The RuntimeError: Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same error occurs when there is a mismatch between the device (CPU or GPU) of the input tensor and the model’s weights. In your case, the input tensor is on the CPU (torch.FloatTensor), while the model’s weights are on the GPU (torch.cuda.FloatTensor).
Another reason behind the error is when your model is on the GPU, but your data is on the CPU. So, you need to send your input tensors to the GPU.
There are two steps to fix the RuntimeError: Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same error.
- Step 1: Move the model to the GPU (if it’s not already there).
- Step 2: Move the input tensor to the same device as the model.
Step 1: Move the model to the GPU (if it’s not already there)
If the input tensors are on the GPU and the model weights are on the CPU, you will encounter the same error. To resolve this, you must move the model weights to the GPU.
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = model.to(device)This code will move your model to the GPU if a GPU is available, otherwise, it will use the CPU. Once you have moved the model to the appropriate device, make sure your input tensors are also on the same device before performing the forward pass:
Step 2: Move the input tensor to the same device as the model
input_tensor = input_tensor.to(device)After moving the model and the input tensor to the same device, you can perform the forward pass without encountering the error.
That’s it.
