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torch.copysign
torch.copysign(input, other, *, out=None) → Tensor
-
Create a new floating-point tensor with the magnitude of
input
and the sign ofother
, elementwise.Supports broadcasting to a common shape, and integer and float inputs.
- Parameters
- Keyword Arguments
-
out (Tensor, optional) – the output tensor.
Example:
>>> a = torch.randn(5) >>> a tensor([-1.2557, -0.0026, -0.5387, 0.4740, -0.9244]) >>> torch.copysign(a, 1) tensor([1.2557, 0.0026, 0.5387, 0.4740, 0.9244]) >>> a = torch.randn(4, 4) >>> a tensor([[ 0.7079, 0.2778, -1.0249, 0.5719], [-0.0059, -0.2600, -0.4475, -1.3948], [ 0.3667, -0.9567, -2.5757, -0.1751], [ 0.2046, -0.0742, 0.2998, -0.1054]]) >>> b = torch.randn(4) tensor([ 0.2373, 0.3120, 0.3190, -1.1128]) >>> torch.copysign(a, b) tensor([[ 0.7079, 0.2778, 1.0249, -0.5719], [ 0.0059, 0.2600, 0.4475, -1.3948], [ 0.3667, 0.9567, 2.5757, -0.1751], [ 0.2046, 0.0742, 0.2998, -0.1054]]) >>> a = torch.tensor([1.]) >>> b = torch.tensor([-0.]) >>> torch.copysign(a, b) tensor([-1.])
Note
copysign handles signed zeros. If the other argument has a negative zero (-0), the corresponding output value will be negative.
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https://pytorch.org/docs/2.1/generated/torch.copysign.html