torch_allclose: Allclose

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

Allclose

Description

Allclose

Usage

torch_allclose(self, other, rtol = 1e-05, atol = 1e-08, equal_nan = FALSE)

Arguments

self	(Tensor) first tensor to compare
other	(Tensor) second tensor to compare
rtol	(float, optional) relative tolerance. Default: 1e-05
atol	(float, optional) absolute tolerance. Default: 1e-08
equal_nan	(bool, optional) if TRUE, then two NaN s will be compared as equal. Default: FALSE

allclose(input, other, rtol=1e-05, atol=1e-08, equal_nan=False) -> bool

This function checks if all input and other satisfy the condition:

\vert \mbox{input} - \mbox{other} \vert \leq \mbox{atol} + \mbox{rtol} \times \vert \mbox{other} \vert

elementwise, for all elements of input and other. The behaviour of this function is analogous to ⁠numpy.allclose <https://docs.scipy.org/doc/numpy/reference/generated/numpy.allclose.html>⁠_

Examples

if (torch_is_installed()) {

torch_allclose(torch_tensor(c(10000., 1e-07)), torch_tensor(c(10000.1, 1e-08)))
torch_allclose(torch_tensor(c(10000., 1e-08)), torch_tensor(c(10000.1, 1e-09)))
torch_allclose(torch_tensor(c(1.0, NaN)), torch_tensor(c(1.0, NaN)))
torch_allclose(torch_tensor(c(1.0, NaN)), torch_tensor(c(1.0, NaN)), equal_nan=TRUE)
}

torch documentation built on May 29, 2024, 9:54 a.m.