Changelog¶
All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog.
[0.3.0] - 2022-11-04¶
[0.3.0] - Added¶
support for pytorch-lightning 1.8.0
support for python 3.10
support for PyTorch 1.13
support for
ZeroRedundancyOptimizer
[0.3.0] - Fixed¶
call to PL
BaseFinetuning.freeze
did not properly hand control ofBatchNorm
module thawing to FTS schedule. Resolves #5.fixed codecov config for azure pipeline gpu-based coverage
[0.3.0] - Changed¶
Refactored unexpected and expected multi-warning checks to use a single test helper function
Adjusted multiple FTS imports to adapt to reorganized PL/Lite imports
Refactored fts-torch collect_env interface to allow for (slow) collect_env evolution on a per-torch version basis
Bumped required jsonargparse version
adapted to PL protection of
_distributed_available
made callback setup stage arg mandatory
updated mypy config to align with PL
Trainer
handlingupdated dockerfile defs for PyTorch 1.13 and python 3.10
updated github actions versions to current versions
excluded python 3.10 from torch 1.9 testing due to incompatibility
[0.3.0] - Deprecated¶
removed use of deprecated
LightningCLI
save_config_overwrite
in PL 1.8
[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 ofdatasets.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 schedulersadded 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 versionfine-tuning
in textual contexts. (The way language evolves,fine-tuning
will eventually becomefinetuning
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)