The size of tensor a (10) must match the size of tensor b (64) at non-singleton dimension 1错误
时间: 2024-06-16 14:05:56 浏览: 9
这个错误是由于两个张量的维度不匹配导致的。在这个错误中,张量a的大小是10,而张量b的大小是64,但在非单例维度1上它们的大小不匹配。
要解决这个错误,你需要确保两个张量在所有维度上的大小都匹配。你可以通过调整张量的形状或重新计算数据来实现匹配。
可能的解决方法包括:
1. 调整张量a的形状,使其在维度1上的大小与张量b相匹配。
2. 调整张量b的形状,使其在维度1上的大小与张量a相匹配。
3. 检查你的数据是否正确,确保它们具有相同的大小和形状。
相关问题
The size of tensor a (10) must match the size of tensor b (3) at non-singleton dimension 1
The error message "The size of tensor a (10) must match the size of tensor b (3) at non-singleton dimension 1" indicates that the dimensions of tensor a and tensor b do not match at dimension 1, which prevents the operation from being completed. It seems that the number of elements in tensor a at dimension 1 is 10, while the number of elements in tensor b at dimension 1 is 3.
To fix this issue, you can either resize one of the tensors to match the other tensor's dimension at dimension 1, or reshape one of the tensors to have a different number of dimensions.
Here are some possible solutions:
1. Reshape tensor a: You can reshape tensor a to match the number of elements in tensor b at dimension 1. For example, if tensor a has a shape of (10, 5) and tensor b has a shape of (3, 5), you can reshape tensor a to have a shape of (3, 2, 5) using the reshape() function.
2. Resize tensor b: Alternatively, you can resize tensor b to match the number of elements in tensor a at dimension 1. For example, if tensor a has a shape of (10, 5) and tensor b has a shape of (3, 5), you can resize tensor b to have a shape of (10, 5) using the resize() function.
3. Verify the input data: Double-check the input data for tensor a and tensor b to ensure that they have the correct dimensions and sizes.
The size of tensor a (100) must match the size of tensor b (10) at non-singleton dimension 0
这个错误提示意味着张量a和张量b在非单一维度0上的大小不匹配,因此无法完成操作。如果张量a的大小为100,张量b的大小为10,则无法在第0个维度上匹配它们。要解决这个问题,您需要确保张量a和张量b在所有维度上的大小都匹配,或者使用广播机制来匹配它们的大小。
以下是两种解决方法的示例代码:
1. 确保张量a和张量b在所有维度上的大小都匹配:
```python
import torch
a = torch.randn(100, 5)
b = torch.randn(10, 5)
if a.size(0) != b.size(0):
raise ValueError("The size of tensor a ({}) must match the size of tensor b ({}) at non-singleton dimension 0".format(a.size(0), b.size(0)))
# 进行操作
```
2. 使用广播机制来匹配张量a和张量b的大小:
```python
import torch
a = torch.randn(100, 5)
b = torch.randn(10, 5)
# 使用广播机制来匹配张量a和张量b的大小
a = a.unsqueeze(1) # 在第1个维度上添加一个维度
b = b.unsqueeze(0) # 在第0个维度上添加一个维度
a = a.expand(-1, 10, -1) # 在第1个维度上复制10次
b = b.expand(100, -1, -1) # 在第0个维度上复制100次
# 进行操作
```
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