torch.clamp
-
torch.clamp(input, min, max, *, out=None) → Tensor
-
Clamp all elements in
input
into the range[
min
,max
]
. Let min_value and max_value bemin
andmax
, respectively, this returns:- Parameters
-
- input (Tensor) – the input tensor.
- min (Number) – lower-bound of the range to be clamped to
- max (Number) – upper-bound of the range to be clamped to
- Keyword Arguments
-
out (Tensor, optional) – the output tensor.
Example:
>>> a = torch.randn(4) >>> a tensor([-1.7120, 0.1734, -0.0478, -0.0922]) >>> torch.clamp(a, min=-0.5, max=0.5) tensor([-0.5000, 0.1734, -0.0478, -0.0922])
-
torch.clamp(input, *, min, out=None) → Tensor
Clamps all elements in
input
to be larger or equalmin
.- Parameters
-
input (Tensor) – the input tensor.
- Keyword Arguments
-
- min (Number) – minimal value of each element in the output
- out (Tensor, optional) – the output tensor.
Example:
>>> a = torch.randn(4) >>> a tensor([-0.0299, -2.3184, 2.1593, -0.8883]) >>> torch.clamp(a, min=0.5) tensor([ 0.5000, 0.5000, 2.1593, 0.5000])
-
torch.clamp(input, *, max, out=None) → Tensor
Clamps all elements in
input
to be smaller or equalmax
.- Parameters
-
input (Tensor) – the input tensor.
- Keyword Arguments
-
- max (Number) – maximal value of each element in the output
- out (Tensor, optional) – the output tensor.
Example:
>>> a = torch.randn(4) >>> a tensor([ 0.7753, -0.4702, -0.4599, 1.1899]) >>> torch.clamp(a, max=0.5) tensor([ 0.5000, -0.4702, -0.4599, 0.5000])
© 2019 Torch Contributors
Licensed under the 3-clause BSD License.
https://pytorch.org/docs/1.8.0/generated/torch.clamp.html