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self.layer6,
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self.layer7,
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self.layer8,
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]
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def forward(self, x):
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同様
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class ZFNet(AlexNet):
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同様
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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net = ZFNet()
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net = net.to(device)
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torchsummary.summary(net, input_size=(3, 224, 224))
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```
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3
エラー詳細追記
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```
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```bash
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Traceback (most recent call last):
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File "/home/〇〇/workspace/machineLearning/popularModel/alexNet.py", line 824, in <module>
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summary(net, input_size=(3, 224, 224))
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File "/home/〇〇/.local/share/virtualenvs/machineLearning-WvLHzLrB/lib/python3.8/site-packages/torchsummary/torchsummary.py", line 72, in summary
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model(*x)
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File "/home/〇〇/.local/share/virtualenvs/machineLearning-WvLHzLrB/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
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result = self.forward(*input, **kwargs)
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File "/home/〇〇/workspace/machineLearning/popularModel/alexNet.py", line 161, in forward
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x = layer(x)
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File "/home/〇〇/.local/share/virtualenvs/machineLearning-WvLHzLrB/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
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result = self.forward(*input, **kwargs)
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File "/home/〇〇/.local/share/virtualenvs/machineLearning-WvLHzLrB/lib/python3.8/site-packages/torch/nn/modules/container.py", line 119, in forward
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input = module(input)
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File "/home/〇〇/.local/share/virtualenvs/machineLearning-WvLHzLrB/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
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result = self.forward(*input, **kwargs)
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File "/home/〇〇/.local/share/virtualenvs/machineLearning-WvLHzLrB/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 399, in forward
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return self._conv_forward(input, self.weight, self.bias)
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File "/home/〇〇/.local/share/virtualenvs/machineLearning-WvLHzLrB/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 395, in _conv_forward
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return F.conv2d(input, weight, bias, self.stride,
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RuntimeError: Input type (torch.cuda.FloatTensor) and weight type (torch.FloatTensor) should be the same
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```
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2
補足
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torchsummary.summary(net, input_size=(3, 224, 224))
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```
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```
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```bash
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----------------------------------------------------------------
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Layer (type) Output Shape Param #
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================================================================
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Params size (MB): 472.91
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Estimated Total Size (MB): 491.39
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----------------------------------------------------------------
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```
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```
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＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝補足＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝
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nn.ModuleListを通常のリストとした場合は正しく動いたのですが、以下のように新しいモデルを継承により作った場合に、エラーが発生しました。
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```Python
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class ZFNet(AlexNet):
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def __init__(self, conv_channels_list=[96, 256, 384, 384, 256]):
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super(ZFNet, self).__init__()
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self.layer1 = nn.Sequential(
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nn.Conv2d(
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in_channels=3,
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out_channels=conv_channels_list[0],
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kernel_size=7,
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stride=2,
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padding=2
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),
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nn.MaxPool2d(kernel_size=3, stride=2),
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nn.LocalResponseNorm(size=5, k=2),
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nn.ReLU(inplace=True)
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)
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```
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```bash
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RuntimeError: Input type (torch.cuda.FloatTensor) and weight type (torch.FloatTensor) should be the same
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```
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modelはGPUに乗せており、printでも確認できました。このエラーの理由も教えていただきたいです。
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1
誤字の訂正
title
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nn.Softmax(dim=1)
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self.
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self.layers = nn.ModuleList([
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self.layer1,
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self.layer2,
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self.layer3,
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])
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def forward(self, x):
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for layer in self.
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for layer in self.layers:
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x = layer(x)
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return x
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