Standard weekly patch release

[1.1.6] - 2021-01-26

Changed

• Increased TPU check timeout from 20s to 100s (#5598)
• Ignored step param in Neptune logger's log_metric method (#5510)
• Pass batch outputs to on_train_batch_end instead of epoch_end outputs (#4369)

Fixed

• Fixed toggle_optimizer to reset requires_grad state (#5574)
• Fixed FileNotFoundError for best checkpoint when using DDP with Hydra (#5629)
• Fixed an error when logging a progress bar metric with a reserved name (#5620)
• Fixed Metric's state_dict not included when child modules (#5614)
• Fixed Neptune logger creating multiple experiments when GPUs > 1 (#3256)
• Fixed duplicate logs appearing in console when using the python logging module (#5509)
• Fixed tensor printing in trainer.test() (#5138)
• Fixed not using dataloader when hparams present (#4559)

Contributors

@awaelchli @bryant1410 @lezwon @manipopopo @PiotrJander @psinger @rnett @SeanNaren @swethmandava @tchaton

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Standard weekly patch release

[1.1.5] - 2021-01-19

Fixed

• Fixed a visual bug in the progress bar display initialization (#4579)
• Fixed logging on_train_batch_end in a callback with multiple optimizers (#5521)
• Fixed reinit_scheduler_properties with correct optimizer (#5519)
• Fixed val_check_interval with fast_dev_run (#5540)

Contributors

@awaelchli, @carmocca, @rohitgr7

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Standard weekly patch release

[1.1.4] - 2021-01-12

Added

• Add automatic optimization property setter to lightning module (#5169)

Changed

• Changed deprecated enable_pl_optimizer=True (#5244)

Fixed

• Fixed transfer_batch_to_device for DDP with len(devices_ids) == 1 (#5195)
• Logging only on not should_accumulate() during training (#5417)
• Resolve interpolation bug with Hydra (#5406)
• Check environ before selecting a seed to prevent warning message (#4743)

Contributors

@ananthsub, @SeanNaren, @tchaton

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Standard weekly patch release

[1.1.3] - 2021-01-05

Added

• Added a check for optimizer attached to lr_scheduler (#5338)
• Added support for passing non-existing filepaths to resume_from_checkpoint (#4402)

Changed

• Skip restore from resume_from_checkpoint while testing (#5161)
• Allowed log_momentum for adaptive optimizers in LearningRateMonitor (#5333)
• Disabled checkpointing, earlystopping and logging with fast_dev_run (#5277)
• Distributed group defaults to WORLD if None (#5125)

Fixed

• Fixed trainer.test returning non-test metrics (#5214)
• Fixed metric state reset (#5273)
• Fixed --num-nodes on DDPSequentialPlugin (#5327)
• Fixed invalid value for weights_summary (#5296)
• Fixed Trainer.test not using the latest best_model_path (#5161)
• Fixed existence check for hparams not using underlying filesystem (#5250)
• Fixed LightningOptimizer AMP bug (#5191)
• Fixed casted key to string in _flatten_dict (#5354)

Contributors

@8greg8, @haven-jeon, @kandluis, @marload, @rohitgr7, @tadejsv, @tarepan, @tchaton

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standard weekly patch release

Overview

Detail changes

Added

• Support number for logging with sync_dist=True (#5080)
• Added offset logging step when resuming for Wandb logger (#5050)

Removed

• enable_pl_optimizer=False by default to temporarily fix AMP issues (#5163)

Fixed

• Metric reduction with Logging (#5150)
• Remove nan loss in manual optimization (#5121)
• Un-balanced logging properly supported (#5119)
• Fix hanging in DDP HPC accelerators (#5157)
• Fix saved filename in ModelCheckpoint if it already exists (#4861)
• Fix reset TensorRunningAccum (#5106)
• Updated DALIClassificationLoader to not use deprecated arguments (#4925)
• Corrected call to torch.no_grad (#5124)

Contributors

@8greg8, @ananthsub, @borisdayma, @gan3sh500, @rohitgr7, @SeanNaren, @tchaton, @VinhLoiIT

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standard weekly patch release

Overview

Detail changes

Added

• Add a notebook example to reach a quick baseline of ~94% accuracy on CIFAR10 using Resnet in Lightning (#4818)

Changed

• Simplify accelerator steps (#5015)
• Refactor load in checkpoint connector (#4593)

Removed

• Drop duplicate metrics (#5014)
• Remove beta arg from F1 class and functional (#5076)

Fixed

• Fixed trainer by default None in DDPAccelerator (#4915)
• Fixed LightningOptimizer to expose optimizer attributes (#5095)
• Do not warn when the name key is used in the lr_scheduler dict (#5057)
• Check if optimizer supports closure (#4981)
• Extend LightningOptimizer to exposure underlying Optimizer attributes + update doc (#5095)
• Add deprecated metric utility functions back to functional (#5067, #5068)
• Allow any input in to_onnx and to_torchscript (#4378)
• Do not warn when the name key is used in the lr_scheduler dict (#5057)

Contributors

@Borda, @carmocca, @hemildesai, @rohitgr7, @s-rog, @tarepan, @tchaton

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Model Parallelism Training and More Logging Options

Overview

Lightning 1.1 is out! You can now train models with twice the parameters and zero code changes with the new sharded model training! We also have a new plugin for sequential model parallelism, more logging options, and a lot of improvements!
Release highlights: https://bit.ly/3gyLZpP

Learn more about sharded training: https://bit.ly/2W3hgI0

Detail changes

Added

• Added "monitor" key to saved ModelCheckpoints (#4383)
• Added ConfusionMatrix class interface (#4348)
• Added multiclass AUROC metric (#4236)
• Added global step indexing to the checkpoint name for a better sub-epoch checkpointing experience (#3807)
• Added optimizer hooks in callbacks (#4379)
• Added option to log momentum (#4384)
• Added current_score to ModelCheckpoint.on_save_checkpoint (#4721)
• Added logging using self.log in train and evaluation for epoch end hooks (#4913)
• Added ability for DDP plugin to modify optimizer state saving (#4675)
• Added casting to python types for NumPy scalars when logging hparams (#4647)
• Added prefix argument in loggers (#4557)
• Added printing of total num of params, trainable and non-trainable params in ModelSummary (#4521)
• Added PrecisionRecallCurve, ROC, AveragePrecision class metric (#4549)
• Added custom Apex and NativeAMP as Precision plugins (#4355)
• Added DALI MNIST example (#3721)
• Added sharded plugin for DDP for multi-GPU training memory optimizations (#4773)
• Added experiment_id to the NeptuneLogger (#3462)
• Added Pytorch Geometric integration example with Lightning (#4568)
• Added all_gather method to LightningModule which allows gradient-based tensor synchronizations for use-cases such as negative sampling. (#5012)
• Enabled self.log in most functions (#4969)
• Added changeable extension variable for ModelCheckpoint (#4977)

Changed

• Removed multiclass_roc and multiclass_precision_recall_curve, use roc and precision_recall_curve instead (#4549)
• Tuner algorithms will be skipped if fast_dev_run=True (#3903)
• WandbLogger does not force wandb reinit arg to True anymore and creates a run only when needed (#4648)
• Changed automatic_optimization to be a model attribute (#4602)
• Changed Simple Profiler report to order by percentage time spent + num calls (#4880)
• Simplify optimization Logic (#4984)
• Classification metrics overhaul (#4837)
• Updated fast_dev_run to accept integer representing num_batches (#4629)
• Refactored optimizer (#4658)

Deprecated

• Deprecated prefix argument in ModelCheckpoint (#4765)
• Deprecated the old way of assigning hyper-parameters through self.hparams = ... (#4813)
• Deprecated mode='auto' from ModelCheckpoint and EarlyStopping (#4695)

Removed

• Removed reorder parameter of the auc metric (#5004)

Fixed

• Added feature to move tensors to CPU before saving (#4309)
• Fixed LoggerConnector to have logged metrics on root device in DP (#4138)
• Auto convert tensors to contiguous format when gather_all (#4907)
• Fixed PYTHONPATH for DDP test model (#4528)
• Fixed allowing logger to support indexing (#4595)
• Fixed DDP and manual_optimization (#4976)

Contributors

@ananyahjha93, @awaelchli, @blatr, @Borda, @borisdayma, @carmocca, @ddrevicky, @george-gca, @gianscarpe, @irustandi, @janhenriklambrechts, @jeremyjordan, @justusschock, @lezwon, @rohitgr7, @s-rog, @SeanNaren, @SkafteNicki, @tadejsv, @tchaton, @williamFalcon, @zippeurfou

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standard weekly patch release

Detail changes

Added

• Added casting to python types for numpy scalars when logging hparams (#4647)
• Added warning when progress bar refresh rate is less than 20 on Google Colab to prevent crashing (#4654)
• Added F1 class metric (#4656)

Changed

• Consistently use step=trainer.global_step in LearningRateMonitor independently of logging_interval (#4376)
• Metric states are no longer as default added to state_dict (#4685)
• Renamed class metric Fbeta >> FBeta (#4656)
• Model summary: add 1 decimal place (#4745)
• Do not override PYTHONWARNINGS (#4700)

Fixed

• Fixed checkpoint hparams dict casting when omegaconf is available (#4770)
• Fixed incomplete progress bars when total batches not divisible by refresh rate (#4577)
• Updated SSIM metric (#4566)(#4656)
• Fixed batch_arg_name - add batch_arg_name to all calls to _adjust_batch_sizebug (#4812)
• Fixed torchtext data to GPU (#4785)
• Fixed a crash bug in MLFlow logger (#4716)

Contributors

@awaelchli, @jonashaag, @jungwhank, @M-Salti, @moi90, @pgagarinov, @s-rog, @Samyak2, @SkafteNicki, @teddykoker, @ydcjeff

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standard weekly patch release

Detail changes

Added

• Added lambda closure to manual_optimizer_step (#4618)

Changed

• Change Metrics persistent default mode to False (#4685)

Fixed

• Prevent crash if sync_dist=True on CPU (#4626)
• Fixed average pbar Metrics (#4534)
• Fixed setup callback hook to correctly pass the LightningModule through (#4608)
• Allowing decorate model init with saving hparams inside (#4662)
• Fixed split_idx set by LoggerConnector in on_trainer_init to Trainer (#4697)

Contributors

@ananthsub, @Borda, @SeanNaren, @SkafteNicki, @tchaton

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standard weekly patch release

Detail changes

Added

• Added metrics aggregation in Horovod and fixed early stopping (#3775)
• Added manual_optimizer_step which work with AMP Native and accumulated_grad_batches (#4485)
• Added persistent(mode) method to metrics, to enable and disable metric states being added to state_dict (#4482)
• Added congratulations at the end of our notebooks (#4555)

Changed

• Changed fsspec to tuner (#4458)
• Unify sLURM/TorchElastic under backend plugin (#4578, #4580, #4581, #4582, #4583)

Fixed

• Fixed feature-lack in hpc_load (#4526)
• Fixed metrics states being overridden in DDP mode (#4482)
• Fixed lightning_getattr, lightning_hasattr not finding the correct attributes in datamodule (#4347)
• Fixed automatic optimization AMP by manual_optimization_step (#4485)
• Replace MisconfigurationException with warning in ModelCheckpoint Callback (#4560)
• Fixed logged keys in mlflow logger (#4412)
• Fixed is_picklable by catching AttributeError (#4508)

Contributors

@dscarmo, @jtamir, @kazhang, @maxjeblick, @rohitgr7, @SkafteNicki, @tarepan, @tchaton, @tgaddair, @williamFalcon

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