Skip to content

Bump hydra-core from 1.3.1 to 1.3.2#536

Merged
ashleve merged 1 commit intodevfrom
dependabot/pip/hydra-core-1.3.2
Feb 24, 2023
Merged

Bump hydra-core from 1.3.1 to 1.3.2#536
ashleve merged 1 commit intodevfrom
dependabot/pip/hydra-core-1.3.2

Conversation

@dependabot
Copy link
Contributor

@dependabot dependabot bot commented on behalf of github Feb 23, 2023

Bumps hydra-core from 1.3.1 to 1.3.2.

Release notes

Sourced from hydra-core's releases.

Hydra 1.3.2

1.3.2 (2023-02-22)

Features

  • Add a hydra.utils.get_object function that gives users access to Hydra's dotpath-lookup machinery. (#2139)
  • Allow config_path to specify a non-relative module path, by starting with pkg:// (#2564)

Maintenance Changes

  • Drop support for python3.6 (#2304)

Links:

Changelog

Sourced from hydra-core's changelog.

1.3.2 (2023-02-22)

Features

  • Add a hydra.utils.get_object function that gives users access to Hydra's dotpath-lookup machinery. (#2139)
  • Allow config_path to specify a non-relative module path, by starting with pkg:// (#2564)

Maintenance Changes

  • Drop support for python3.6 (#2304)
Commits

Dependabot compatibility score

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot merge will merge this PR after your CI passes on it
  • @dependabot squash and merge will squash and merge this PR after your CI passes on it
  • @dependabot cancel merge will cancel a previously requested merge and block automerging
  • @dependabot reopen will reopen this PR if it is closed
  • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

Bumps [hydra-core](https://github.com/facebookresearch/hydra) from 1.3.1 to 1.3.2.
- [Release notes](https://github.com/facebookresearch/hydra/releases)
- [Changelog](https://github.com/facebookresearch/hydra/blob/v1.3.2/NEWS.md)
- [Commits](facebookresearch/hydra@v1.3.1...v1.3.2)

---
updated-dependencies:
- dependency-name: hydra-core
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Feb 23, 2023
@ashleve ashleve changed the base branch from main to dev February 24, 2023 12:16
@ashleve ashleve merged commit 82f31b9 into dev Feb 24, 2023
@ashleve ashleve deleted the dependabot/pip/hydra-core-1.3.2 branch February 24, 2023 12:17
Unity-Billal-mesloub referenced this pull request in Unity-Billal-mesloub/lightning-hydra-template Dec 30, 2025
* Dev (#135)

* remove logging best so far metric values from mnist model

* update tests

* update README.md

* comment out wandb tests

* Dev (#136)

* comment improvements

* add __init__.py

* add disabling pin memory on fast dev run

* rename template_utils.py to utils.py

* improve README.md

* add num_classes property to mnist datamodule

* add sh to requirements.txt

* bump package versions

* Release/0.9 (#141)

* add flake8 and prettier to pre-commit-config
* add setup.cfg
* add workers=True to seed_everything()
* update lightning badge logo
* bump package versions
* update README.md
* add __init__.py files
* add more logger configs parameters
* add default Dockerfile
* change .env.template to .env.example
* move inference example to readme
* remove img_dataset.py
* simplify names of wandb callbacks
* remove wandb test marker
* format files with prettier

* Refactor dockerfile (#149)

* refactor dockerfile to allow mounting

* update README.md

* Release/1.0 (#156)

* update to Hydra 1.1
* add bash folder with scripts for conda setup and run scheduling
* add saving seed in `log_hyperparameters()` method
* redesign Dockerfile to make it weight less
* add `test_after_training` parameter to config
* add inheritance to trainer configs
* remove forcing ddp-friendly configuration
* refactor tests
* remove conda_env_gpu.yaml
* remove default langage version from pre-commit config
* add mnist datamodule unit test
* rename test folder from 'smoke' to 'shell'
* remove wandb import from utils.py
* change 'use_artifact' to 'log_artifact' in wandb callbacks
* add rank zero decorator to wandb callbacks
* add dumping rich tree config to file
* get rid of `=` character in ckpt names
* update requirements.txt
* update LICENSE
* update README.md

* Update README.md

* Update wandb_callbacks.py (#152)

* Update wandb_callbacks.py
* UploadCodeAsArtifact: Add the functionality to use git to decide which files are source files. Can upload all files that are not ignored by git instead of all '*.py' file.
* UploadCheckpointsAsArtifact: ckpts are output of the run, so use `experiment.log_artifact(ckpts)` instead

* Release/1.1 (#174)

* introduce different running modes: default, debug, experiment
* fix pytorch installation in setup_conda.sh
* fix incorrect calculation of precision, recall and f1 score in wandb callback
* add `_self_` to config.yaml for compatibility with hydra1.1
* fix setting seed in `train.py` so it's skipped when `seed=null`
* add exception message when trying to use wandb callbacks with `trainer.fast_dev_run=true`
* change `axis=-1` to `dim=-1` in LogImagePredictions callback
* add 'Reproducibilty' section to README.md

* Enanche trainer debug #177 (#179)

*modifiy `configs/trainer/debug.yaml` to enable some debug options
*remove unused `if config.get("debug"):` in `extras`
*update the documentation

* Move LICENSE to README.md (#180)

* Hotfix (#187)

* make debug mode automatically set level of all command line loggers to `DEBUG`
* make debug mode automatically set the trainer config to `debug.yaml`
* add generator seed to fix test data leaking to train data in datamodule `setup()`
* move Dockerfile to `dockerfiles` branch
* update README.md

* Update `mnist_datamodule.py`

* General documentation improvements (#193)

*add a new way for accessing datamodule attributes to the README
*general documentation improvements

* Clarify meaning of EarlyStopping patience (#195)

*specify that EarlyStopping patience is counted in validation epochs and not in training epochs.

* Release/1.2 (#198)

* update template to pytorch 1.10+ and lightning 1.5+
* add experiment mode to all experiment configs and implement special logging paths for experiment mode
* add `MaxMetric` to model, for computation of best so far validation accuracy
* add RichProgressBar to default callbacks
* get rid of trick for preventing auto hparam logging, since lightning now supports it with `self.save_hyperparameters(logger=False)`
* add `self.save_hyperparameters()` to datamodule since lightinng now supports it
* deprecate Apex support
* deprecate bash script for conda setup
* change `terminate_on_nan` debug option to `detect_anomaly` for compatibility with lightning v1.5
* specify model and datamodule during `trainer.test()`, for compatibility with lightning v1.5
* remove `configs/trainer/all_params.yaml`
* make hyperparameter optimization compatible with lightning v1.5
* general documentation improvements

* Release/1.2 (#199)

*add manual resetting of metrics at the end of every epoch
*set `pytorch-lightning>=1.5` in `requirements.txt`

* Update documentation

* Local config files (#205)

* Introduce local config files

* Add vendor dir (#207)

Implement "best practice" for storing third party code

* Unify log dir structure (#211)

* Unifiy log dir paths
* Add a little helper script `logs/latest` which can be used to quickly change into the latest log dir of a specific kind
* Update README

* Avoid conflict between isort and black (#214)

Specify black profile for isort inside .pre-commit-config.yaml just in case someone deletes the setup.cfg

* Fix missing parameter in "Accessing datamodule attributes" trick in the README (#219)

* Remove deprecated trainer arguments (#223)

* Remove deprecated trainer arguments: `weight summary` and `progress_bar_refresh_rate`
* Remove deprecated example from README
* Add RichModelSummary to the callbacks

* Rename accelerator="ddp" to strategy="ddp" (#228)

* Remove redundant parts in filenames (#213)

* Remove redundant parts in config filenames
* Change `mnist_model.py` to `mnist_module.py`
* Change `MNISTLitModel` to `MNISTLitModule`
* Change folder `modules/` to `components/`
* Update README

* Add metric name validation for hyperparameter search (#241)

* Documentation and comment improvements (#242)

* Update requirements.txt for mac compatibility (#247)

* Refactoring configs (#248)

- make every run be an experiment by default
- deprecate `mode` configs
- introduce `debug` configs
- introduce `log_dir` configs
- remove unnecessary utilities from `utils.extras()`
- add config flag for skipping training
- update README.md

* Refactor rich config printing (#249)

- Refactor `print_config()` method
- Modify `print_config()` so all config groups are always printend

* Multiple pipelines - training and evaluation (#250)

- introduce best practice for multiple pipelines
- Implement evaluation pipeline
- allow for using relative ckpt paths
- general refactoring
- update README.md

* Add nbstripout to pre-commit hooks (#252)

- Add jupyter notebook output cell clearing before commit

* Rename folder `bash` to `scripts` (#253)

* Move wandb callbacks to the `wandb-callbacks` branch (#254)

* Remove `src/callbacks/`
* Remove `configs/callbacks/wandb.yaml`
* Update readme

* Update requirements and pre-commit hooks (#255)

* Update package versions in requirements.txt
* Update pre-commit hooks versions in pre-commit-config.yaml
* Specify testpath in setup.cfg
* Update readme

* Remove optuna default values (#235)

* Remove some of the optuna default values
* Add more explanatory comments in mnist_optuna.yaml

* fix : Not printing best ckeckpoint (#261)

* change `config.trainer.get("train")` to `config.get("train")` in `training_pipeline.py`

* Recursively instantiate `SimpleDenseNet` using Hydra (#209)

* Add recursive instantiation of `net` object which is passed to `MNISTLitModule` on init

* Log model hparams first (#263)

* Change the order of logging hparams for more convenient tensorboard usage

* Fix logging path in mlflow (#269)

* make MLFlow logger place all run logs in the same directory so UI can read all of them at once

* Add docformatter to pre-commit hooks (#270)

* Add docformatter to pre-commit hooks
* Autoformat all docstrings

* Add veryfing logger is not None before logging hparams (#275)

* Readme improvements (#276)

* Fix errors in 'accessing datamodule attributes trick' in the readme (#279)

* fix accessing attribute from config syntax in the readme
* fix config printing warning in the readme

* Fix val_acc_best calculation (#287)

* Add val_acc_best metric reset at the start of the run to prevent storing results from validation sanity checks

* Remove logs/latest script

* Rename `quee` to `queue` in `print_config()`

* Refactor ckpt_path (#293)

* Move setting seed to `utils.extras()` (#294)

* Move optimized metric retrieval to `utils.get_metric_value()` (#295)

* Improve comments and code formatting (#296)

* Rename `config` to `cfg` (#297)

* Update requirements.txt and pre-commit hooks (#298)

* Add `utils.finish()` to test pipeline (#299)

* Move callbacks and loggers instantation to utils (#300)

* Remove `_convert_=partial` from trainer instantiation (#301)

* Add pipeline wrapper decorator (#304)

* Add _pipeline_wrapper.py

* Add pyrootutils (#305)

* Refactor configs (#306)

* Format files with pre-commit hooks and improve comments

* Refactoring tests (#307)

* Rename test.py to eval.py (#309)

* Rename "pipelines" to "tasks" (#311)

* Add object instantiation to module files for quick debugging (#312)

* Adapt template to hydra 1.2 - no more changing work dir by default (#313)

* Fix evaluation config (#315)

* Fix optuna search space (#316)

* Add bandit (#317)

* Github Actions (#318)

* Rename utils.extras() to utils.start() (#319)

* Replace setup.cfg with pyproject.toml (#320)

* Add closing neptune, mlflow and comet to utils.finish() (#321)

* Fix output dir path in logger configs (#323)

* Replace `os` with `pathlib` (#324)

* Fix MLFlowLogger class name (#326)

* Disable callbacks in overfit.yaml (#329)

* Improve comments (#330)

* Split utils into several files (#332)

* Improve trainer configs (#333)

* Add code coverage to CI (#335)

* Disable hydra command line logger during debugging (#336)

* Disable `pyrootutils` changing work dir by default (#337)

* Update `train.py` and `eval.py` (#338)

* Add test coverage settings to `pyproject.toml` (#339)

* Add `deterministic` flag to trainer config (#342)

* Add `mps.yaml` trainer config for accelerated training on mac (#344)

* Add enforcing tags (#340)

* Remove experiment name (#345)

* Move extra config utils to `configs/extras/default.yaml` (#346)

* Configure Optimizer in Hydra using _partial_: true (#334)

* Add saving tags to file (#354)

* Replace asserts with warnings in task_utils.py (#353)

* Improve main in mnist_datamodule.py and simple_dense_net.py (#355)

* Comment out experiment name in logger configs (#357)

* Fix typos in configs (#358)

* Add sampler override to default hparams_search config (#360)

* Split callbacks config into multiple files (#365)

* Refactor utils (#366)

* Update train_task.py (#367)

* Update logger configs (#368)

* Update tests (#370)

* Add setup.py (#369)

* Update train.py and eval.py (#371)

* Add code quality workflows for main branch and pull requests (#364)

* Add `logs/` folder (#373)

* Fix missing logging of seed hyperparameter (#374)

* Add missing function imports to `utils/__init__.py` (#376)

* Add docstrings to tests (#375)

* Add codespell linter and fix spelling mistakes (#377)

* Update README.md (#372)

* Remove tracking gradient norm from default debug config (#378)

* Make tasks return metric dict and object dict (#379)

* Replace switching optuna sampler with a comment (#381)

* Add testing metric values to `test_train.py` and `test_eval.py` (#380)

* Remove comment

* Add names to all steps of workflows (#382)

* Update train_task.py

* Rename `task_utils.py` to `utils.py` (#383)

* Fix typo

* Add pull request template (#385)

* Remove unnecessary comments (#384)

* Construct config path from root (#387)

* Add `md-format` to pre-commits (#386)

* Add Makefile (#388)

* Update README.md (#389)

* Add warning when best ckpt is not found (#390)

* Fix warning message in `train_task.py` (#391)

* Set `pythonpath=True` in model and datamodule (#392)

* Rename workflows (#395)

* Update README.md (#394)

* Add `work_dir` to config paths (#397)

* Update `requirements.txt` (#398)

* Update dependabot (#399)

* Bump torchmetrics from 0.8.0 to 0.9.2 (#400)

* Fix typing (#401)

* Fix missing cpu trainer (#402)

* Bump pytorch-lightning from 1.6.5 to 1.7.1 (#408)

* Update README.md (#419)

* Add separate job for windows in tests worfklow (#422)

* Update Makefile (#423)

* Move tasks code inside entry files (#421)

* Update README.md (#425)

* Fix docstring (#428)

* Improve comments (#429)

* Update `make clean-logs` in Makefile (#430)

* Pre-commit config updates for jupyter notebooks and flake8 W503 (#435)

* Fix logging metrics in DDP mode (#426)

* Add shellcheck linter (#427)

* Add Vertex AI integration repo to readme (#440)

* Improve comments (#441)

* Update readme (#442)

* Fix broken link of datamodule (#444)

* Add scheduler example (#439)

* Make use of learning rate scheduler optional (#449)

* Made `trainer.configure_optimizers()` robust to unspecified learning rate schedulers

* Bump torchmetrics from 0.9.3 to 0.10.0 (#454)

* Bump pytorch-lightning from 1.7.1 to 1.8.1 (#468)

* Update command for using tags in readme (#465)

* Rename `step()` to `model_step()` for compatibility with recent lightning release (#472)

* Fix deprecated TPU import (#473)

* Move macos testing to separate workflow task (#474)

* Add `task` and `num_classes` args to accuracy metric (#475)

* Improve comments (#476)

* Send hparams to all loggers (#479)

* Upgrade to hydra 1.3 (#480)

* Remove debug from makefile (#482)

* Improve utils warnings (#483)

* Fix loading MNISTLitModule from ckpt (#481)

* Add explicit comment/warning to `training_epoch_end()` (#486)

* Add `codecov.yml` to prevent failing pipeline on coverage decrease (#484)

* Refactor `task_wrapper` decorator (#488)

* Bump hydra-core from 1.3.0 to 1.3.1 (#492)

* Add release drafter (#493)

* Update code examples in readme (#494)

* Add `dev` branch to pr tests workflow (#497)

* Improve root setup (#496)

* Refactor tests (#498)

* Rename `datamodules` folder to `data` (#501)

* Update `README.md` (#499)

* Remove object instantiation from `__main__` methods  (#502)

* Add PR authors to release draft config (#503)

* Fix readme typo (#507)

* Fix use of deprecated LightningLoggerBase class (#517)

* Hotfix for isort poetry incompatibility (#515)

* Bump pytorch-lightning from 1.8.3 to 1.9.1 (#522)

* Deprecate Python 3.7 (#523)

* Update `README.md` (#524)

* Bump hydra-core from 1.3.1 to 1.3.2 (#536)

Bumps [hydra-core](https://github.com/facebookresearch/hydra) from 1.3.1 to 1.3.2.
- [Release notes](https://github.com/facebookresearch/hydra/releases)
- [Changelog](https://github.com/facebookresearch/hydra/blob/v1.3.2/NEWS.md)
- [Commits](facebookresearch/hydra@v1.3.1...v1.3.2)

---
updated-dependencies:
- dependency-name: hydra-core
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Set hydra version to 1.3 in tests (#542)

* Encourage resetting all validation metrics when training starts (#540)

* Support for installing dependencies with conda (#532)

* Add `__init__.py` to `configs/` folder (#539)

* Release v2.0.0 (#545)

* Support for logging with Aim (#534)

* Update template to Lightning 2.0 (#548)

* Update pre-commit hooks (#549)

* Refactor utils (#541)

* Add option for pytorch 2.0 model compilation (#550)

* Update `README.md` (#551)

---------

Co-authored-by: Mattie Tesfaldet <mattie@meta.com>
Co-authored-by: Johnny <johnnynuca14@gmail.com>

* Update `README.md` (#553)

* Fix name `instantiatiators.py` -> `instantiators.py` (#558)

* Fix dead links in callback configs (#557)

* Set strategy to `ddp` in ddp config (#571)

* Set `sync_dist=True` when logging best so far validation accuracy (#572)

* Lightning + Aim dependency fix in conda environment.yaml and setup.py. (#575)

* Change "pytorch_lightning" to "lightning" in instantiators.py (#577)

* Fix WandB config improper hierarchical display of keys (#583)

* Remove yaml extension from hydra defaults lists (#584)

* Docstrings revamp (#589)

* Rename `pyrootutils` to `rootutils` (#592)

* Fix `.log` being saved in project root dir instead of log dir (#588)

* Fix accelerator in `tests/test_train.py` (#595)

* Update Lightning DDP documentation links in `README.md` (#601)

* Fix `torch.compile` on `nn.module` instead of on `LightningModule` (#587)

* Update function arguments typing (#603)

* DDP-related improvements to datamodule and logging (#594)

* Dividing batch size by number of devices in MNISTDataModule's setup fn
* .log file is now the same across devices when training in a DDP setting
* Adding rank-aware pylogger

* Add FSDP support to `MNISTLitModule` (#604)

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Łukasz Zalewski <ashlevegalaxy@gmail.com>
Co-authored-by: Yiyao Wei <yiyao.wei@icloud.com>
Co-authored-by: Zhengyu Yang <25852061+zhengyu-yang@users.noreply.github.com>
Co-authored-by: Giuseppe Scriva <67858959+gscriva@users.noreply.github.com>
Co-authored-by: ashleve <zalewski.ukas@gmail.com>
Co-authored-by: Eungbean Lee <27231912+eungbean@users.noreply.github.com>
Co-authored-by: Charles Gaydon <11660435+CharlesGaydon@users.noreply.github.com>
Co-authored-by: Nils Werner <nils@hey.com>
Co-authored-by: Zhenyu Jiang <stevetod98@gmail.com>
Co-authored-by: charles <charlesguan94@gmail.com>
Co-authored-by: LEE HANBIN <hanbin@kakao.com>
Co-authored-by: Xin Hu <laohuxin@gmail.com>
Co-authored-by: Johnny <johnnync13@gmail.com>
Co-authored-by: lyp <38273833+yipliu@users.noreply.github.com>
Co-authored-by: yu-xiang-wang <104632366+yu-xiang-wang@users.noreply.github.com>
Co-authored-by: Eli Simhayev <elisimhayev@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Alexander Tong <alexandertongdev@gmail.com>
Co-authored-by: Yongtae723 <50616781+Yongtae723@users.noreply.github.com>
Co-authored-by: yangliz5 <yangyang.li@northwestern.edu>
Co-authored-by: Alex Morehead <alex.morehead@gmail.com>
Co-authored-by: Lukas <lukasz.zalewski.ai@gmail.com>
Co-authored-by: YuCao16 <62466929+YuCao16@users.noreply.github.com>
Co-authored-by: Guilherme Pires <mail@gpir.es>
Co-authored-by: Mattie Tesfaldet <tesfaldet@hotmail.com>
Co-authored-by: Mattie Tesfaldet <mattie@meta.com>
Co-authored-by: Johnny <johnnynuca14@gmail.com>
Co-authored-by: Yunchong Gan <yunchong@pku.edu.cn>
Co-authored-by: Théis Bazin <9104039+tbazin@users.noreply.github.com>
Co-authored-by: André Aquilina <32460579+dreaquil@users.noreply.github.com>
Co-authored-by: Stefan Geyer <git@caplett.com>
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

dependencies Pull requests that update a dependency file

Projects

None yet

Development

Successfully merging this pull request may close these issues.

1 participant