python - Pytorch 神经网络中张量大小错误

Question

我想使用预训练的 AlexNet 对我的数据集中的非分类图像进行分类，我得到一个RuntimeError: stack expects each tensor to be equal size, but got [3, 224, 224] at entry 0 and [4, 224, 224] 在我的 Jupyter Notebook 的 417 单元格的第 19 项。请你帮我解决这样的错误。

我有一个包含不同房间图像的数据集：浴室、厨房、客厅等。所以，我有 6 个班级。我有 1547 张图片被分类，我想使用预训练的神经网络对其他图片进行分类。我在 Pytorch 中创建了一个数据集，然后我下载了预训练的 AlexNet，然后我在张量的大小上遇到了这样的错误。拜托，你能帮帮我吗？ Colab 与代码

有错误的单元格的图片

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-417-17d11cc21579> in <module>
      3     # Train phase
      4     model.train()
----> 5     for idx, (inputs, labels) in enumerate(data_loader['train']):
      6         optimizer.zero_grad()
      7         inputs = inputs.to(device)

~/opt/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py in __next__(self)
    519             if self._sampler_iter is None:
    520                 self._reset()
--> 521             data = self._next_data()
    522             self._num_yielded += 1
    523             if self._dataset_kind == _DatasetKind.Iterable and \

~/opt/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py in _next_data(self)
    559     def _next_data(self):
    560         index = self._next_index()  # may raise StopIteration
--> 561         data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
    562         if self._pin_memory:
    563             data = _utils.pin_memory.pin_memory(data)

~/opt/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py in fetch(self, possibly_batched_index)
     45         else:
     46             data = self.dataset[possibly_batched_index]
---> 47         return self.collate_fn(data)

~/opt/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py in default_collate(batch)
     82             raise RuntimeError('each element in list of batch should be of equal size')
     83         transposed = zip(*batch)
---> 84         return [default_collate(samples) for samples in transposed]
     85 
     86     raise TypeError(default_collate_err_msg_format.format(elem_type))

~/opt/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py in <listcomp>(.0)
     82             raise RuntimeError('each element in list of batch should be of equal size')
     83         transposed = zip(*batch)
---> 84         return [default_collate(samples) for samples in transposed]
     85 
     86     raise TypeError(default_collate_err_msg_format.format(elem_type))

~/opt/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py in default_collate(batch)
     54             storage = elem.storage()._new_shared(numel)
     55             out = elem.new(storage)
---> 56         return torch.stack(batch, 0, out=out)
     57     elif elem_type.__module__ == 'numpy' and elem_type.__name__ != 'str_' \
     58             and elem_type.__name__ != 'string_':

RuntimeError: stack expects each tensor to be equal size, but got [3, 224, 224] at entry 0 and [4, 224, 224] at entry 19

标签： pythonneural-networkpytorchtransfer-learningpre-trained-model