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Stacktraceを追加しました
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@@ -81,7 +81,72 @@
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scheduler.step()
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print(f"epoch {str(epoch).zfill(2)}\ttrain_loss: {train_loss}\tval_loss: {val_loss}\tval_acc: {val_acc}")
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##以下出現したエラー
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85
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---------------------------------------------------------------------------
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86
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RuntimeError Traceback (most recent call last)
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87
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<ipython-input-8-2396f00cf9e1> in <module>()
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3 earlystop_counter = 0
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89
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4 for epoch in range(100):
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----> 5 train_loss = training(model, train_dataset, optimizer, loss_func)
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6 val_loss, val_acc = evaluation(model, val_dataset, loss_func)
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7
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6 frames
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<ipython-input-6-33676f519731> in training(model, dataset, optimizer, loss_func)
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96
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6 img = img.to("cuda")
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7 target = target.to("cuda")
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98
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----> 8 pred = model(img)
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9 loss = loss_func(pred, target)
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10 losses.append(loss.item())
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/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
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720 result = self._slow_forward(*input, **kwargs)
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721 else:
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--> 722 result = self.forward(*input, **kwargs)
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723 for hook in itertools.chain(
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724 _global_forward_hooks.values(),
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/usr/local/lib/python3.6/dist-packages/torchvision/models/resnet.py in forward(self, x)
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218
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219 def forward(self, x):
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--> 220 return self._forward_impl(x)
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221
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/usr/local/lib/python3.6/dist-packages/torchvision/models/resnet.py in _forward_impl(self, x)
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201 def _forward_impl(self, x):
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202 # See note [TorchScript super()]
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--> 203 x = self.conv1(x)
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204 x = self.bn1(x)
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205 x = self.relu(x)
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/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
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720 result = self._slow_forward(*input, **kwargs)
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721 else:
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--> 722 result = self.forward(*input, **kwargs)
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723 for hook in itertools.chain(
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724 _global_forward_hooks.values(),
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/usr/local/lib/python3.6/dist-packages/torch/nn/modules/conv.py in forward(self, input)
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417
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418 def forward(self, input: Tensor) -> Tensor:
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--> 419 return self._conv_forward(input, self.weight)
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420
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421 class Conv3d(_ConvNd):
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/usr/local/lib/python3.6/dist-packages/torch/nn/modules/conv.py in _conv_forward(self, input, weight)
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414 _pair(0), self.dilation, self.groups)
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415 return F.conv2d(input, weight, self.bias, self.stride,
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--> 416 self.padding, self.dilation, self.groups)
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417
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418 def forward(self, input: Tensor) -> Tensor:
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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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google colabを使ってpytorchを活用したresnet34の転移学習を上記のコードで行うとしたのですが、エラーが出てしました。どなたか解決策をご教授していただけますか？
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更新10/28
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