Aliases in torch

Created On: Jul 22, 2025 | Last Updated On: Jul 22, 2025

The following are aliases in torch to their counterparts in the nested namespaces in which they are defined. Feel free to use either the top-level version in torch (e.g. torch.broadcast_tensors()) or the nested version torch.functional.broadcast_tensors().

align_tensors
atleast_1d	Returns a 1-dimensional view of each input tensor with zero dimensions.
atleast_2d	Returns a 2-dimensional view of each input tensor with zero dimensions.
atleast_3d	Returns a 3-dimensional view of each input tensor with zero dimensions.
block_diag	Create a block diagonal matrix from provided tensors.
broadcast_shapes	Similar to broadcast_tensors() but for shapes.
broadcast_tensors	Broadcasts the given tensors according to Broadcasting semantics.
cartesian_prod	Do cartesian product of the given sequence of tensors.
cdist	Computes batched the p-norm distance between each pair of the two collections of row vectors.
chain_matmul	Returns the matrix product of the $N$ 2-D tensors.
einsum	Sums the product of the elements of the input operands along dimensions specified using a notation based on the Einstein summation convention.
lu	Computes the LU factorization of a matrix or batches of matrices A.
meshgrid	Creates grids of coordinates specified by the 1D inputs in attr:tensors.
norm	Returns the matrix norm or vector norm of a given tensor.
split	Splits the tensor into chunks.
stft	Short-time Fourier transform (STFT).
tensordot	Returns a contraction of a and b over multiple dimensions.
unique	Returns the unique elements of the input tensor.
unique_consecutive	Eliminates all but the first element from every consecutive group of equivalent elements.
unravel_index	Converts a tensor of flat indices into a tuple of coordinate tensors that index into an arbitrary tensor of the specified shape.