New_boxes = boxes + torch.FloatTensor([left, top, left, top]).unsqueeze( RuntimeError: The size of tensor a (0) must match the size of tensor b (4) at non-singleton dimension 1

1

I faced this error when I tried to train model with large dataset (as I tested it with a few subset and works fine). I added “drop_last=True” to avoid the division problem by the batch size.

Any idea about the error I faced : “The size of tensor a (0) must match the size of tensor b (4) at non-singleton dimension 1”

Thanks

2

Based on the error message it seems boxes is an empty tensor:

boxes = torch.tensor([])
boxes + torch.tensor([0., 1., 2., 3.])
# RuntimeError: The size of tensor a (0) must match the size of tensor b (4) at non-singleton dimension 0

so make sure this tensor is valid before trying to add another tensor to it.