torch_clamp: Clamp

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Clamp

Description

Clamp

Usage

torch_clamp(self, min = NULL, max = NULL)

Arguments

self	(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

clamp(input, min, max, out=NULL) -> Tensor

Clamp all elements in input into the range [ min, max ⁠]⁠ and return a resulting tensor:

y_i = \left\{ \begin{array}{ll} \mbox{min} & \mbox{if } x_i < \mbox{min} \\ x_i & \mbox{if } \mbox{min} \leq x_i \leq \mbox{max} \\ \mbox{max} & \mbox{if } x_i > \mbox{max} \end{array} \right.

If input is of type FloatTensor or DoubleTensor, args min and max must be real numbers, otherwise they should be integers.

clamp(input, *, min, out=NULL) -> Tensor

Clamps all elements in input to be larger or equal min.

If input is of type FloatTensor or DoubleTensor, value should be a real number, otherwise it should be an integer.

clamp(input, *, max, out=NULL) -> Tensor

Clamps all elements in input to be smaller or equal max.

If input is of type FloatTensor or DoubleTensor, value should be a real number, otherwise it should be an integer.

Examples

if (torch_is_installed()) {

a = torch_randn(c(4))
a
torch_clamp(a, min=-0.5, max=0.5)


a = torch_randn(c(4))
a
torch_clamp(a, min=0.5)


a = torch_randn(c(4))
a
torch_clamp(a, max=0.5)
}

torch documentation built on June 7, 2023, 6:19 p.m.