Python 操作错误：Can'；t读取数据（错误的B树签名）。当我从2.hdf5文件中读取数据时，PyTorch显示此错误。怎么办？

我正在尝试在Pytorch中运行以下代码：

import numpy as np
import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data as data


class H5Dataset(data.Dataset):

    def __init__(self, trainx_path, trainy_path):

        super(H5Dataset, self).__init__()
        x_file = h5py.File(trainx_path)
        y_file = h5py.File(trainy_path)

        self.data = x_file.get('X')        
        self.target = y_file.get('y')

    def __getitem__(self, size):

      permutation1 = list(np.random.permutation(249000))  
      permutation2 = list(np.random.permutation(np.arange(249000,498000)))

      size1 = int(size/2)
      index1=list(permutation1[0:size1])
      index2=list(permutation2[0:size1])
      index = index1+index2
      labels=np.array(self.target).reshape(498000,-1)
      train_labels=labels[index]
      train_batch=[]

      for i in range(size):
          img=(self.data)[index[i]]
          train_batch.append(img)    
      train_batch=np.array(train_batch)

      return (torch.from_numpy(train_batch).float(), torch.from_numpy(train_labels).float())


    def __len__(self):
        return len(self.data)


dataset = H5Dataset('//content//drive//My Drive//E2E_1//train_x.hdf5','//content//drive//My Drive//E2E_1//train_y.hdf5')
train_loader = torch.utils.data.DataLoader(dataset, batch_size=64, shuffle=True, num_workers=2, pin_memory=False) 


class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(2, 64, kernel_size=(2,2), padding=(8,8), stride=(2,2),padding_mode='zeros')
        self.pool = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(64, 128, kernel_size=(2,2), padding=(8,8), stride=(2,2),padding_mode='zeros')
        self.fc1 = nn.Linear(32768, 500) 
        self.drop = nn.Dropout(p=0.5) 
        self.fc2 = nn.Linear(500, 1)
        self.fc3 = nn.Linear(1,1)  

    def forward(self, x):
        x = self.pool(F.relu(self.conv1(x)))
        x = F.relu(self.conv2(x))
        x = x.view(-1, 16 * 16 * 128)
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x


net = Net()
print(net)

import torch.optim as optim

criterion = nn.BCELoss()
optimizer = optim.Adam(net.parameters(), lr=0.0001)

for epoch in range(2):  # loop over the dataset multiple times

    running_loss = 0.0
    for i, data in enumerate(train_loader, 0):
        # get the inputs; data is a list of [inputs, labels]
        inputs, labels = data

        # zero the parameter gradients
        optimizer.zero_grad()

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

        # print statistics
        running_loss += loss.item()
        if i % 32 == 31:    # print every 32 mini-batches
            print('[%d, %5d] loss: %.3f' %
                  (epoch + 1, i + 1, running_loss / 32))
            running_loss = 0.0


print('Finished Training')

但是我得到了以下错误。我的train_x和train_y数据存储在两个单独的.hdf5文件中，当我在训练时尝试读取它们时，会弹出此错误。请告诉我必须做些什么改变

OSError                                   Traceback (most recent call last)
<ipython-input-8-a8f66fac8b5c> in <module>()
      2 
      3     running_loss = 0.0
----> 4     for i, data in enumerate(train_loader, 0):
      5         # get the inputs; data is a list of [inputs, labels]
      6         inputs, labels = data

3 frames
/usr/local/lib/python3.6/dist-packages/torch/_utils.py in reraise(self)
    392             # (https://bugs.python.org/issue2651), so we work around it.
    393             msg = KeyErrorMessage(msg)
--> 394         raise self.exc_type(msg)

OSError: Caught OSError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
    data = fetcher.fetch(index)
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "<ipython-input-5-0df8cfc88081>", line 37, in __getitem__
    img=(self.data)[index[i]]
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
  File "/usr/local/lib/python3.6/dist-packages/h5py/_hl/dataset.py", line 573, in __getitem__
    self.id.read(mspace, fspace, arr, mtype, dxpl=self._dxpl)
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
  File "h5py/h5d.pyx", line 182, in h5py.h5d.DatasetID.read
  File "h5py/_proxy.pyx", line 130, in h5py._proxy.dset_rw
  File "h5py/_proxy.pyx", line 84, in h5py._proxy.H5PY_H5Dread
OSError: Can't read data (wrong B-tree signature)

OSError回溯（最近一次调用）
在（）
2.
3运行损耗=0.0
---->4对于i，枚举中的数据（列装载机，0）：
5#获取输入；数据是[输入、标签]列表
6输入，标签=数据
3帧
/usr/local/lib/python3.6/dist-packages/torch//u utils.py in reraise（self）
392             # (https://bugs.python.org/issue2651)，所以我们努力解决这个问题。
393 msg=KeyErrorMessage（消息）
-->394提升自交换类型（msg）
OSError:在DataLoader工作进程0中捕获到OSError。
原始回溯（最近一次呼叫最后一次）：
文件“/usr/local/lib/python3.6/dist-packages/torch/utils/data/\u-utils/worker.py”，第178行，在\u-worker\u循环中
data=fetcher.fetch（索引）
文件“/usr/local/lib/python3.6/dist-packages/torch/utils/data/_-utils/fetch.py”，fetch中第44行
data=[self.dataset[idx]用于可能的批处理索引中的idx]
文件“/usr/local/lib/python3.6/dist-packages/torch/utils/data/_-utils/fetch.py”，第44行，在
data=[self.dataset[idx]用于可能的批处理索引中的idx]
文件“”，第37行，在\uu getitem中__
img=（self.data）[index[i]]
文件“h5py/_objects.pyx”，第54行，在h5py._objects.with_phil.wrapper中
文件“h5py/_objects.pyx”，第55行，在h5py._objects.with_phil.wrapper中
文件“/usr/local/lib/python3.6/dist packages/h5py/_hl/dataset.py”，第573行，在__
self.id.read（mspace、fspace、arr、mtype、dxpl=self.\u dxpl）
文件“h5py/_objects.pyx”，第54行，在h5py._objects.with_phil.wrapper中
文件“h5py/_objects.pyx”，第55行，在h5py._objects.with_phil.wrapper中
文件“h5py/h5d.pyx”，第182行，位于h5py.h5d.DatasetID.read中
文件“h5py/_proxy.pyx”，第130行，在h5py._proxy.dset_rw中
文件“h5py/_proxy.pyx”，第84行，在h5py._proxy.h5py_h5py中
OSError:无法读取数据（错误的B树签名）

---

我得到上面显示的错误。我是PyTorch的新手，所以请你建议一下可以做什么

我也有同样的错误！您找到解决方案了吗？错误：无法读取数据（错误的B树签名）