Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[TPU] update is_tpu_exists utils internal logic to rely on xmp.spawn #6719

Merged
merged 12 commits into from
Mar 29, 2021
Merged

[TPU] update is_tpu_exists utils internal logic to rely on xmp.spawn #6719

merged 12 commits into from
Mar 29, 2021

Conversation

tchaton
Copy link
Contributor

@tchaton tchaton commented Mar 29, 2021 •
edited by carmocca
Loading

What does this PR do?

c.f title.

Fixes #6692

Before submitting

  • Was this discussed/approved via a GitHub issue? (not for typos and docs)
  • Did you read the contributor guideline, Pull Request section?
  • Did you make sure your PR does only one thing, instead of bundling different changes together?
  • Did you make sure to update the documentation with your changes? (if necessary)
  • Did you write any new necessary tests? (not for typos and docs)
  • Did you verify new and existing tests pass locally with your changes?
  • Did you update the CHANGELOG? (not for typos, docs, test updates, or internal minor changes/refactorings)

PR review

Anyone in the community is free to review the PR once the tests have passed.
Before you start reviewing make sure you have read Review guidelines. In short, see the following bullet-list:

  • Is this pull request ready for review? (if not, please submit in draft mode)
  • Check that all items from Before submitting are resolved
  • Make sure the title is self-explanatory and the description concisely explains the PR
  • Add labels and milestones (and optionally projects) to the PR so it can be classified

Did you have fun?

Make sure you had fun coding 🙃

Your Name and others added 2 commits March 29, 2021 11:29
@tchaton tchaton self-assigned this Mar 29, 2021
@tchaton tchaton added this to the 1.2.x milestone Mar 29, 2021
@tchaton tchaton changed the title [TPU] Update is_tpu_exists utils to rely on spawn [TPU] update is_tpu_exists utils internal logic to rely on xmp.spawn Mar 29, 2021
kaushikb11
kaushikb11 approved these changes Mar 29, 2021
View reviewed changes
Copy link
Contributor

@kaushikb11 kaushikb11 left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM!

@codecov
Copy link

codecov bot commented Mar 29, 2021 •
edited
Loading

Codecov Report

Merging #6719 (40015dd) into master (dcf6e4e) will decrease coverage by 5%.
The diff coverage is 50%.

@@           Coverage Diff           @@
##           master   #6719    +/-   ##
=======================================
- Coverage      91%     87%    -5%     
=======================================
  Files         192     192            
  Lines       12175   12225    +50     
=======================================
- Hits        11129   10589   -540     
- Misses       1046    1636   +590

carmocca
carmocca approved these changes Mar 29, 2021
View reviewed changes
tests/utilities/test_xla_device_utils.py Outdated Show resolved Hide resolved
@carmocca
Copy link
Contributor

Test failures are real @tchaton

@tchaton tchaton enabled auto-merge (squash) March 29, 2021 16:20
@carmocca carmocca added ready PRs ready to be merged bug Something isn't working accelerator: tpu Tensor Processing Unit labels Mar 29, 2021
@tchaton tchaton merged commit 3a4c424 into master Mar 29, 2021
@tchaton tchaton deleted the is_tpu_exists branch March 29, 2021 17:59
@carmocca carmocca mentioned this pull request Mar 29, 2021
Closed
carmocca added a commit that referenced this pull request Mar 29, 2021
@tchaton @kaushikb11 @carmocca
[TPU] update is_tpu_exists utils internal logic to rely on xmp.spawn (#…
c700590 
…6719)

* update_logic

* update

* Update tests/utilities/test_xla_device_utils.py

* Update pytorch_lightning/utilities/xla_device.py

Co-authored-by: Kaushik B <[email protected]>

* Update pytorch_lightning/utilities/xla_device.py

Co-authored-by: Kaushik B <[email protected]>

* update test

* Update tests/utilities/test_xla_device_utils.py

* update

* Apply fix

* Docstring

* flake8

* update

Co-authored-by: Your Name <[email protected]>
Co-authored-by: Kaushik B <[email protected]>
Co-authored-by: Carlos Mocholi <[email protected]>
Borda pushed a commit that referenced this pull request Mar 30, 2021
@tchaton @kaushikb11
@carmocca @Borda
[TPU] update is_tpu_exists utils internal logic to rely on xmp.spawn (#…
67d4749 
…6719)

* update_logic

* update

* Update tests/utilities/test_xla_device_utils.py

* Update pytorch_lightning/utilities/xla_device.py

Co-authored-by: Kaushik B <[email protected]>

* Update pytorch_lightning/utilities/xla_device.py

Co-authored-by: Kaushik B <[email protected]>

* update test

* Update tests/utilities/test_xla_device_utils.py

* update

* Apply fix

* Docstring

* flake8

* update

Co-authored-by: Your Name <[email protected]>
Co-authored-by: Kaushik B <[email protected]>
Co-authored-by: Carlos Mocholi <[email protected]>
lexierule pushed a commit that referenced this pull request Mar 30, 2021
@tchaton @kaushikb11
@carmocca @lexierule
[TPU] update is_tpu_exists utils internal logic to rely on xmp.spawn (#…
aa92c4c 
…6719)

* update_logic

* update

* Update tests/utilities/test_xla_device_utils.py

* Update pytorch_lightning/utilities/xla_device.py

Co-authored-by: Kaushik B <[email protected]>

* Update pytorch_lightning/utilities/xla_device.py

Co-authored-by: Kaushik B <[email protected]>

* update test

* Update tests/utilities/test_xla_device_utils.py

* update

* Apply fix

* Docstring

* flake8

* update

Co-authored-by: Your Name <[email protected]>
Co-authored-by: Kaushik B <[email protected]>
Co-authored-by: Carlos Mocholi <[email protected]>
@jiasenwu jiasenwu mentioned this pull request Mar 30, 2021
Closed
11 tasks
facebook-github-bot pushed a commit to facebookresearch/d2go that referenced this pull request Apr 14, 2021
@facebook-github-bot
Synchronize PyTorchLightning/pytorch-lightning (revision 0b843848@mas…
44e4108 
…ter) to github/third-party/PyTorchLightning/pytorch-lightning

Summary:
### New commit log messages
## [UnReleased] - 2021-MM-DD

### Added

- Added more explicit exception message when trying to execute `trainer.test()` or `trainer.validate()` with `fast_dev_run=True` ([#6667](Lightning-AI/pytorch-lightning#6667))

- Added `LightningCLI` class to provide simple reproducibility with minimum boilerplate training cli. ([#4492](Lightning-AI/pytorch-lightning#4492))

- Trigger warning when non-metric logged value with multi processes hasn't been reduced ([#6417](Lightning-AI/pytorch-lightning#6417))

- Added `gradient_clip_algorithm` argument to Trainer for gradient clipping by value ([#6123](Lightning-AI/pytorch-lightning#6123)).

- Added a way to print to terminal without breaking up the progress bar ([#5470](Lightning-AI/pytorch-lightning#5470))

- Added support to checkpoint after training steps in `ModelCheckpoint` callback ([#6146](Lightning-AI/pytorch-lightning#6146))

- Added `checkpoint` parameter to callback's `on_save_checkpoint` hook ([#6072](Lightning-AI/pytorch-lightning#6072))

- Added `RunningStage.SANITY_CHECKING` ([#4945](Lightning-AI/pytorch-lightning#4945))

- Added `TrainerState.{FITTING,VALIDATING,TESTING,PREDICTING,TUNING}` ([#4945](Lightning-AI/pytorch-lightning#4945))

- Added `Trainer.validate()` method to perform one evaluation epoch over the validation set ([#4948](Lightning-AI/pytorch-lightning#4948))

- Added `LightningEnvironment` for Lightning-specific DDP ([#5915](Lightning-AI/pytorch-lightning#5915))

- Added `teardown()` hook to LightningDataModule ([#4673](Lightning-AI/pytorch-lightning#4673))

- Added `auto_insert_metric_name` parameter to `ModelCheckpoint` ([#6277](Lightning-AI/pytorch-lightning#6277))

- Added arg to `self.log` that enables users to give custom names when dealing with multiple dataloaders ([#6274](Lightning-AI/pytorch-lightning#6274))

- Added `teardown` method to `BaseProfiler` to enable subclasses defining post-profiling steps outside of `__del__` ([#6370](Lightning-AI/pytorch-lightning#6370))

- Added `setup` method to `BaseProfiler` to enable subclasses defining pre-profiling steps for every process ([#6633](Lightning-AI/pytorch-lightning#6633))

- Added no return warning to predict ([#6139](Lightning-AI/pytorch-lightning#6139))

- Added `Trainer.predict` config validation ([#6543](Lightning-AI/pytorch-lightning#6543))

- Added `AbstractProfiler` interface ([#6621](Lightning-AI/pytorch-lightning#6621))

- Added support for including module names for forward in the autograd trace of `PyTorchProfiler` ([#6349](Lightning-AI/pytorch-lightning#6349))

- Added support for the PyTorch 1.8.1 autograd profiler ([#6618](Lightning-AI/pytorch-lightning#6618))

- Added `outputs` parameter to callback's `on_validation_epoch_end` & `on_test_epoch_end` hooks ([#6120](Lightning-AI/pytorch-lightning#6120))

- Added `configure_sharded_model` hook ([#6679](Lightning-AI/pytorch-lightning#6679))

- Added support for `precision=64`, enabling training with double precision ([#6595](Lightning-AI/pytorch-lightning#6595))

- Added support for DDP communication hooks ([#6736](Lightning-AI/pytorch-lightning#6736))

- Added `artifact_location` argument to `MLFlowLogger` which will be passed to the `MlflowClient.create_experiment` call ([#6677](Lightning-AI/pytorch-lightning#6677))

- Added `model` parameter to precision plugins' `clip_gradients` signature ([#6764](Lightning-AI/pytorch-lightning#6764))

### Changed

- Renamed `pytorch_lightning.callbacks.swa` to `pytorch_lightning.callbacks.stochastic_weight_avg` ([#6259](Lightning-AI/pytorch-lightning#6259))

- Refactor `RunningStage` and `TrainerState` usage ([#4945](Lightning-AI/pytorch-lightning#4945))

- Changed `trainer.evaluating` to return `True` if validating or testing ([#4945](Lightning-AI/pytorch-lightning#4945))

- Changed `setup()` and `teardown()` stage argument to take any of `{fit,validate,test,predict}` ([#6386](Lightning-AI/pytorch-lightning#6386))

- Changed profilers to save separate report files per state and rank ([#6621](Lightning-AI/pytorch-lightning#6621))

- Changed `PyTorchProfiler` to use `torch.autograd.profiler.record_function` to record functions ([#6349](Lightning-AI/pytorch-lightning#6349))

### Deprecated

- `period` has been deprecated in favor of `every_n_val_epochs` in the `ModelCheckpoint` callback ([#6146](Lightning-AI/pytorch-lightning#6146))

- Deprecated `trainer.running_sanity_check` in favor of `trainer.sanity_checking` ([#4945](Lightning-AI/pytorch-lightning#4945))

- Deprecated `Profiler(output_filename)` in favor of `dirpath` and `filename` ([#6621](Lightning-AI/pytorch-lightning#6621))

- Deprecated `PytorchProfiler(profiled_functions)` in favor of `record_functions` ([#6349](Lightning-AI/pytorch-lightning#6349))

- Deprecated metrics in favor of `torchmetrics` ([#6505](Lightning-AI/pytorch-lightning#6505),
    [#6530](Lightning-AI/pytorch-lightning#6530),
    [#6540](Lightning-AI/pytorch-lightning#6540),
    [#6547](Lightning-AI/pytorch-lightning#6547),
    [#6515](Lightning-AI/pytorch-lightning#6515),
    [#6572](Lightning-AI/pytorch-lightning#6572),
    [#6573](Lightning-AI/pytorch-lightning#6573),
    [#6584](Lightning-AI/pytorch-lightning#6584),
    [#6636](Lightning-AI/pytorch-lightning#6636),
    [#6637](Lightning-AI/pytorch-lightning#6637),
    [#6649](Lightning-AI/pytorch-lightning#6649),
    [#6659](Lightning-AI/pytorch-lightning#6659),
)

### Removed

- Removed support for passing a bool value to `profiler` argument of Trainer ([#6164](Lightning-AI/pytorch-lightning#6164))

- Removed no return warning from val/test step ([#6139](Lightning-AI/pytorch-lightning#6139))

- Removed passing a `ModelCheckpoint` instance to `Trainer(checkpoint_callback)` ([#6166](Lightning-AI/pytorch-lightning#6166))

- Removed deprecated Trainer argument `enable_pl_optimizer` and `automatic_optimization` ([#6163](Lightning-AI/pytorch-lightning#6163))

- Removed deprecated metrics ([#6161](Lightning-AI/pytorch-lightning#6161))
    * from `pytorch_lightning.metrics.functional.classification` removed `to_onehot`, `to_categorical`, `get_num_classes`, `roc`, `multiclass_roc`, `average_precision`, `precision_recall_curve`, `multiclass_precision_recall_curve`
    * from `pytorch_lightning.metrics.functional.reduction` removed `reduce`, `class_reduce`

- Removed deprecated `ModelCheckpoint` arguments `prefix`, `mode="auto"` ([#6162](Lightning-AI/pytorch-lightning#6162))

- Removed `mode='auto'` from `EarlyStopping` ([#6167](Lightning-AI/pytorch-lightning#6167))

- Removed legacy references for magic keys in the `Result` object ([#6016](Lightning-AI/pytorch-lightning#6016))

- Removed deprecated `LightningModule` `hparams` setter ([#6207](Lightning-AI/pytorch-lightning#6207))

- Removed legacy code to log or include metrics in the progress bar by returning them in a dict with the `"log"/"progress_bar"` magic keys. Use `self.log` instead ([#6734](Lightning-AI/pytorch-lightning#6734))

- Removed `optimizer_idx` argument from `training_step` in manual optimization ([#6093](Lightning-AI/pytorch-lightning#6093))

### Fixed

- Set better defaults for `rank_zero_only.rank` when training is launched with SLURM and torchelastic ([#6802](Lightning-AI/pytorch-lightning#6802))

- Made the `Plugin.reduce` method more consistent across all Plugins to reflect a mean-reduction by default ([#6011](Lightning-AI/pytorch-lightning#6011))

- Move lightning module to correct device type when using LightningDistributedWrapper ([#6070](Lightning-AI/pytorch-lightning#6070))

- Do not print top-k verbose log with `ModelCheckpoint(monitor=None)` ([#6109](Lightning-AI/pytorch-lightning#6109))

- Fixed csv extension check ([#6436](Lightning-AI/pytorch-lightning#6436))

- Fixed `ModelCheckpoint(monitor=None, save_last=True)` not saving checkpoints ([#6136](Lightning-AI/pytorch-lightning#6136))

- Fixed `ModelCheckpoint(save_top_k=0, save_last=True)` not saving the `last` checkpoint ([#6136](Lightning-AI/pytorch-lightning#6136))

- Fixed `.teardown(stage='fit')` getting called during `trainer.test` ([#6386](Lightning-AI/pytorch-lightning#6386))

- Fixed `.on_fit_{start,end}()` getting called during `trainer.test` ([#6386](Lightning-AI/pytorch-lightning#6386))

- Fixed LightningModule `all_gather` on cpu tensors ([#6416](Lightning-AI/pytorch-lightning#6416))

- Fixed torch distributed not available in setup hook for DDP ([#6506](Lightning-AI/pytorch-lightning#6506))

- Fixed `EarlyStopping` logic when `min_epochs` or `min_steps` requirement is not met ([#6705](Lightning-AI/pytorch-lightning#6705))

## [1.2.7] - 2021-04-06

### Fixed

- Fixed resolve a bug with omegaconf and xm.save ([#6741](Lightning-AI/pytorch-lightning#6741))
- Fixed an issue with IterableDataset when __len__ is not defined ([#6828](Lightning-AI/pytorch-lightning#6828))
- Sanitize None params during pruning ([#6836](Lightning-AI/pytorch-lightning#6836))
- Enforce an epoch scheduler interval when using SWA ([#6588](Lightning-AI/pytorch-lightning#6588))
- Fixed TPU Colab hang issue, post training ([#6816](Lightning-AI/pytorch-lightning#6816))
- Fixed a bug where `TensorBoardLogger` would give a warning and not log correctly to a symbolic link `save_dir` ([#6730](Lightning-AI/pytorch-lightning#6730))

## [1.2.6] - 2021-03-30

### Changed

- Changed the behavior of `on_epoch_start` to run at the beginning of validation & test epoch ([#6498](Lightning-AI/pytorch-lightning#6498))

### Removed

- Removed legacy code to include `step` dictionary returns in `callback_metrics`. Use `self.log_dict` instead. ([#6682](Lightning-AI/pytorch-lightning#6682))

### Fixed

- Fixed `DummyLogger.log_hyperparams` raising a `TypeError` when running with `fast_dev_run=True` ([#6398](Lightning-AI/pytorch-lightning#6398))
- Fixed error on TPUs when there was no `ModelCheckpoint` ([#6654](Lightning-AI/pytorch-lightning#6654))
- Fixed `trainer.test` freeze on TPUs ([#6654](Lightning-AI/pytorch-lightning#6654))
- Fixed a bug where gradients were disabled after calling `Trainer.predict` ([#6657](Lightning-AI/pytorch-lightning#6657))
- Fixed bug where no TPUs were detected in a TPU pod env ([#6719](Lightning-AI/pytorch-lightning#6719))

## [1.2.5] - 2021-03-23

### Changed

- Update Gradient Clipping for the TPU Accelerator ([#6576](Lightning-AI/pytorch-lightning#6576))
- Refactored setup for typing friendly ([#6590](Lightning-AI/pytorch-lightning#6590))

### Fixed

- Fixed a bug where `all_gather` would not work correctly with `tpu_cores=8` ([#6587](Lightning-AI/pytorch-lightning#6587))
- Fixed comparing required versions ([#6434](Lightning-AI/pytorch-lightning#6434))
- Fixed duplicate logs appearing in console when using the python logging module ([#6275](Lightning-AI/pytorch-lightning#6275))
- Added Autocast in validation, test and predict modes for Native AMP ([#6565](Lightning-AI/pytorch-lightning#6565))

Reviewed By: shuyingsunshine21

Differential Revision: D27528929

fbshipit-source-id: 311c88f71461c2c79bbf185e28d7a6d683ccc26f
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Reviewers

@kaushikb11 kaushikb11 kaushikb11 approved these changes

@carmocca carmocca carmocca approved these changes

@SeanNaren SeanNaren SeanNaren approved these changes

@awaelchli awaelchli Awaiting requested review from awaelchli

@Borda Borda Awaiting requested review from Borda Borda is a code owner

@justusschock justusschock Awaiting requested review from justusschock justusschock is a code owner

@williamFalcon williamFalcon Awaiting requested review from williamFalcon

Assignees

@tchaton tchaton

Labels
accelerator: tpu Tensor Processing Unit bug Something isn't working ready PRs ready to be merged
Projects
None yet
Milestone
pl:1.2.x
Development

Successfully merging this pull request may close these issues.

No TPU devices were found in a TPU pod env.
4 participants
@tchaton @carmocca @SeanNaren @kaushikb11