Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog.

[0.2.3] - 2022-10-01

[0.2.3] - Added

• support for pytorch-lightning 1.7.7

• add new temporary HF expected warning to examples

• added HF evaluate dependency for examples

[0.2.3] - Changed

• Use HF evaluate.load() instead of datasets.load_metric()

[0.2.2] - 2022-09-17

[0.2.2] - Added

• support for pytorch-lightning 1.7.6

• added detection of multiple instances of a given callback dependency parent

• add new expected warning to examples

[0.2.2] - Fixed

• import fts to workaround pl TypeError via sphinx import, switch to non-TLS pytorch inv object connection due to current certificate issues

[0.2.2] - Changed

• bumped pytorch dependency in docker image to 1.12.1

[0.2.1] - 2022-08-13

[0.2.1] - Added

• support for pytorch-lightning 1.7.1

• added support for ReduceLROnPlateau lr schedulers

• improved user experience with additional lr scheduler configuration inspection (using an allowlist approach) and enhanced documentation. Expanded use of allow_untested to allow use of unsupported/untested lr schedulers

• added initial user-configured optimizer state inspection prior to phase 0 execution, issuing warnings to the user if appropriate. Added associated documentation #4

[0.2.1] - Fixed

• pruned test_examples.py from wheel

[0.2.1] - Changed

• removed a few unused internal conditions relating to lr reinitialization and parameter group addition

[0.2.0] - 2022-08-06

[0.2.0] - Added

• support for pytorch-lightning 1.7.0

• switched to src-layout project structure

• increased flexibility of internal package management

• added a patch to examples to allow them to work with torch 1.12.0 despite issue #80809

• added sync for test log calls for multi-gpu testing

[0.2.0] - Fixed

• adjusted runif condition for examples tests

• minor type annotation stylistic correction to avoid jsonargparse issue fixed in #148

[0.2.0] - Changed

• streamlined MANIFEST.in directives

• updated docker image dependencies

• disable mypy unused ignore warnings due to variable behavior depending on ptl installation method (e.g. pytorch-lightning vs full lightning package)

• changed full ci testing on mac to use macOS-11 instead of macOS-10.15

• several type-hint mypy directive updates

• unpinned protobuf in requirements as no longer necessary

• updated cuda docker images to use pytorch-lightning 1.7.0, torch 1.12.0 and cuda-11.6

• refactored mock strategy test to use a different mock strategy

• updated pyproject.toml with jupytext metadata bypass configuration for nb test cleanup

• updated ptl external class references for ptl 1.7.0

• narrowed scope of runif test helper module to only used conditions

• updated nb tutorial links to point to stable branch of docs

• unpinned jsonargparse and bumped min version to 4.9.0

• moved core requirements.txt to requirements/base.txt and update load_requirements and setup to reference lightning meta package

• update azure pipelines ci to use torch 1.12.0

• renamed instantiate_registered_class meth to instantiate_class due to ptl 1.7 deprecation of cli registry functionality

[0.2.0] - Deprecated

• removed ddp2 support

• removed use of ptl cli registries in examples due to its deprecation

[0.1.8] - 2022-07-13

[0.1.8] - Added

• enhanced support and testing for lr schedulers with lr_lambdas attributes

• accept and automatically convert schedules with non-integer phase keys (that are convertible to integers) to integers

[0.1.8] - Fixed

• pinned jsonargparse to be <= 4.10.1 due to regression with PTL cli with 4.10.2

[0.1.8] - Changed

• updated PL links for new lightning-ai github urls

• added a minimum hydra requirement for cli usage (due to omegaconf version incompatibility)

• separated cli requirements

• replace closed compound instances of finetuning with the hyphenated compound version fine-tuning in textual contexts. (The way language evolves, fine-tuning will eventually become finetuning but it seems like the research community prefers the hyphenated form for now.)

• update fine-tuning scheduler logo for hyphenation

• update strategy resolution in test helper module runif

[0.1.8] - Deprecated

[0.1.7] - 2022-06-10

[0.1.7] - Fixed

• bump omegaconf version requirement in examples reqs (in addition to extra reqs) due to omegaconf bug

[0.1.7] - Added

[0.1.7] - Changed

[0.1.7] - Deprecated

[0.1.6] - 2022-06-10

[0.1.6] - Added

• Enable use of untested strategies with new flag and user warning

• Update various dependency minimum versions

• Minor example logging update

[0.1.6] - Fixed

• minor privacy policy link update

• bump omegaconf version requirement due to omegaconf bug

[0.1.6] - Changed

[0.1.6] - Deprecated

[0.1.5] - 2022-06-02

[0.1.5] - Added

• Bumped latest tested PL patch version to 1.6.4

• Added basic notebook-based example tests a new ipynb-specific extra

• Updated docker definitions

• Extended multi-gpu testing to include both oldest and latest supported PyTorch versions

• Enhanced requirements parsing functionality

[0.1.5] - Fixed

• cleaned up acknowledged warnings in multi-gpu example testing

[0.1.5] - Changed

[0.1.5] - Deprecated

[0.1.4] - 2022-05-24

[0.1.4] - Added

• Added LR scheduler reinitialization functionality (#2)

• Added advanced usage documentation

• Added advanced scheduling examples

• added notebook-based tutorial link

• enhanced cli-based example hparam logging among other code clarifications

[0.1.4] - Changed

[0.1.4] - Fixed

• addressed URI length limit for custom badge

• allow new deberta fast tokenizer conversion warning for transformers >= 4.19

[0.1.4] - Deprecated

[0.1.3] - 2022-05-04

[0.1.3] - Added

[0.1.3] - Changed

• bumped latest tested PL patch version to 1.6.3

[0.1.3] - Fixed

[0.1.3] - Deprecated

[0.1.2] - 2022-04-27

[0.1.2] - Added

• added multiple badges (docker, conda, zenodo)

• added build status matrix to readme

[0.1.2] - Changed

• bumped latest tested PL patch version to 1.6.2

• updated citation cff configuration to include all version metadata

• removed tag-based trigger for azure-pipelines multi-gpu job

[0.1.2] - Fixed

[0.1.2] - Deprecated

[0.1.1] - 2022-04-15

[0.1.1] - Added

• added conda-forge package

• added docker release and pypi workflows

• additional badges for readme, testing enhancements for oldest/newest pl patch versions

[0.1.1] - Changed

• bumped latest tested PL patch version to 1.6.1, CLI example depends on PL logger fix (#12609)

[0.1.1] - Deprecated

[0.1.1] - Fixed

• Addressed version prefix issue with readme transformation for pypi

[0.1.0] - 2022-04-07

[0.1.0] - Added

• None (initial release)

[0.1.0] - Changed

• None (initial release)

[0.1.0] - Deprecated

• None (initial release)

[0.1.0] - Fixed

• None (initial release)