torch_quantile: Quantile

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

Quantile

Description

Quantile

Usage

torch_quantile(self, q, dim = NULL, keepdim = FALSE, interpolation = "linear")

Arguments

self	(Tensor) the input tensor.
q	(float or Tensor) a scalar or 1D tensor of quantile values in the range ⁠[0, 1]⁠
dim	(int) the dimension to reduce.
keepdim	(bool) whether the output tensor has dim retained or not.
interpolation	The interpolation method.

quantile(input, q) -> Tensor

Returns the q-th quantiles of all elements in the input tensor, doing a linear interpolation when the q-th quantile lies between two data points.

quantile(input, q, dim=None, keepdim=FALSE, *, out=None) -> Tensor

Returns the q-th quantiles of each row of the input tensor along the dimension dim, doing a linear interpolation when the q-th quantile lies between two data points. By default, dim is None resulting in the input tensor being flattened before computation.

If keepdim is TRUE, the output dimensions are of the same size as input except in the dimensions being reduced (dim or all if dim is NULL) where they have size 1. Otherwise, the dimensions being reduced are squeezed (see torch_squeeze). If q is a 1D tensor, an extra dimension is prepended to the output tensor with the same size as q which represents the quantiles.

Examples

if (torch_is_installed()) {

a <- torch_randn(c(1, 3))
a
q <- torch_tensor(c(0, 0.5, 1))
torch_quantile(a, q)


a <- torch_randn(c(2, 3))
a
q <- torch_tensor(c(0.25, 0.5, 0.75))
torch_quantile(a, q, dim=1, keepdim=TRUE)
torch_quantile(a, q, dim=1, keepdim=TRUE)$shape
}

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