Changelog¶

All notable changes to metatensor-operations are documented here, following the keep a changelog format. This project follows Semantic Versioning.

Unreleased ¶

axis="components" can now be passed to metatensor.operations.rename_dimension (#763)
split, split_block, slice and slice_block have been updated to accept a list of integer directly specifying which samples/properties to keep in the output. The corresponding parameter has been renamed to selection or selections (for slice and split respectively) (#772)

block_from_array now takes optional parameters to specify the names of sample, component and property dimensions

Fixed a bug in metatensor.torch.sort where the labels where not properly sorted (#647)
Fix metatensor.abs when used with complex values (#553)

Use torch.jit.script by default on all operations when using the TorchScript backend (i.e. metatensor.torch) (#504)

join() operation now includes the sort_samples argument to control the sorting of samples in the output joined TensorMap. This defaults to False, opposite to the previous default behaviour.

detach() operation to detach all values in a TensorMap/TensorBlock from any computational graph
requires_grad() operation to set the requires_grad of all values in a TensorMap/TensorBlock when storing data in torch Tensors.

the to operation was removed. Similar functionality is now offered by TensorMap.to, TensorBlock.to, and the operations detach() and requires_grad().

Creation operations: empty_like(), ones_like(), zeros_like(), random_like(), block_from_array();
Linear algebra: dot(), lstsq(), solve();
Logic function: allclose(), equal(), equal_metadata();
Manipulation operations: drop_blocks(), join(), manipulate dimension, one_hot(), remove_gradients(), samples reduction, slice(), split(), to();
Mathematical functions: abs(), add(), divide(), multiply(), pow(), subtract();
Set operations: unique_metadata(), sort();