Question

import torchvision
from torch.utils.data import Dataset, DataLoader
from torch import from_numpy, tensor
import numpy as np
trans = transforms.Compose(
    [
     transforms.Resize(128),
     transforms.ToTensor()
    ])
class UBFCDataset(Dataset):

    def __init__(self):
       

        xy = np.loadtxt('/content/drive/My Drive/Subject3hr.csv')
        self.x_data = torch.from_numpy(xy[:])
        self.len = xy.shape[0]
       

    def __len__(self):
        return self.len

    def __getitem__(self, index):
        train_data_tensor = torchvision.datasets.ImageFolder("/content/drive/My Drive/Meta-rPPG-master/da", transform=trans)
        
        return train_data_tensor[index], self.x_data[index]

dataset = UBFCDataset()
dataset[0]
train_loader = DataLoader(dataset=dataset,batch_size=128,shuffle=True)

for epoch in range(2):
    for i, data in enumerate(train_loader, 0):
        # get the inputs
        inputs, labels = data
        print(inputs.shape)
        # Run your training process
        print(f'Epoch: {i} | Inputs {inputs} | Labels {labels}')

错误：

AttributeError                            Traceback (most recent call last)
<ipython-input-156-fecbaf453580> in <module>()
      4         inputs, labels = data
      5 
----> 6         print(inputs.shape)
      7         # Run your training process
      8         print(f'Epoch: {i} | Inputs {inputs} | Labels {labels}')

AttributeError: 'list' object has no attribute 'shape'

Answer 1

您假设变量类型是一个numpy数组，而实际上是一个原始列表。这是固定代码：

- name: Checkout repo  
  uses: actions/checkout@v2
  with:
    repository: 'MyOrg/MyRepo'
    ref: ${{env.CURRENT_BRANCH}}

如何找到输入张量的形状？

1 个答案: