Einops Versions Save

Major changes:

• torch.compile just works, registration of operations happens automatically
• JAX's distributed arrays can use ellipses, and in general ellipsis processing now preserves axis identity. This involved changing internal gears of einops.
• Array API: einops operations can be used with any framework that follows the standard (see einops.array_api)
• Python 3.7 is dead. Good bye, you were great at the time
• Gluon is dropped as previously announced
• reduce/repeat/rearrange all accept lists now

PRs list

• Preserve axis identity + drop python 3.7 by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/255
• Support array api by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/261
• add type-based caching by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/262
• Uniform support for list inputs across rearrange/reduce/repeat by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/263
• Drop gluon by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/264
• automatically register torch ops in torchdynamo by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/265
• release 0.7.0rc1, highlight changes in README by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/266
• cover dynamic shapes in torch.compile, introduce fallback if shape was not cacheable by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/275
• bump version by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/276
• fix #279, update description by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/281
• Add support for any/all reductions in einops.reduce by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/282
• maintenance: cache pip dependencies by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/283
• maintenance: update versions of github actions by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/285

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.6.1...v0.7.0

What's Changed

• cover dynamic shapes in torch.compile, introduce fallback if shape was not cacheable by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/275
• bump version by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/276

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.7.0rc1...v0.7.0rc2

Major changes:

• torch.compile just works, registration of operations happens automatically
• JAX's distributed arrays can use ellipses, and in general ellipsis processing now preserves axis identity. This involved changing internal gears of einops.
• Array API: einops operations can be used with any framework that follows the standard (see einops.array_api)
• Python 3.7 is dead. Good bye, you were great at the time
• Gluon is dropped as previously announced
• Reduce/repeat/rearrange all accept lists now

What's Changed

• Support array api by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/261
• add type-based caching by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/262
• Uniform support for list inputs across rearrange/reduce/repeat by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/263
• Drop gluon by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/264
• automatically register torch ops in torchdynamo by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/265
• release 0.7.0rc1, highlight changes in README by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/266
• Preserve axis identity + drop python 3.7 by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/255

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.6.1...v0.7.0rc1

pre-release is published to allow public testing of new caching logic (pattern analysis is now dependent on input dimensionality to preserve axis identity).

What's Changed

• Preserve axis identity + drop python 3.7 by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/255

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.6.1...v0.6.2rc0

• einops layers perfectly interplay with torch.compile
• einops operations needs registration: run einops._torch_specific.allow_ops_in_compiled_graph() before torch.compile
• paddle is now supported (thanks to @zhouwei25)
• as previously announced, support of mxnet is dropped

What's Changed

• Add PaddlePaddle backend for einops by @zhouwei25 in https://github.com/arogozhnikov/einops/pull/242 , https://github.com/arogozhnikov/einops/pull/245
• Add allow_ops_in_compiled_graph to support torch.compile by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/251
• torch.concat -> torch.cat to support packing for torch < 1.10 by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/238
• chores: improve documentation and testing by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/246
• Remove mxnet by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/231

New Contributors

• @zhouwei25 made their first contribution in https://github.com/arogozhnikov/einops/pull/242

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.6.0...v0.6.1

What's Changed

• Introduce einops.pack and einops.unpack by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/222
• Update example to match description by @EPronovost in https://github.com/arogozhnikov/einops/pull/217
• Improve type hinting by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/221
• Cosmetics for pack/unpack: documentation and comments by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/223
• Preparations for 0.6.0 release by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/224

New Contributors

• @EPronovost made their first contribution in https://github.com/arogozhnikov/einops/pull/217

Announcement

Sunsetting experimental mxnet support: no demand and package is outdated, with numerous deprecations and poor support of corner cases. 0.6.0 will be the last release with mxnet backend.

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.5.0...v0.6.0

What's Changed

• Create einsum operation by @MilesCranmer in https://github.com/arogozhnikov/einops/pull/197
• Add flax layers by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/214
• Add oneflow backend by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/181
• Add oneflow backend by @rentainhe in https://github.com/arogozhnikov/einops/pull/180
• Fix wrong error message by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/196
• Clarify documentation re. default bias on EinMix by @maxeonyx in https://github.com/arogozhnikov/einops/pull/201
• corrected spelling mistake: einsops -> einops by @cs-mshah in https://github.com/arogozhnikov/einops/pull/205
• add mean-reduction for bfloat16, fix #206 by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/209
• add py.typed (adopt PEP 561) by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/211
• Delete tensorflow-specific readme file by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/212
• Adopt pypa/hatch by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/213

New Contributors

• @rentainhe made their first contribution in https://github.com/arogozhnikov/einops/pull/180
• @MilesCranmer made their first contribution in https://github.com/arogozhnikov/einops/pull/197
• @maxeonyx made their first contribution in https://github.com/arogozhnikov/einops/pull/201
• @cs-mshah made their first contribution in https://github.com/arogozhnikov/einops/pull/205

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.4.1...v0.5.0

What's Changed

• fix numpy dependency problem by @lucidrains in https://github.com/arogozhnikov/einops/pull/176

New Contributors

• @lucidrains made their first contribution in https://github.com/arogozhnikov/einops/pull/176

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.4.0...v0.4.1

Main Changes

• torch.jit.script is supported (in addition to previous torch.jit.trace)
• EinMix (swiss-knife for next-gen MLPs) is added. A much-improved einsum/linear layer is now available.
• einops.repeat in torch does not create copy when possible

Detailed PRs

• Update documentation by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/137
• Multiple updates in docs, add Rearrange layer to torch test by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/138
• Add support for torch scripting of einops layers by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/139
• Introduce EinMix - swiss-knife for next-gen MLPs by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/142
• Docs improvements: wording, visual style, EinMix by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/143
• Move docs to a separate folder by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/144
• Type hinting + add testing for EinMix composition/decomposition by @arogozhnikov in https://github.com/arogozhnikov/einops/pull/154
• Reject repeated axes in parse_shape by @dmitriy-serdyuk in https://github.com/arogozhnikov/einops/pull/159
• Enable ellipsis in patterns for parse_shape. by @dmitriy-serdyuk in https://github.com/arogozhnikov/einops/pull/162

New Contributors

• @dmitriy-serdyuk made their first contribution in https://github.com/arogozhnikov/einops/pull/159

Full Changelog: https://github.com/arogozhnikov/einops/compare/v0.3.2...v0.4.0

• documentation and domain (#75, #76, #77, #79, #81), thanks to @cgarciae
• typos and spellcheck (thank @ollema and @GarrettMooney )
• moved away from keras to tf.keras
• adjustments to tutorials and testing
• other minor improvements