Question

我正在这个BRATS Unet的main.py上工作

https://github.com/pykao/Modified-3D-UNet-Pytorch/blob/master/main.py

# create your optimizer
print ("Creating Optimizer")
##optimizer = optim.adam(net.parameteres(), lr=)
optimizer = torch.optim.Adam(model.parameters(), lr=args.lr)
print ("Created! \n")

trainloader = torch.utils.data.DataLoader(train_idx, batch_size=2, shuffle=True)
testloader  = torch.utils.data.DataLoader(test_idx, batch_size=2, shuffle=False)

for epoch in range(2):  # loop over the dataset multiple times
    running_loss = 0.0
    for i, data in enumerate(trainloader, 0):
        print("inside for")
        # get the inputs THIS ERRORS OUT
        inputs, labels = data

        # zero the parameter gradients
        optimizer.zero_grad()

        # forward + backward + optimize
        outputs = model(inputs)
        loss = criterion(outputs, target)
        loss.backward()
        optimizer.step()

        # print statistics
        running_loss += loss.item()
        if i % 2000 == 1999:    # print every 2000 mini-batches
            print('[%d, %5d] loss: %.3f' %
                  (epoch + 1, i + 1, running_loss / 2000))
            running_loss = 0.0

print('Finished Training')

我得到以下输出：

Creating Optimizer
Created!

inside for
Traceback (most recent call last):
  File "main.py", line 109, in <module>
    outputs = model(inputs)
  File "/home/MAHEUNIX/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/mnt/c/Users/MAHE/Modified Unet3D Master -TestRun/model.py", line 99, in forward
    out = self.conv3d_c1_1(x)
  File "/home/MAHEUNIX/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/MAHEUNIX/anaconda3/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 448, in forward
    self.padding, self.dilation, self.groups)
RuntimeError: Expected 5-dimensional input for 5-dimensional weight [16, 4, 3, 3, 3], but got 0-dimensional input of size [] instead

我不熟悉PyTorch，因此Trainloader，testloader可能未正确使用。请假设您帮我的时候我不太了解。谢谢。

新错误：

Traceback (most recent call last):
  File "/mnt/c/Users/MAHE/Modified Unet3D Master -TestRun/main.py", line 91, in <module>
    for id, info in enumerate(trainloader,0):
  File "/home/MAHEUNIX/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 615, in __next__
    batch = self.collate_fn([self.dataset[i] for i in indices])
  File "/home/MAHEUNIX/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 615, in <listcomp>
    batch = self.collate_fn([self.dataset[i] for i in indices])
KeyError: 0

Answer 1

您应该将数据集传递给数据加载器API。因此，将train_data和test_data而不是train_idx和test_idx传递到torch.utils.data.DataLoader。

我的ADAM算法在哪里产生此尺寸错误？

1 个答案: