# torch_quantile: Quantile In torch: Tensors and Neural Networks with 'GPU' Acceleration

Quantile

## Usage

 `1` ```torch_quantile(self, q, dim = NULL, keepdim = FALSE, interpolation) ```

## 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```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 } ```

### Example output

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torch documentation built on Oct. 7, 2021, 9:22 a.m.