From 057f05f2b7f637d1e06cf840b5f97bc1cf8a3b2c Mon Sep 17 00:00:00 2001 From: Mauricio Villegas Date: Fri, 4 Jun 2021 06:43:43 +0100 Subject: [PATCH] Fix support for torch Module type hints in LightningCLI (#7807) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Fixed support for torch Module type hints in LightningCLI * - Fix issue with serializing values when type hint is Any. - Run unit test only on newer torchvision versions in which the base class is Module. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Minor change * Update CHANGELOG.md Co-authored-by: Carlos Mocholí Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Carlos Mocholí (cherry picked from commit f34584001c7a88aa7204ade4f0145ba109e5f1bc) --- CHANGELOG.md | 214 +++++++++++++++++++++++++++++++++--- requirements/extra.txt | 2 +- tests/utilities/test_cli.py | 54 +++++++++ 3 files changed, 252 insertions(+), 18 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 9e1517ebc2b36..cc9a903e855ab 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,186 @@ All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). +## [1.4.0] - 2021-MM-DD + +### Added + +- Added support to `LightningModule.to_torchscript` for saving to custom filesystems with fsspec ([#7617](https://github.com/PyTorchLightning/pytorch-lightning/pull/7617)) + + +- Added `KubeflowEnvironment` for use with the `PyTorchJob` operator in Kubeflow + + +- Added LightningCLI support for config files on object stores ([#7521](https://github.com/PyTorchLightning/pytorch-lightning/pull/7521)) + + +- Added `ModelPruning(prune_on_train_epoch_end=True|False)` to choose when to apply pruning ([#7704](https://github.com/PyTorchLightning/pytorch-lightning/pull/7704)) + + +- Added support for checkpointing based on a provided time interval during training ([#7515](https://github.com/PyTorchLightning/pytorch-lightning/pull/7515)) + + +- Added dataclasses for progress tracking ( + [#6603](https://github.com/PyTorchLightning/pytorch-lightning/pull/6603), + [#7574](https://github.com/PyTorchLightning/pytorch-lightning/pull/7574)) + + +- Added argument `trainer.predict(ckpt_path)` ([#7430](https://github.com/PyTorchLightning/pytorch-lightning/pull/7430)) + + +- Added `clip_grad_by_value` support for TPUs ([#7025](https://github.com/PyTorchLightning/pytorch-lightning/pull/7025)) + + +- Added `sub_dir` parameter to `TensorBoardLogger` ([#6195](https://github.com/PyTorchLightning/pytorch-lightning/pull/6195)) + + +- Added correct `dataloader_idx` to batch transfer hooks ([#6241](https://github.com/PyTorchLightning/pytorch-lightning/pull/6241)) + + +- Added `include_none=bool` argument to `apply_to_collection` ([#7769](https://github.com/PyTorchLightning/pytorch-lightning/pull/7769)) + + +- Added `apply_to_collections` to apply a function to two zipped collections ([#7769](https://github.com/PyTorchLightning/pytorch-lightning/pull/7769)) + + +- Added `ddp_fully_sharded` support ([#7487](https://github.com/PyTorchLightning/pytorch-lightning/pull/7487)) + + +- Added `__len__` to `IndexBatchSamplerWrapper` ([#7681](https://github.com/PyTorchLightning/pytorch-lightning/pull/7681)) + + +- Added `should_rank_save_checkpoint` property to Training Plugins ([#7684](https://github.com/PyTorchLightning/pytorch-lightning/pull/7684)) + + +- Added `save_config_filename` init argument to `LightningCLI` to ease resolving name conflicts ([#7741](https://github.com/PyTorchLightning/pytorch-lightning/pull/7741)) + + +### Changed + +- Changed calling of `untoggle_optimizer(opt_idx)` out of the closure function ([#7563](https://github.com/PyTorchLightning/pytorch-lightning/pull/7563) + +- Changed the `Trainer`'s `checkpoint_callback` argument to allow only boolean values ([#7539](https://github.com/PyTorchLightning/pytorch-lightning/pull/7539)) + + +- Log epoch metrics before the `on_evaluation_end` hook ([#7272](https://github.com/PyTorchLightning/pytorch-lightning/pull/7272)) + + +- Changed these `Trainer` methods to be protected: `call_setup_hook`, `call_configure_sharded_model`, `pre_dispatch`, `dispatch`, `post_dispatch`, `call_teardown_hook`, `run_train`, `run_sanity_check`, `run_evaluate`, `run_evaluation`, `run_predict`, `track_output_for_epoch_end` + + +- Changed `clip_grad_norm` to use `torch.nn.utils.clip_grad_norm_` ([#7025](https://github.com/PyTorchLightning/pytorch-lightning/pull/7025)) + + +- Validation is now always run inside the training epoch scope ([#7357](https://github.com/PyTorchLightning/pytorch-lightning/pull/7357)) + + +- Refactored Loops + * Moved attributes `global_step`, `current_epoch`, `max/min_steps`, `max/min_epochs`, `batch_idx`, and `total_batch_idx` to TrainLoop ([#7437](https://github.com/PyTorchLightning/pytorch-lightning/pull/7025)) + * Refactored result handling in training loop ([#7506](https://github.com/PyTorchLightning/pytorch-lightning/pull/7506)) + * Moved attributes `hiddens` and `split_idx` to TrainLoop ([#7507](https://github.com/PyTorchLightning/pytorch-lightning/pull/7507)) + * Refactored the logic around manual and automatic optimization inside the optimizer loop ([#7526](https://github.com/PyTorchLightning/pytorch-lightning/pull/7526)) + * Simplified "should run validation" logic ([#7682](https://github.com/PyTorchLightning/pytorch-lightning/pull/7682)) + * Refactored "should run validation" logic when the trainer is signaled to stop ([#7701](https://github.com/PyTorchLightning/pytorch-lightning/pull/7701)) + + +- Refactored logging + * Renamed and moved `core/step_result.py` to `trainer/connectors/logger_connector/result.py` ([#7736](https://github.com/PyTorchLightning/pytorch-lightning/pull/7736)) + + +- Moved `ignore_scalar_return_in_dp` warning suppression to the DataParallelPlugin class ([#7421](https://github.com/PyTorchLightning/pytorch-lightning/pull/7421/)) + + +- Changed the behaviour when logging evaluation step metrics to no longer append `/epoch_*` to the metric name ([#7351](https://github.com/PyTorchLightning/pytorch-lightning/pull/7351)) + + +- Raise `ValueError` when a `None` value is `self.log`-ed ([#7771](https://github.com/PyTorchLightning/pytorch-lightning/pull/7771)) + + +- Changed `resolve_training_type_plugins` to allow setting `num_nodes` and `sync_batchnorm` from `Trainer` setting ([#7026](https://github.com/PyTorchLightning/pytorch-lightning/pull/7026)) + + +- Default `seed_everything(workers=True)` in the `LightningCLI` ([#7504](https://github.com/PyTorchLightning/pytorch-lightning/pull/7504)) + + +- Changed `model.state_dict()` in `CheckpointConnector` to allow `training_type_plugin` to customize the model's `state_dict()` ([#7474](https://github.com/PyTorchLightning/pytorch-lightning/pull/7474)) + + +- MLflowLogger now uses the env variable `MLFLOW_TRACKING_URI` as default tracking uri ([#7457](https://github.com/PyTorchLightning/pytorch-lightning/pull/7457)) + + +- Changed `WandbLogger(log_model={True/'all'})` to log models as artifacts ([#6231](https://github.com/PyTorchLightning/pytorch-lightning/pull/6231)) +- MLFlowLogger now accepts `run_name` as an constructor argument ([#7622](https://github.com/PyTorchLightning/pytorch-lightning/issues/7622)) + + +- Changed `teardown()` in `Accelerator` to allow `training_type_plugin` to customize `teardown` logic ([#7579](https://github.com/PyTorchLightning/pytorch-lightning/pull/7579)) + + +- `Trainer.fit` now raises an error when using manual optimization with unsupported features such as `gradient_clip_val` or `accumulate_grad_batches` ([#7788](https://github.com/PyTorchLightning/pytorch-lightning/pull/7788)) + + +### Deprecated + + +- Deprecated `TrainerModelHooksMixin` in favor of `pytorch_lightning.utilities.signature_utils` ([#7422](https://github.com/PyTorchLightning/pytorch-lightning/pull/7422)) + + +- Deprecated `num_nodes` and `sync_batchnorm` arguments in `DDPPlugin` and `DDPSpawnPlugin` ([#7026](https://github.com/PyTorchLightning/pytorch-lightning/pull/7026)) + + +### Removed + +- Removed `ProfilerConnector` ([#7654](https://github.com/PyTorchLightning/pytorch-lightning/pull/7654)) + + +- Prune deprecated classif. metrics from `pytorch_lightning.metrics.functional.classification` ([#7499](https://github.com/PyTorchLightning/pytorch-lightning/pull/7499)) + + +- Removed deprecated data parallel classes `LightningDataParallel` and `LightningDistributedDataParallel` from `pytorch_lightning.overrides.data_parallel` ([#7510](https://github.com/PyTorchLightning/pytorch-lightning/pull/7510)) + + +- Removed deprecated trainer attributes - `get_model` and `accelerator_backend` ([#7502](https://github.com/PyTorchLightning/pytorch-lightning/pull/7502)) + + +- Removed support for `self.log(tbptt_reduce_fx)` and `self.log(tbptt_pad_token)`. Please, open a discussion explaining your use-case if you relied on these. ([#7644](https://github.com/PyTorchLightning/pytorch-lightning/pull/7644)) + + +- Removed deprecated utils modules `model_utils`, `warning_utils`, `xla_device_utils` and partially `argparse_utils` ([#7503](https://github.com/PyTorchLightning/pytorch-lightning/pull/7503)) + + +- Removed deprecated trainer attributes - `on_cpu`, `on_tpu`, `use_tpu`, `on_gpu`, `use_dp`, `use_ddp`, `use_ddp2`, `use_horovod`, `use_single_gpu` ([#7501](https://github.com/PyTorchLightning/pytorch-lightning/pull/7501)) + + +### Fixed + +- Fixed ambiguous warning when both overfit and train dataloader shuffling are enabled ([#7685](https://github.com/PyTorchLightning/pytorch-lightning/pull/7685)) + +- Fixed dataloaders are not reset when tuning the model ([#7566](https://github.com/PyTorchLightning/pytorch-lightning/pull/7566)) + + +- Fixed global step update when the epoch is skipped ([#7677](https://github.com/PyTorchLightning/pytorch-lightning/pull/7677)) + + +- Fixed training loop total batch counter when accumulate grad batches was enabled ([#7692](https://github.com/PyTorchLightning/pytorch-lightning/pull/7692)) + + +- Fixed broadcasting in multi-node, multi-gpu DDP using torch 1.7 ([#7592](https://github.com/PyTorchLightning/pytorch-lightning/pull/7592)) + + +- Fixed `ProgressBar` pickling after calling `trainer.predict` ([#7608](https://github.com/PyTorchLightning/pytorch-lightning/pull/7608)) + + +- Fixed `None` loss keys getting added in `training_epoch_end` when using manual optimization and not returning a loss ([#7772](https://github.com/PyTorchLightning/pytorch-lightning/pull/7772)) + + +- Fixed print errors in `ProgressBar` when `trainer.fit` is not called ([#7674](https://github.com/PyTorchLightning/pytorch-lightning/pull/7674)) + + +- Fixed formatting of info message when max training time reached ([#7780](https://github.com/PyTorchLightning/pytorch-lightning/pull/7780)) + + +- Fixed a bug where `precision=64` with `accelerator='ddp_spawn'` would throw a pickle error ([#6924](https://github.com/PyTorchLightning/pytorch-lightning/pull/6924)) + + ## [1.3.4] - 2021-06-01 ### Fixed @@ -41,8 +221,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - Fixed setting correct `DistribType` for `ddp_cpu` (spawn) backend ([#7492](https://github.com/PyTorchLightning/pytorch-lightning/pull/7492)) - Fixed incorrect number of calls to LR scheduler when `check_val_every_n_epoch > 1` ([#7032](https://github.com/PyTorchLightning/pytorch-lightning/pull/7032)) -## [1.3.1] - 2021-05-11 +## [1.3.1] - 2021-05-11 ### Fixed @@ -55,11 +235,11 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). ### Added -- Added support for the `EarlyStopping` callback to run at the end of the training epoch ([#6944](https://github.com/PyTorchLightning/pytorch-lightning/pull/6944/)) +- Added support for the `EarlyStopping` callback to run at the end of the training epoch ([#6944](https://github.com/PyTorchLightning/pytorch-lightning/pull/6944)) - Added synchronization points before and after `setup` hooks are run ([#7202](https://github.com/PyTorchLightning/pytorch-lightning/pull/7202)) - Added a `teardown` hook to `ClusterEnvironment` ([#6942](https://github.com/PyTorchLightning/pytorch-lightning/pull/6942)) - Added utils for metrics to scalar conversions ([#7180](https://github.com/PyTorchLightning/pytorch-lightning/pull/7180)) -- Added utils for NaN/Inf detection for gradients and parameters ([#6834](https://github.com/PyTorchLightning/pytorch-lightning/pull/6834/)) +- Added utils for NaN/Inf detection for gradients and parameters ([#6834](https://github.com/PyTorchLightning/pytorch-lightning/pull/6834)) - Added more explicit exception message when trying to execute `trainer.test()` or `trainer.validate()` with `fast_dev_run=True` ([#6667](https://github.com/PyTorchLightning/pytorch-lightning/pull/6667)) - Added `LightningCLI` class to provide simple reproducibility with minimum boilerplate training CLI ( [#4492](https://github.com/PyTorchLightning/pytorch-lightning/pull/4492), @@ -85,7 +265,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - Added `outputs` parameter to callback's `on_validation_epoch_end` & `on_test_epoch_end` hooks ([#6120](https://github.com/PyTorchLightning/pytorch-lightning/pull/6120)) - Added `configure_sharded_model` hook ([#6679](https://github.com/PyTorchLightning/pytorch-lightning/pull/6679)) - Added support for `precision=64`, enabling training with double precision ([#6595](https://github.com/PyTorchLightning/pytorch-lightning/pull/6595)) -- Added support for DDP communication hooks ([#6736](https://github.com/PyTorchLightning/pytorch-lightning/issues/6736)) +- Added support for DDP communication hooks ([#6736](https://github.com/PyTorchLightning/pytorch-lightning/pull/6736)) - Added `artifact_location` argument to `MLFlowLogger` which will be passed to the `MlflowClient.create_experiment` call ([#6677](https://github.com/PyTorchLightning/pytorch-lightning/pull/6677)) - Added `model` parameter to precision plugins' `clip_gradients` signature ( [#6764](https://github.com/PyTorchLightning/pytorch-lightning/pull/6764), @@ -104,14 +284,14 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - Added `tpu_distributed` check for TPU Spawn barrier ([#7241](https://github.com/PyTorchLightning/pytorch-lightning/pull/7241)) - Added device updates to TPU Spawn for Pod training ([#7243](https://github.com/PyTorchLightning/pytorch-lightning/pull/7243)) - Added warning when missing `Callback` and using `resume_from_checkpoint` ([#7254](https://github.com/PyTorchLightning/pytorch-lightning/pull/7254)) -- DeepSpeed single file saving ([#6900](https://github.com/PyTorchLightning/pytorch-lightning/issues/6900)) +- DeepSpeed single file saving ([#6900](https://github.com/PyTorchLightning/pytorch-lightning/pull/6900)) - Added Training type Plugins Registry ( - [#6982](https://github.com/PyTorchLightning/pytorch-lightning/issues/6982), - [#7063](https://github.com/PyTorchLightning/pytorch-lightning/issues/7063), - [#7214](https://github.com/PyTorchLightning/pytorch-lightning/issues/7214), - [#7224](https://github.com/PyTorchLightning/pytorch-lightning/issues/7224) + [#6982](https://github.com/PyTorchLightning/pytorch-lightning/pull/6982), + [#7063](https://github.com/PyTorchLightning/pytorch-lightning/pull/7063), + [#7214](https://github.com/PyTorchLightning/pytorch-lightning/pull/7214), + [#7224](https://github.com/PyTorchLightning/pytorch-lightning/pull/7224) ) -- Add `ignore` param to `save_hyperparameters` ([#6056](https://github.com/PyTorchLightning/pytorch-lightning/issues/6056)) +- Add `ignore` param to `save_hyperparameters` ([#6056](https://github.com/PyTorchLightning/pytorch-lightning/pull/6056)) ### Changed @@ -129,7 +309,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - The trainer no longer tries to save a checkpoint on exception or run callback's `on_train_end` functions ([#6864](https://github.com/PyTorchLightning/pytorch-lightning/pull/6864)) - Changed `PyTorchProfiler` to use `torch.autograd.profiler.record_function` to record functions ([#6349](https://github.com/PyTorchLightning/pytorch-lightning/pull/6349)) - Disabled `lr_scheduler.step()` in manual optimization ([#6825](https://github.com/PyTorchLightning/pytorch-lightning/pull/6825)) -- Changed warnings and recommendations for dataloaders in `ddp_spawn` ([#6762](https://github.com/PyTorchLightning/pytorch-lightning/pull/6762/)) +- Changed warnings and recommendations for dataloaders in `ddp_spawn` ([#6762](https://github.com/PyTorchLightning/pytorch-lightning/pull/6762)) - `pl.seed_everything` will now also set the seed on the `DistributedSampler` ([#7024](https://github.com/PyTorchLightning/pytorch-lightning/pull/7024)) - Changed default setting for communication of multi-node training using `DDPShardedPlugin` ([#6937](https://github.com/PyTorchLightning/pytorch-lightning/pull/6937)) - `trainer.tune()` now returns the tuning result ([#7258](https://github.com/PyTorchLightning/pytorch-lightning/pull/7258)) @@ -164,7 +344,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - Deprecated the `save_function` property from the `ModelCheckpoint` callback ([#7201](https://github.com/PyTorchLightning/pytorch-lightning/pull/7201)) - Deprecated `LightningModule.write_predictions` and `LightningModule.write_predictions_dict` ([#7066](https://github.com/PyTorchLightning/pytorch-lightning/pull/7066)) - Deprecated `TrainerLoggingMixin` in favor of a separate utilities module for metric handling ([#7180](https://github.com/PyTorchLightning/pytorch-lightning/pull/7180)) -- Deprecated `TrainerTrainingTricksMixin` in favor of a separate utilities module for NaN/Inf detection for gradients and parameters ([#6834](https://github.com/PyTorchLightning/pytorch-lightning/pull/6834/)) +- Deprecated `TrainerTrainingTricksMixin` in favor of a separate utilities module for NaN/Inf detection for gradients and parameters ([#6834](https://github.com/PyTorchLightning/pytorch-lightning/pull/6834)) - `period` has been deprecated in favor of `every_n_val_epochs` in the `ModelCheckpoint` callback ([#6146](https://github.com/PyTorchLightning/pytorch-lightning/pull/6146)) - Deprecated `trainer.running_sanity_check` in favor of `trainer.sanity_checking` ([#4945](https://github.com/PyTorchLightning/pytorch-lightning/pull/4945)) - Deprecated `Profiler(output_filename)` in favor of `dirpath` and `filename` ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621)) @@ -270,7 +450,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - Fixed auto-scaling mode when calling tune method on trainer ([#7321](https://github.com/PyTorchLightning/pytorch-lightning/pull/7321)) - Fixed finetuning complex models correctly unfreezes ([#6880](https://github.com/PyTorchLightning/pytorch-lightning/pull/6880)) - Ensure we set the eval/train flag correctly on accelerator model ([#6877](https://github.com/PyTorchLightning/pytorch-lightning/pull/6877)) -- Set better defaults for `rank_zero_only.rank` when training is launched with SLURM and torchelastic ([#6802](https://github.com/PyTorchLightning/pytorch-lightning/pull/6802/)) +- Set better defaults for `rank_zero_only.rank` when training is launched with SLURM and torchelastic ([#6802](https://github.com/PyTorchLightning/pytorch-lightning/pull/6802)) - Fixed matching the number of outputs of backward with forward for AllGatherGrad ([#6625](https://github.com/PyTorchLightning/pytorch-lightning/pull/6625)) - Fixed the `gradient_clip_algorithm` has no effect ([#6928](https://github.com/PyTorchLightning/pytorch-lightning/pull/6928)) - Fixed CUDA OOM detection and handling ([#6934](https://github.com/PyTorchLightning/pytorch-lightning/pull/6934)) @@ -486,7 +666,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - Changed `computer_vision_fine_tunning` example to use `BackboneLambdaFinetuningCallback` ([#5377](https://github.com/PyTorchLightning/pytorch-lightning/pull/5377)) - Changed `automatic casting` for LoggerConnector `metrics` ([#5218](https://github.com/PyTorchLightning/pytorch-lightning/pull/5218)) - Changed `iou` [func] to allow float input ([#4704](https://github.com/PyTorchLightning/pytorch-lightning/pull/4704)) -- Metric `compute()` method will no longer automatically call `reset()` ([#5409](https://github.com/PyTorchLightning/pytorch-lightning/pull/5409/)) +- Metric `compute()` method will no longer automatically call `reset()` ([#5409](https://github.com/PyTorchLightning/pytorch-lightning/pull/5409)) - Set PyTorch 1.4 as min requirements, also for testing and examples `torchvision>=0.5` and `torchtext>=0.5` ([#5418](https://github.com/PyTorchLightning/pytorch-lightning/pull/5418)) - Changed `callbacks` argument in `Trainer` to allow `Callback` input ([#5446](https://github.com/PyTorchLightning/pytorch-lightning/pull/5446)) - Changed the default of `find_unused_parameters` to `False` in DDP ([#5185](https://github.com/PyTorchLightning/pytorch-lightning/pull/5185)) @@ -1253,7 +1433,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - Fixed getting `experiment_id` from MLFlow only once instead of each training loop ([#3394](https://github.com/PyTorchLightning/pytorch-lightning/pull/3394)) - Fixed `overfit_batches` which now correctly disables shuffling for the training loader. ([#3501](https://github.com/PyTorchLightning/pytorch-lightning/pull/3501)) - Fixed gradient norm tracking for `row_log_interval > 1` ([#3489](https://github.com/PyTorchLightning/pytorch-lightning/pull/3489)) -- Fixed `ModelCheckpoint` name formatting ([3164](https://github.com/PyTorchLightning/pytorch-lightning/pull/3163)) +- Fixed `ModelCheckpoint` name formatting ([#3164](https://github.com/PyTorchLightning/pytorch-lightning/pull/3163)) - Fixed example implementation of AutoEncoder ([#3190](https://github.com/PyTorchLightning/pytorch-lightning/pull/3190)) - Fixed invalid paths when remote logging with TensorBoard ([#3236](https://github.com/PyTorchLightning/pytorch-lightning/pull/3236)) - Fixed change `t()` to `transpose()` as XLA devices do not support `.t()` on 1-dim tensor ([#3252](https://github.com/PyTorchLightning/pytorch-lightning/pull/3252)) @@ -1513,8 +1693,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). - Added option `save_last` to save the model at the end of every epoch in `ModelCheckpoint` ([#1908](https://github.com/PyTorchLightning/pytorch-lightning/pull/1908)) - Early stopping checks `on_validation_end` ([#1458](https://github.com/PyTorchLightning/pytorch-lightning/pull/1458)) - Speed up single-core TPU training by loading data using `ParallelLoader` ([#2033](https://github.com/PyTorchLightning/pytorch-lightning/pull/2033)) -- Added a model hook `transfer_batch_to_device` that enables moving custom data structures to the target device ([1756](https://github.com/PyTorchLightning/pytorch-lightning/pull/1756)) -- Added [black](https://black.readthedocs.io/en/stable/) formatter for the code with code-checker on pull ([1610](https://github.com/PyTorchLightning/pytorch-lightning/pull/1610)) +- Added a model hook `transfer_batch_to_device` that enables moving custom data structures to the target device ([#1756](https://github.com/PyTorchLightning/pytorch-lightning/pull/1756)) +- Added [black](https://black.readthedocs.io/en/stable/) formatter for the code with code-checker on pull ([#1610](https://github.com/PyTorchLightning/pytorch-lightning/pull/1610)) - Added back the slow spawn ddp implementation as `ddp_spawn` ([#2115](https://github.com/PyTorchLightning/pytorch-lightning/pull/2115)) - Added loading checkpoints from URLs ([#1667](https://github.com/PyTorchLightning/pytorch-lightning/pull/1667)) - Added a callback method `on_keyboard_interrupt` for handling KeyboardInterrupt events during training ([#2134](https://github.com/PyTorchLightning/pytorch-lightning/pull/2134)) diff --git a/requirements/extra.txt b/requirements/extra.txt index db2e66540eef1..cb9515beefb9a 100644 --- a/requirements/extra.txt +++ b/requirements/extra.txt @@ -7,4 +7,4 @@ torchtext>=0.5 # onnx>=1.7.0 onnxruntime>=1.3.0 hydra-core>=1.0 -jsonargparse[signatures]>=3.11.1 +jsonargparse[signatures]>=3.13.1 diff --git a/tests/utilities/test_cli.py b/tests/utilities/test_cli.py index 5780a83e75db8..c1eabca5d663d 100644 --- a/tests/utilities/test_cli.py +++ b/tests/utilities/test_cli.py @@ -20,18 +20,26 @@ from argparse import Namespace from contextlib import redirect_stdout from io import StringIO +from typing import List, Optional from unittest import mock import pytest +import torch import yaml +from packaging import version from pytorch_lightning import LightningDataModule, LightningModule, Trainer from pytorch_lightning.callbacks import LearningRateMonitor, ModelCheckpoint from pytorch_lightning.plugins.environments import SLURMEnvironment from pytorch_lightning.utilities import _TPU_AVAILABLE from pytorch_lightning.utilities.cli import LightningArgumentParser, LightningCLI, SaveConfigCallback +from pytorch_lightning.utilities.imports import _TORCHVISION_AVAILABLE from tests.helpers import BoringDataModule, BoringModel +torchvision_version = version.parse('0') +if _TORCHVISION_AVAILABLE: + torchvision_version = version.parse(__import__('torchvision').__version__) + @mock.patch('argparse.ArgumentParser.parse_args') def test_default_args(mock_argparse, tmpdir): @@ -443,3 +451,49 @@ def __init__( assert cli.model.submodule2 == cli.config_init['model']['submodule2'] assert isinstance(cli.config_init['model']['submodule1'], BoringModel) assert isinstance(cli.config_init['model']['submodule2'], BoringModel) + + +@pytest.mark.skipif(torchvision_version < version.parse('0.8.0'), reason='torchvision>=0.8.0 is required') +def test_lightning_cli_torch_modules(tmpdir): + + class TestModule(BoringModel): + + def __init__( + self, + activation: torch.nn.Module = None, + transform: Optional[List[torch.nn.Module]] = None, + ): + super().__init__() + self.activation = activation + self.transform = transform + + config = """model: + activation: + class_path: torch.nn.LeakyReLU + init_args: + negative_slope: 0.2 + transform: + - class_path: torchvision.transforms.Resize + init_args: + size: 64 + - class_path: torchvision.transforms.CenterCrop + init_args: + size: 64 + """ + config_path = tmpdir / 'config.yaml' + with open(config_path, 'w') as f: + f.write(config) + + cli_args = [ + f'--trainer.default_root_dir={tmpdir}', + '--trainer.max_epochs=1', + f'--config={str(config_path)}', + ] + + with mock.patch('sys.argv', ['any.py'] + cli_args): + cli = LightningCLI(TestModule) + + assert isinstance(cli.model.activation, torch.nn.LeakyReLU) + assert cli.model.activation.negative_slope == 0.2 + assert len(cli.model.transform) == 2 + assert all(isinstance(v, torch.nn.Module) for v in cli.model.transform)