Sizes of tensors must match except in dimension 1. Expected size 256 but got size 513 for tensor number 4 in the list

这个错误通常表示在进行某些操作时，需要的张量大小不匹配。在这个错误消息中，张量编号为4的大小为513，但是需要的大小为256。请检查你的代码，并确保在进行操作时张量的大小是相同的，除了维度1。你可能需要使用PyTorch中的view()函数来调整张量的大小，或者使用其他类似的函数。如果你仍然无法解决问题，请提供更多的上下文和代码，以便更好地理解问题。

相关问题

untimeError: Sizes of tensors must match except in dimension 1. Expected size 256 but got size 128 for tensor number 1 in the list.

这个错误通常是由于在进行张量操作时，两个张量的大小不匹配导致的。具体来说，这个错误提示中的“dimension 1”指的是张量的第二个维度，即列数。在你的代码中，有两个张量的列数分别为256和128，这是不允许的。

要解决这个问题，你需要检查你的代码中涉及到这两个张量的操作，确保它们的列数相同。如果你无法确定哪些操作导致了这个错误，可以尝试使用print语句或调试器来跟踪代码执行过程中的张量大小。

Sizes of tensors must match except in dimension 1. Expected size 2 but got size 1 for tensor number 1 in the list.

This error message typically occurs when you are trying to perform an operation that requires tensors of the same size, but one or more of the tensors in the list has a different size than expected. In particular, the error message suggests that the tensors have dimensions greater than 1, and that the only dimension in which they can differ is the first dimension (i.e., the batch size).

For example, suppose you have a list of tensors representing the inputs to a neural network, and you want to concatenate them along the second dimension (e.g., to combine two 1D feature vectors into a single 2D feature matrix). If the tensors have different sizes along the second dimension, you will get this error message.

To resolve this issue, you should check the sizes of the tensors in the list and make sure they are consistent with the operation you are trying to perform. If necessary, you may need to reshape or pad the tensors to ensure that they have the same size.