unsqueeze¶
dragon.vm.torch.
unsqueeze
(
input,
dim,
out=None
)[source]¶Expand the dimensions of input with size 1.
dim
could be negative:x = torch.ones(2, 3, 4, 5) # dimension is the size-1 position in output print(torch.unsqueeze(x, dim=0).shape) # (2, 3, 4, 5) -> (1, 2, 3, 4, 5) print(torch.unsqueeze(x, dim=1).shape) # (2, 3, 4, 5) -> (2, 1, 3, 4, 5) # A negative dimension is the last-k dimension print(torch.unsqueeze(x, dim=4).shape) # (2, 3, 4, 5) -> (2, 3, 4, 5, 1) print(torch.unsqueeze(x, dim=-1).shape) # Equivalent # Also, dimension could be a sequence of integers print(torch.unsqueeze(x, dim=(-1, -3)).shape) # (2, 3, 4, 5) -> (2, 3, 4, 1, 5, 1)
- Parameters:
- input (dragon.vm.torch.Tensor) – The input tensor.
- dim (Union[int, Sequence[int]]) – The position to insert the new dimension.
- out (dragon.vm.torch.Tensor, optional) – The output tensor.
- Returns:
dragon.vm.torch.Tensor – The new tensor.