einops.repeat: Allows reordering elements and repeating them in arbitrary...

In einops: Flexible, Powerful, and Readable Tensor Operations

Allows reordering elements and repeating them in arbitrary combinations.

Description

This operation includes functionality of repeat, tile, and broadcast functions.

Usage

einops.repeat(x, expr, ..., .row_major = getOption("einops_row_major", FALSE))

`repeat`(x, expr, ..., .row_major = getOption("einops_row_major", FALSE))

Arguments

x	tensor: array, matrix, or list of arrays of the same shape and type
expr	string: reduction pattern
...	either corresponding axes lengths or a single list of them.
.row_major	logical: whether to use row-major order for the output tensor. If TRUE, the operation is performed in row-major order, but the output will be in whatever order the parent framework uses (e.g. column-major for base::array()).

Details

When composing axes, C-order enumeration is used (consecutive elements have different last axis). Find more examples in the vignettes.

Value

tensor of the same type as input, with dimensions according to output pattern

Why can't the function be called as ⁠repeat()⁠?

repeat is a reserved keyword in R that acts the same as ⁠while(TRUE)⁠, and has no way of being overridden. Hence, this function can only be called as einops.repeat() or using backticks as `repeat`().

Examples

if (requireNamespace("abind", quietly = TRUE)) {

set.seed(42)
# a grayscale image (of shape height x width)
image <- array(rnorm(30 * 40), dim = c(30, 40))

# change it to RGB format by repeating in each channel
output <- einops.repeat(image, 'h w -> h w c', c = 3)
# Visualize the output
as_image_tensor(output)

# repeat image 2 times along height (vertical axis)
output <- einops.repeat(image, 'h w -> (r h) w', r = 2)

# repeat image 2 times along height and 3 times along width
output <- einops.repeat(image, 'h w -> (h2 h) (w3 w)', h2 = 2, w3 = 3)

# convert each pixel to a small square 2x2, i.e. upsample an image by 2x
output <- einops.repeat(image, 'h w -> (h h2) (w w2)', h2 = 2, w2 = 2)

# 'pixelate' an image first by downsampling by 2x, then upsampling
downsampled <- reduce(image, '(h h2) (w w2) -> h w', 'mean', h2 = 2, w2 = 2)
output <- einops.repeat(downsampled, 'h w -> (h h2) (w w2)', h2 = 2, w2 = 2)
as_image_tensor(einops.repeat(output, 'h w -> h w 3'))

}

einops documentation built on Sept. 9, 2025, 5:29 p.m.