RunTimeError:1ongly baches of spatial targets supported (3D tensors) but go targets of size : : [1,3,7,7]
时间: 2024-05-09 15:20:51 浏览: 118
pytorch模型提示超出内存RuntimeError: CUDA out of memory.
5星 · 资源好评率100%
This error occurs when trying to run a machine learning model that expects a 3D tensor as input, but receives a tensor of size [1,3,7,7]. This means that the input tensor has only 4 dimensions, while the model expects 5 dimensions.
To fix this error, you need to reshape the input tensor to have a 5th dimension. One way to do this is to add a singleton dimension at the beginning or end of the tensor, depending on the requirements of the model.
For example, if the model expects the input tensor to have dimensions [batch_size, num_channels, height, width, depth], you can reshape the tensor as follows:
```
input_tensor = torch.rand(1, 3, 7, 7) # Example input tensor
input_tensor = input_tensor.unsqueeze(0) # Add batch dimension
input_tensor = input_tensor.unsqueeze(-1) # Add depth dimension
```
This will result in an input tensor of size [1, 3, 7, 7, 1], which can be used as input to the model without raising the RunTimeError.
阅读全文