The size of tensor a (32) must match the size of tensor b (784) at non-singleton dimension 2
时间: 2023-09-25 11:17:15 浏览: 102
这是一个错误提示信息,提示你的代码中有一个 tensor 的维度不匹配。具体来说,你有两个 tensor a 和 b,它们的形状分别为 (batch_size, 32) 和 (batch_size, 28, 28),在进行某个操作时需要它们的维度匹配,但是在第 2 维上不匹配,因为 a 的第 2 维大小为 32,而 b 的第 2 维大小为 28。你需要检查代码中这个操作的实现,或者调整 a 和 b 的形状,使得它们在这个维度上匹配。
相关问题
The size of tensor a (32) must match the size of tensor b (224) at non-singleton dimension 2
这个错误提示意味着张量a和张量b在非单一维度2上的大小不匹配,因此无法完成操作。要解决这个问题,需要确保张量a和张量b在维度2上的大小相同。可以使用PyTorch中的view()函数来更改张量的形状,以确保它们在所需的维度上具有相同的大小。例如,可以使用以下代码将张量a的形状更改为(?, 32, ?),其中?表示任意大小的维度,以匹配张量b的形状(?, 224, ?):
```python
a = a.view(-1, 32, -1)
```
这将自动计算第一个和第三个维度的大小,以确保在维度2上具有相同的大小。然后,您可以执行所需的操作。
The size of tensor a (32) must match the size of tensor b (512) at non-singleton dimension 1
The error message "The size of tensor a (32) must match the size of tensor b (512) at non-singleton dimension 1" indicates that there is a size mismatch between two tensors in dimension 1. In order to perform operations between tensors, their sizes must match along all dimensions except for the singleton dimensions.
To resolve this error, you can check the shape of tensor a and tensor b along dimension 1 and ensure they have the same size. If they don't have the same size, you may need to reshape or resize one or both tensors to match their sizes.
Related questions:
1. How can I check the shape of a tensor in PyTorch?
2. How do I resize or reshape a tensor in PyTorch?
3. What are singleton dimensions in tensors?
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