最近在处理VOT数据集时，遇到了一个奇怪的问题，特此记录。

源代码如下：

def ltr_collate_stack1(batch):
    """Puts each data field into a tensor. The tensors are stacked at dim=1 to form the batch"""

    error_msg = "batch must contain tensors, numbers, dicts or lists; found {}"
    elem_type = type(batch[0])
    if isinstance(batch[0], torch.Tensor):
        out = None
        if _check_use_shared_memory():
            # If we're in a background process, concatenate directly into a
            # shared memory tensor to avoid an extra copy
            numel = sum([x.numel() for x in batch])
            storage = batch[0].storage()._new_shared(numel)
            out = batch[0].new(storage)
            # print(batch.shape)
            # print(out.shape)
        return torch.stack(batch, 1, out=out)

按道理来说代码执行结束，out.shape和storage.shape一致，但是在pytorch2.1.1版本中，这两个却不一致，将代码修改如下即可正确运行：

def ltr_collate_stack1(batch):
    """Puts each data field into a tensor. The tensors are stacked at dim=1 to form the batch"""

    error_msg = "batch must contain tensors, numbers, dicts or lists; found {}"
    elem_type = type(batch[0])
    if isinstance(batch[0], torch.Tensor):
        out = None
        if _check_use_shared_memory():
            # If we're in a background process, concatenate directly into a
            # shared memory tensor to avoid an extra copy
            numel = sum([x.numel() for x in batch])
            storage = batch[0].storage()._new_shared(numel)
            out = batch[0].new(storage).view(-1)
            # print(batch.shape)
            # print(out.shape)
        return torch.stack(batch, 1, out=out)