Index

Symbols

**kwargs (pytorch_lightning.accelerators.Accelerator.optimizer_step parameter) (pytorch_lightning.callbacks.LambdaCallback parameter), [1] (pytorch_lightning.core.datamodule.LightningDataModule.from_argparse_args parameter) (pytorch_lightning.core.lightning.LightningModule.forward parameter), [1] (pytorch_lightning.core.lightning.LightningModule.manual_backward parameter), [1] (pytorch_lightning.core.lightning.LightningModule.print parameter), [1] (pytorch_lightning.core.lightning.LightningModule.to_onnx parameter), [1] (pytorch_lightning.core.lightning.LightningModule.to_torchscript parameter), [1] (pytorch_lightning.lite.LightningLite.backward parameter), [1] (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.plugins.training_type.DataParallelPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDP2Plugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.spawn parameter) (pytorch_lightning.plugins.training_type.SingleDevicePlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.spawn parameter) (pytorch_lightning.utilities.argparse.from_argparse_args parameter), [1]

**neptune_run_kwargs (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] *args (pytorch_lightning.core.lightning.LightningModule.forward parameter), [1] (pytorch_lightning.core.lightning.LightningModule.manual_backward parameter), [1] (pytorch_lightning.core.lightning.LightningModule.print parameter), [1] (pytorch_lightning.lite.LightningLite.backward parameter), [1] (pytorch_lightning.plugins.training_type.DataParallelPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDP2Plugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.spawn parameter) (pytorch_lightning.plugins.training_type.SingleDevicePlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.spawn parameter) *dataloaders (pytorch_lightning.lite.LightningLite.setup_dataloaders parameter), [1] *optimizers (pytorch_lightning.lite.LightningLite.setup parameter), [1]

_

__init__() (pytorch_lightning.lite.LightningLite method)

A

AbstractProfiler (class in pytorch_lightning.profiler) Accelerator (class in pytorch_lightning.accelerators) accelerator (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] accumulate_grad_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] add_argparse_args() (in module pytorch_lightning.utilities.argparse) (pytorch_lightning.core.datamodule.LightningDataModule class method) add_arguments_to_parser() (pytorch_lightning.utilities.cli.LightningCLI method) add_core_arguments_to_parser() (pytorch_lightning.utilities.cli.LightningCLI method) add_dataloader_idx (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] add_default_arguments_to_parser() (pytorch_lightning.utilities.cli.LightningCLI method) add_lightning_class_args() (pytorch_lightning.utilities.cli.LightningArgumentParser method) add_lr_scheduler_args() (pytorch_lightning.utilities.cli.LightningArgumentParser method) add_optimizer_args() (pytorch_lightning.utilities.cli.LightningArgumentParser method) add_to_queue() (pytorch_lightning.core.lightning.LightningModule method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) advance() (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.ManualOptimization method) (pytorch_lightning.loops.optimization.OptimizerLoop method) AdvancedProfiler (class in pytorch_lightning.profiler) after_save_checkpoint() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) agg_and_log_metrics() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) agg_default_func (pytorch_lightning.loggers.base.LightningLoggerBase parameter), [1] (pytorch_lightning.loggers.base.LightningLoggerBase.update_agg_funcs parameter) (pytorch_lightning.loggers.base.LoggerCollection.update_agg_funcs parameter) agg_key_funcs (pytorch_lightning.loggers.base.LightningLoggerBase parameter), [1] (pytorch_lightning.loggers.base.LightningLoggerBase.update_agg_funcs parameter) (pytorch_lightning.loggers.base.LoggerCollection.update_agg_funcs parameter) (pytorch_lightning.loggers.base.merge_dicts parameter), [1] all_gather() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.ParallelPlugin method) (pytorch_lightning.plugins.training_type.SingleDevicePlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) allgather_bucket_size (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2]

allgather_partitions (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] allow_zero_length_dataloader_with_multiple_devices (pytorch_lightning.core.hooks.DataHooks attribute) amount (pytorch_lightning.callbacks.ModelPruning parameter), [1] amp_backend (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] amp_level (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] annealing_epochs (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1] annealing_strategy (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1] anonymous (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] ApexMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) api_key (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] apply_lottery_ticket_hypothesis() (pytorch_lightning.callbacks.ModelPruning method) apply_pruning (pytorch_lightning.callbacks.ModelPruning parameter), [1] apply_pruning() (pytorch_lightning.callbacks.ModelPruning method) args (pytorch_lightning.core.datamodule.LightningDataModule.from_argparse_args parameter) (pytorch_lightning.core.lightning.LightningModule.save_hyperparameters parameter) (pytorch_lightning.loggers.base.DummyLogger.log_hyperparams parameter) (pytorch_lightning.loggers.base.LightningLoggerBase.log_hyperparams parameter) (pytorch_lightning.loggers.base.LoggerCollection.log_hyperparams parameter) (pytorch_lightning.loggers.comet.CometLogger.log_hyperparams parameter) (pytorch_lightning.loggers.CometLogger.log_hyperparams parameter) (pytorch_lightning.loggers.csv_logs.CSVLogger.log_hyperparams parameter) (pytorch_lightning.loggers.CSVLogger.log_hyperparams parameter) (pytorch_lightning.loggers.mlflow.MLFlowLogger.log_hyperparams parameter) (pytorch_lightning.loggers.MLFlowLogger.log_hyperparams parameter) (pytorch_lightning.loggers.test_tube.TestTubeLogger.log_hyperparams parameter) (pytorch_lightning.loggers.TestTubeLogger.log_hyperparams parameter) (pytorch_lightning.loggers.wandb.WandbLogger.log_hyperparams parameter) (pytorch_lightning.loggers.WandbLogger.log_hyperparams parameter) (pytorch_lightning.utilities.argparse.from_argparse_args parameter), [1] (pytorch_lightning.utilities.cli.instantiate_class parameter), [1] artifact_location (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] auto_device_count() (pytorch_lightning.accelerators.Accelerator static method) (pytorch_lightning.accelerators.CPUAccelerator static method) (pytorch_lightning.accelerators.GPUAccelerator static method) (pytorch_lightning.accelerators.IPUAccelerator static method) (pytorch_lightning.accelerators.TPUAccelerator static method) auto_insert_metric_name (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] auto_lr_find (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] auto_scale_batch_size (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] auto_select_gpus (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] autocast() (pytorch_lightning.lite.LightningLite method) automatic_optimization (pytorch_lightning.core.lightning.LightningModule property) avg_fn (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1] avg_fn() (pytorch_lightning.callbacks.StochasticWeightAveraging static method)

B

backbone_initial_lr (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] backbone_initial_ratio_lr (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] BackboneFinetuning (class in pytorch_lightning.callbacks) backward() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin method) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) barrier() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.plugins.training_type.DataParallelPlugin method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.SingleDevicePlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) BaseFinetuning (class in pytorch_lightning.callbacks) BasePredictionWriter (class in pytorch_lightning.callbacks) BaseProfiler (class in pytorch_lightning.profiler) batch (pytorch_lightning.accelerators.Accelerator.batch_to_device parameter) (pytorch_lightning.core.hooks.DataHooks.on_after_batch_transfer parameter), [1] (pytorch_lightning.core.hooks.DataHooks.on_before_batch_transfer parameter), [1] (pytorch_lightning.core.hooks.DataHooks.transfer_batch_to_device parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_predict_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_predict_batch_start parameter) (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_start parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_start parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_start parameter), [1] (pytorch_lightning.core.lightning.LightningModule.predict_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.tbptt_split_batch parameter), [1] (pytorch_lightning.core.lightning.LightningModule.test_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.training_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.validation_step parameter), [1] (pytorch_lightning.loops.batch.TrainingBatchLoop.advance parameter) (pytorch_lightning.loops.batch.TrainingBatchLoop.on_run_start parameter) (pytorch_lightning.loops.optimization.ManualOptimization.advance parameter)

batch_arg_name (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) batch_idx (pytorch_lightning.core.hooks.ModelHooks.on_predict_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_predict_batch_start parameter) (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_start parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_start parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_start parameter), [1] (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.optimizer_zero_grad parameter), [1] (pytorch_lightning.core.lightning.LightningModule.predict_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.test_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.training_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.validation_step parameter), [1] (pytorch_lightning.loops.batch.TrainingBatchLoop.advance parameter) (pytorch_lightning.loops.batch.TrainingBatchLoop.on_run_start parameter) (pytorch_lightning.loops.epoch.TrainingEpochLoop property) (pytorch_lightning.loops.FitLoop property) (pytorch_lightning.loops.optimization.ManualOptimization.advance parameter) batch_parts_outputs (pytorch_lightning.core.lightning.LightningModule.test_step_end parameter), [1] (pytorch_lightning.core.lightning.LightningModule.training_step_end parameter), [1] (pytorch_lightning.core.lightning.LightningModule.validation_step_end parameter), [1] batch_size (pytorch_lightning.core.datamodule.LightningDataModule.from_datasets parameter) (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] batch_to_device() (pytorch_lightning.accelerators.Accelerator method) before_instantiate_classes() (pytorch_lightning.utilities.cli.LightningCLI method) benchmark (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] block_backward_sync() (pytorch_lightning.plugins.training_type.DDPShardedPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnShardedPlugin method) (pytorch_lightning.plugins.training_type.ParallelPlugin method) block_size (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] broadcast() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.training_type.DataParallelPlugin method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.SingleDevicePlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method)

C

Callback (class in pytorch_lightning.callbacks) (class in pytorch_lightning.callbacks.base) callback_state (pytorch_lightning.callbacks.BackboneFinetuning.on_load_checkpoint parameter) (pytorch_lightning.callbacks.base.Callback.on_load_checkpoint parameter) (pytorch_lightning.callbacks.BaseFinetuning.on_load_checkpoint parameter) (pytorch_lightning.callbacks.Callback.on_load_checkpoint parameter), [1] (pytorch_lightning.callbacks.early_stopping.EarlyStopping.on_load_checkpoint parameter) (pytorch_lightning.callbacks.EarlyStopping.on_load_checkpoint parameter) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint.on_load_checkpoint parameter) (pytorch_lightning.callbacks.ModelCheckpoint.on_load_checkpoint parameter) callbacks (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] check_finite (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] check_on_train_epoch_end (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] check_val_every_n_epoch (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] checkpoint (pytorch_lightning.accelerators.Accelerator.save_checkpoint parameter) (pytorch_lightning.callbacks.BackboneFinetuning.on_save_checkpoint parameter) (pytorch_lightning.callbacks.base.Callback.on_save_checkpoint parameter) (pytorch_lightning.callbacks.BaseFinetuning.on_save_checkpoint parameter) (pytorch_lightning.callbacks.Callback.on_save_checkpoint parameter), [1] (pytorch_lightning.callbacks.early_stopping.EarlyStopping.on_save_checkpoint parameter) (pytorch_lightning.callbacks.EarlyStopping.on_save_checkpoint parameter) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint.on_save_checkpoint parameter) (pytorch_lightning.callbacks.ModelCheckpoint.on_save_checkpoint parameter) (pytorch_lightning.callbacks.ModelPruning.on_save_checkpoint parameter) (pytorch_lightning.core.hooks.CheckpointHooks.on_load_checkpoint parameter), [1] (pytorch_lightning.core.hooks.CheckpointHooks.on_save_checkpoint parameter), [1] (pytorch_lightning.plugins.io.CheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.XLACheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.on_load_checkpoint parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.on_save_checkpoint parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.on_load_checkpoint parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.on_save_checkpoint parameter) (pytorch_lightning.plugins.training_type.DeepSpeedPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.SingleTPUPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.save_checkpoint parameter) checkpoint_callback (pytorch_lightning.loggers.base.LightningLoggerBase.after_save_checkpoint parameter) (pytorch_lightning.loggers.base.LoggerCollection.after_save_checkpoint parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.after_save_checkpoint parameter) (pytorch_lightning.loggers.NeptuneLogger.after_save_checkpoint parameter) (pytorch_lightning.loggers.wandb.WandbLogger.after_save_checkpoint parameter) (pytorch_lightning.loggers.WandbLogger.after_save_checkpoint parameter) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] (pytorch_lightning.trainer.trainer.Trainer property) checkpoint_callbacks (pytorch_lightning.trainer.trainer.Trainer property) checkpoint_path (pytorch_lightning.core.lightning.LightningModule.load_from_checkpoint parameter) CheckpointHooks (class in pytorch_lightning.core.hooks) CheckpointIO (class in pytorch_lightning.plugins.io) ckpt_path (pytorch_lightning.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.Trainer.test parameter), [1] (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.test parameter) (pytorch_lightning.trainer.trainer.Trainer.validate parameter) (pytorch_lightning.trainer.Trainer.validate parameter) classes (pytorch_lightning.utilities.cli.LightningArgumentParser.set_choices parameter) clip_grad_by_norm() (pytorch_lightning.plugins.precision.FullyShardedNativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.precision.ShardedNativeMixedPrecisionPlugin method) clip_grad_by_value() (pytorch_lightning.plugins.precision.PrecisionPlugin method)

clip_gradients() (pytorch_lightning.core.lightning.LightningModule method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin method) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) close() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.test_tube.TestTubeLogger method) (pytorch_lightning.loggers.TestTubeLogger method) closure (pytorch_lightning.accelerators.Accelerator.optimizer_step parameter) closure_loss (pytorch_lightning.accelerators.Accelerator.backward parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.pre_backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.post_backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.pre_backward parameter) cls (pytorch_lightning.utilities.argparse.add_argparse_args parameter), [1] (pytorch_lightning.utilities.argparse.from_argparse_args parameter), [1] ClusterEnvironment (class in pytorch_lightning.plugins.environments) collect_quantization (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1] collection (pytorch_lightning.plugins.training_type.DataParallelPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDP2Plugin.reduce parameter) CometLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.comet) config (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] (pytorch_lightning.utilities.cli.SaveConfigCallback parameter), [1] config_filename (pytorch_lightning.utilities.cli.SaveConfigCallback parameter), [1] configure_callbacks() (pytorch_lightning.core.lightning.LightningModule method) configure_gradient_clipping() (pytorch_lightning.core.lightning.LightningModule method) configure_optimizers() (pytorch_lightning.core.lightning.LightningModule method) configure_sharded_model() (pytorch_lightning.core.hooks.ModelHooks method) configure_sync_batchnorm() (pytorch_lightning.plugins.training_type.ParallelPlugin static method) connect() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.OptimizerLoop method) (pytorch_lightning.plugins.precision.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.precision.TPUBf16PrecisionPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) content (pytorch_lightning.lite.LightningLite.save parameter), [1] contiguous_gradients (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] contiguous_memory_optimization (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] cpu_checkpointing (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] CPUAccelerator (class in pytorch_lightning.accelerators) create_git_tag (pytorch_lightning.loggers.test_tube.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.TestTubeLogger parameter), [1] creates_children() (pytorch_lightning.plugins.environments.ClusterEnvironment method) creates_processes_externally (pytorch_lightning.plugins.environments.ClusterEnvironment property) (pytorch_lightning.plugins.environments.KubeflowEnvironment property) (pytorch_lightning.plugins.environments.LightningEnvironment property) (pytorch_lightning.plugins.environments.LSFEnvironment property) (pytorch_lightning.plugins.environments.SLURMEnvironment property) (pytorch_lightning.plugins.environments.TorchElasticEnvironment property) CSVLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.csv_logs) current_dataloader (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) current_dataloader_idx (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) current_epoch (pytorch_lightning.core.lightning.LightningModule property) (pytorch_lightning.loops.FitLoop property)

D

data (pytorch_lightning.core.lightning.LightningModule.all_gather parameter) (pytorch_lightning.lite.LightningLite.all_gather parameter), [1] data_fetcher (pytorch_lightning.loops.epoch.EvaluationEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.on_run_start parameter) DataHooks (class in pytorch_lightning.core.hooks) dataloader (pytorch_lightning.accelerators.Accelerator.process_dataloader parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.process_dataloader parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.process_dataloader parameter) dataloader_idx (pytorch_lightning.accelerators.Accelerator.batch_to_device parameter) (pytorch_lightning.core.hooks.DataHooks.on_after_batch_transfer parameter), [1] (pytorch_lightning.core.hooks.DataHooks.on_before_batch_transfer parameter), [1] (pytorch_lightning.core.hooks.DataHooks.transfer_batch_to_device parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_predict_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_predict_batch_start parameter) (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_start parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_start parameter), [1] (pytorch_lightning.core.lightning.LightningModule.predict_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.test_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.validation_step parameter), [1] (pytorch_lightning.loops.epoch.EvaluationEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.on_run_start parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) dataloader_iter (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) (pytorch_lightning.loops.epoch.TrainingEpochLoop.advance parameter) DataLoaderLoop (class in pytorch_lightning.loops.dataloader.dataloader_loop) dataloaders (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) (pytorch_lightning.loops.dataloader.EvaluationLoop property) (pytorch_lightning.loops.dataloader.PredictionLoop property) (pytorch_lightning.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.Trainer.test parameter), [1] (pytorch_lightning.trainer.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.test parameter) (pytorch_lightning.trainer.trainer.Trainer.validate parameter) (pytorch_lightning.trainer.Trainer.validate parameter) datamodule (pytorch_lightning.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.Trainer.test parameter), [1] (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.test parameter) (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.trainer.Trainer.validate parameter) (pytorch_lightning.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.validate parameter) (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) datamodule_class (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] DataParallelPlugin (class in pytorch_lightning.plugins.training_type) DDP2Plugin (class in pytorch_lightning.plugins.training_type) DDPPlugin (class in pytorch_lightning.plugins.training_type) DDPShardedPlugin (class in pytorch_lightning.plugins.training_type) DDPSpawnPlugin (class in pytorch_lightning.plugins.training_type) DDPSpawnShardedPlugin (class in pytorch_lightning.plugins.training_type) debug (pytorch_lightning.loggers.test_tube.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.TestTubeLogger parameter), [1] DeepSpeedPlugin (class in pytorch_lightning.plugins.training_type) DeepSpeedPrecisionPlugin (class in pytorch_lightning.plugins.precision)

default_func (pytorch_lightning.loggers.base.merge_dicts parameter), [1] default_hp_metric (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] default_root_dir (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] (pytorch_lightning.trainer.trainer.Trainer property) describe() (pytorch_lightning.profiler.BaseProfiler method) description (pytorch_lightning.loggers.test_tube.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.TestTubeLogger parameter), [1] (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] destination (pytorch_lightning.loops.base.Loop.state_dict parameter) detect_anomaly (pytorch_lightning.trainer.Trainer parameter), [1] (pytorch_lightning.trainer.trainer.Trainer parameter), [1], [2], [3] determine_data_use_amount() (pytorch_lightning.trainer.trainer.Trainer method) deterministic (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] device (pytorch_lightning.accelerators.Accelerator.batch_to_device parameter) (pytorch_lightning.accelerators.Accelerator.get_device_stats parameter) (pytorch_lightning.accelerators.GPUAccelerator.get_device_stats parameter) (pytorch_lightning.accelerators.TPUAccelerator.get_device_stats parameter) (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1] (pytorch_lightning.core.hooks.DataHooks.transfer_batch_to_device parameter), [1] (pytorch_lightning.lite.LightningLite property) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin parameter), [1], [2] devices (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] DeviceStatsMonitor (class in pytorch_lightning.callbacks) dictionary (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] dicts (pytorch_lightning.loggers.base.merge_dicts parameter), [1] dims (pytorch_lightning.core.datamodule.LightningDataModule property) dirpath (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] (pytorch_lightning.profiler.AdvancedProfiler parameter), [1], [2] (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] (pytorch_lightning.profiler.SimpleProfiler parameter), [1], [2] disable() (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.RichProgressBar method) disable_validation (pytorch_lightning.trainer.trainer.Trainer property) dispatch() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) divergence_threshold (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] dl_max_batches (pytorch_lightning.loops.epoch.EvaluationEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.on_run_start parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) done (pytorch_lightning.loops.base.Loop property) (pytorch_lightning.loops.batch.TrainingBatchLoop property) (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) (pytorch_lightning.loops.dataloader.EvaluationLoop property) (pytorch_lightning.loops.epoch.EvaluationEpochLoop property) (pytorch_lightning.loops.epoch.PredictionEpochLoop property) (pytorch_lightning.loops.epoch.TrainingEpochLoop property) (pytorch_lightning.loops.FitLoop property) (pytorch_lightning.loops.optimization.ManualOptimization property) (pytorch_lightning.loops.optimization.OptimizerLoop property) DoublePrecisionPlugin (class in pytorch_lightning.plugins.precision) DummyExperiment (class in pytorch_lightning.loggers.base) DummyLogger (class in pytorch_lightning.loggers.base)

E

early_stop_threshold (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) early_stopping_callback (pytorch_lightning.trainer.trainer.Trainer property) early_stopping_callbacks (pytorch_lightning.trainer.trainer.Trainer property) EarlyStopping (class in pytorch_lightning.callbacks) (class in pytorch_lightning.callbacks.early_stopping) emit_nvtx (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] enable() (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.RichProgressBar method) enable_checkpointing (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] enable_graph (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] enable_model_summary (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] enable_progress_bar (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] enable_validation (pytorch_lightning.trainer.trainer.Trainer property) env_parse (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] env_prefix (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] epoch (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.optimizer_zero_grad parameter), [1] EvaluationEpochLoop (class in pytorch_lightning.loops.epoch) EvaluationLoop (class in pytorch_lightning.loops.dataloader) every_n_epochs (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] every_n_train_steps (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] every_n_val_epochs (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] example_input_array (pytorch_lightning.core.lightning.LightningModule property)

example_inputs (pytorch_lightning.core.lightning.LightningModule.to_torchscript parameter), [1] experiment (pytorch_lightning.loggers.base.DummyLogger property) (pytorch_lightning.loggers.base.LightningLoggerBase property) (pytorch_lightning.loggers.base.LoggerCollection property) (pytorch_lightning.loggers.comet.CometLogger property) (pytorch_lightning.loggers.CometLogger property) (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger property) (pytorch_lightning.loggers.neptune.NeptuneLogger property) (pytorch_lightning.loggers.NeptuneLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger property) (pytorch_lightning.loggers.test_tube.TestTubeLogger property) (pytorch_lightning.loggers.TestTubeLogger property) (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger property) (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger property) experiment_id (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger property) experiment_key (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] experiment_name (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] ExperimentWriter (class in pytorch_lightning.loggers.csv_logs) export_to_chrome (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2]

F

fan_speed (pytorch_lightning.callbacks.gpu_stats_monitor.GPUStatsMonitor parameter), [1] (pytorch_lightning.callbacks.GPUStatsMonitor parameter), [1] fast_dev_run (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] file_exists() (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) file_path (pytorch_lightning.core.lightning.LightningModule.to_onnx parameter), [1] (pytorch_lightning.core.lightning.LightningModule.to_torchscript parameter), [1] filename (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] (pytorch_lightning.profiler.AdvancedProfiler parameter), [1], [2] (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] (pytorch_lightning.profiler.SimpleProfiler parameter), [1], [2] filepath (pytorch_lightning.accelerators.Accelerator.save_checkpoint parameter) (pytorch_lightning.lite.LightningLite.load parameter), [1] (pytorch_lightning.lite.LightningLite.save parameter), [1] (pytorch_lightning.plugins.training_type.DeepSpeedPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.SingleTPUPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.remove_checkpoint parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.save_checkpoint parameter) filter_on_optimizer() (pytorch_lightning.callbacks.BaseFinetuning static method) filter_parameters_to_prune() (pytorch_lightning.callbacks.ModelPruning method) filter_params() (pytorch_lightning.callbacks.BaseFinetuning static method) finalize() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.comet.CometLogger method) (pytorch_lightning.loggers.CometLogger method) (pytorch_lightning.loggers.csv_logs.CSVLogger method) (pytorch_lightning.loggers.CSVLogger method) (pytorch_lightning.loggers.mlflow.MLFlowLogger method) (pytorch_lightning.loggers.MLFlowLogger method) (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger method) (pytorch_lightning.loggers.TensorBoardLogger method) (pytorch_lightning.loggers.test_tube.TestTubeLogger method) (pytorch_lightning.loggers.TestTubeLogger method) (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method)

finetune_function() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.BaseFinetuning method) fit() (pytorch_lightning.trainer.trainer.Trainer method) FitLoop (class in pytorch_lightning.loops) flatten_modules() (pytorch_lightning.callbacks.BaseFinetuning static method) flush_logs_every_n_steps (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] fn (pytorch_lightning.core.decorators.parameter_validation parameter), [1] format_checkpoint_name() (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) forward() (pytorch_lightning.core.lightning.LightningModule method) forward_context() (pytorch_lightning.plugins.precision.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) frame (pytorch_lightning.core.lightning.LightningModule.save_hyperparameters parameter) freeze() (pytorch_lightning.callbacks.BaseFinetuning static method) (pytorch_lightning.core.lightning.LightningModule method) freeze_before_training() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.BaseFinetuning method) from_argparse_args() (in module pytorch_lightning.utilities.argparse) (pytorch_lightning.core.datamodule.LightningDataModule class method) from_datasets() (pytorch_lightning.core.datamodule.LightningDataModule class method) FullyShardedNativeMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) function (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.spawn parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.spawn parameter)

G

get_deprecated_arg_names() (pytorch_lightning.trainer.trainer.Trainer class method) get_device_stats() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.CPUAccelerator method) (pytorch_lightning.accelerators.GPUAccelerator method) (pytorch_lightning.accelerators.IPUAccelerator method) (pytorch_lightning.accelerators.TPUAccelerator method) get_from_queue() (pytorch_lightning.core.lightning.LightningModule method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) get_init_arguments_and_types() (in module pytorch_lightning.utilities.argparse) (pytorch_lightning.core.datamodule.LightningDataModule class method) get_metrics() (pytorch_lightning.callbacks.ProgressBarBase method) get_progress_bar_dict() (pytorch_lightning.core.lightning.LightningModule method) global_rank (pytorch_lightning.core.lightning.LightningModule property) (pytorch_lightning.lite.LightningLite property) global_rank() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) global_step (pytorch_lightning.core.lightning.LightningModule property) (pytorch_lightning.loops.FitLoop property) gpu_utilization (pytorch_lightning.callbacks.gpu_stats_monitor.GPUStatsMonitor parameter), [1] (pytorch_lightning.callbacks.GPUStatsMonitor parameter), [1] GPUAccelerator (class in pytorch_lightning.accelerators) gpus (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1]

GPUStatsMonitor (class in pytorch_lightning.callbacks) (class in pytorch_lightning.callbacks.gpu_stats_monitor) grad_norm_dict (pytorch_lightning.core.lightning.LightningModule.log_grad_norm parameter) gradient_clip_algorithm (pytorch_lightning.core.lightning.LightningModule.clip_gradients parameter) (pytorch_lightning.core.lightning.LightningModule.configure_gradient_clipping parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] gradient_clip_val (pytorch_lightning.core.lightning.LightningModule.clip_gradients parameter) (pytorch_lightning.core.lightning.LightningModule.configure_gradient_clipping parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] GradientAccumulationScheduler (class in pytorch_lightning.callbacks) (class in pytorch_lightning.callbacks.gradient_accumulation_scheduler) group (pytorch_lightning.accelerators.Accelerator.all_gather parameter) (pytorch_lightning.core.lightning.LightningModule.all_gather parameter) (pytorch_lightning.lite.LightningLite.all_gather parameter), [1] (pytorch_lightning.plugins.training_type.DDPPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.HorovodPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.all_gather parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.all_gather parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.reduce parameter) group_by_input_shapes (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] group_separator (pytorch_lightning.loggers.base.LightningLoggerBase property)

H

handles_gradient_accumulation (pytorch_lightning.plugins.training_type.DeepSpeedPlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) has_prepared_data (pytorch_lightning.core.datamodule.LightningDataModule property) has_setup_fit (pytorch_lightning.core.datamodule.LightningDataModule property) has_setup_predict (pytorch_lightning.core.datamodule.LightningDataModule property) has_setup_test (pytorch_lightning.core.datamodule.LightningDataModule property) has_setup_validate (pytorch_lightning.core.datamodule.LightningDataModule property)

has_teardown_fit (pytorch_lightning.core.datamodule.LightningDataModule property) has_teardown_predict (pytorch_lightning.core.datamodule.LightningDataModule property) has_teardown_test (pytorch_lightning.core.datamodule.LightningDataModule property) has_teardown_validate (pytorch_lightning.core.datamodule.LightningDataModule property) hiddens (pytorch_lightning.core.lightning.LightningModule.training_step parameter), [1] HorovodPlugin (class in pytorch_lightning.plugins.training_type) hparams_file (pytorch_lightning.core.lightning.LightningModule.load_from_checkpoint parameter) hysteresis (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2]

I

id (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] ignore (pytorch_lightning.core.lightning.LightningModule.save_hyperparameters parameter) init (pytorch_lightning.utilities.cli.instantiate_class parameter), [1] init_parser() (pytorch_lightning.utilities.cli.LightningCLI method) init_val (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) initial_denom_lr (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) initial_scale_power (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] input_array (pytorch_lightning.loggers.base.LightningLoggerBase.log_graph parameter) (pytorch_lightning.loggers.base.LoggerCollection.log_graph parameter) (pytorch_lightning.loggers.comet.CometLogger.log_graph parameter) (pytorch_lightning.loggers.CometLogger.log_graph parameter) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger.log_graph parameter) (pytorch_lightning.loggers.TensorBoardLogger.log_graph parameter) (pytorch_lightning.loggers.test_tube.TestTubeLogger.log_graph parameter) (pytorch_lightning.loggers.TestTubeLogger.log_graph parameter) input_compatible (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1] input_sample (pytorch_lightning.core.lightning.LightningModule.to_onnx parameter), [1]

instantiate_class() (in module pytorch_lightning.utilities.cli) instantiate_classes() (pytorch_lightning.utilities.cli.LightningCLI method) instantiate_trainer() (pytorch_lightning.utilities.cli.LightningCLI method) inter_step_time (pytorch_lightning.callbacks.gpu_stats_monitor.GPUStatsMonitor parameter), [1] (pytorch_lightning.callbacks.GPUStatsMonitor parameter), [1] intra_step_time (pytorch_lightning.callbacks.gpu_stats_monitor.GPUStatsMonitor parameter), [1] (pytorch_lightning.callbacks.GPUStatsMonitor parameter), [1] IPUAccelerator (class in pytorch_lightning.accelerators) IPUPrecisionPlugin (class in pytorch_lightning.plugins.precision) ipus (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] is_global_zero (pytorch_lightning.lite.LightningLite property) (pytorch_lightning.plugins.training_type.ParallelPlugin property) (pytorch_lightning.plugins.training_type.SingleDevicePlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) is_list (pytorch_lightning.utilities.cli.LightningArgumentParser.set_choices parameter) is_using_kubeflow() (pytorch_lightning.plugins.environments.KubeflowEnvironment static method) is_using_lsf() (pytorch_lightning.plugins.environments.LSFEnvironment static method) is_using_torchelastic() (pytorch_lightning.plugins.environments.TorchElasticEnvironment static method)

K

KubeflowEnvironment (class in pytorch_lightning.plugins.environments) kwargs (pytorch_lightning.core.lightning.LightningModule.load_from_checkpoint parameter) (pytorch_lightning.loggers.base.DummyLogger.log_hyperparams parameter) (pytorch_lightning.loggers.base.LightningLoggerBase.log_hyperparams parameter) (pytorch_lightning.loggers.base.LoggerCollection.log_hyperparams parameter) (pytorch_lightning.loggers.comet.CometLogger.log_hyperparams parameter) (pytorch_lightning.loggers.CometLogger.log_hyperparams parameter) (pytorch_lightning.loggers.csv_logs.CSVLogger.log_hyperparams parameter) (pytorch_lightning.loggers.CSVLogger.log_hyperparams parameter) (pytorch_lightning.loggers.mlflow.MLFlowLogger.log_hyperparams parameter) (pytorch_lightning.loggers.MLFlowLogger.log_hyperparams parameter) (pytorch_lightning.loggers.test_tube.TestTubeLogger.log_hyperparams parameter) (pytorch_lightning.loggers.TestTubeLogger.log_hyperparams parameter) (pytorch_lightning.loggers.wandb.WandbLogger.log_hyperparams parameter) (pytorch_lightning.loggers.WandbLogger.log_hyperparams parameter) (pytorch_lightning.utilities.cli.LightningCLI.instantiate_trainer parameter)

L

lambda_func (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] LambdaCallback (class in pytorch_lightning.callbacks) LearningRateMonitor (class in pytorch_lightning.callbacks) (class in pytorch_lightning.callbacks.lr_monitor) leave (pytorch_lightning.callbacks.RichProgressBar parameter), [1] lightning_class (pytorch_lightning.utilities.cli.LightningArgumentParser.add_lightning_class_args parameter) lightning_module (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.plugins.training_type.DDPShardedPlugin property) (pytorch_lightning.plugins.training_type.DDPSpawnShardedPlugin property) (pytorch_lightning.plugins.training_type.DeepSpeedPlugin property) (pytorch_lightning.plugins.training_type.ParallelPlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) lightning_module_state_dict() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) lightning_restore_optimizer_and_schedulers (pytorch_lightning.plugins.training_type.DeepSpeedPlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) LightningArgumentParser (class in pytorch_lightning.utilities.cli) LightningCLI (class in pytorch_lightning.utilities.cli) LightningDataModule (class in pytorch_lightning.core.datamodule) LightningEnvironment (class in pytorch_lightning.plugins.environments) LightningLite (class in pytorch_lightning.lite) LightningLoggerBase (class in pytorch_lightning.loggers.base) LightningModule (class in pytorch_lightning.core.lightning) limit_predict_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] limit_test_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] limit_train_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] limit_val_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] line_count_restriction (pytorch_lightning.profiler.AdvancedProfiler parameter), [1], [2] link_optimizers_and_lr_schedulers() (pytorch_lightning.utilities.cli.LightningCLI static method) link_to (pytorch_lightning.utilities.cli.LightningArgumentParser.add_lr_scheduler_args parameter) (pytorch_lightning.utilities.cli.LightningArgumentParser.add_optimizer_args parameter) load() (pytorch_lightning.lite.LightningLite method) load_checkpoint() (pytorch_lightning.plugins.io.CheckpointIO method) (pytorch_lightning.plugins.io.TorchCheckpointIO method) load_full_weights (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] load_state_dict() (pytorch_lightning.loops.base.Loop method) local_rank (pytorch_lightning.core.lightning.LightningModule property) (pytorch_lightning.lite.LightningLite property) local_rank() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) locations. (pytorch_lightning.plugins.io.TorchCheckpointIO.load_checkpoint parameter) log() (pytorch_lightning.core.lightning.LightningModule method) log_dict() (pytorch_lightning.core.lightning.LightningModule method) log_dir (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.csv_logs.ExperimentWriter parameter), [1] (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger property) log_every_n_steps (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] log_gpu_memory (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] log_grad_norm() (pytorch_lightning.core.lightning.LightningModule method) log_graph (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.test_tube.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.TestTubeLogger parameter), [1] log_graph() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.comet.CometLogger method) (pytorch_lightning.loggers.CometLogger method) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger method) (pytorch_lightning.loggers.TensorBoardLogger method) (pytorch_lightning.loggers.test_tube.TestTubeLogger method) (pytorch_lightning.loggers.TestTubeLogger method) log_hparams() (pytorch_lightning.loggers.csv_logs.ExperimentWriter method) log_hyperparams() (pytorch_lightning.loggers.base.DummyLogger method) (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.comet.CometLogger method) (pytorch_lightning.loggers.CometLogger method) (pytorch_lightning.loggers.csv_logs.CSVLogger method) (pytorch_lightning.loggers.CSVLogger method) (pytorch_lightning.loggers.mlflow.MLFlowLogger method) (pytorch_lightning.loggers.MLFlowLogger method) (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger method) (pytorch_lightning.loggers.TensorBoardLogger method) (pytorch_lightning.loggers.test_tube.TestTubeLogger method) (pytorch_lightning.loggers.TestTubeLogger method) (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method)

log_image() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) log_metrics() (pytorch_lightning.loggers.base.DummyLogger method) (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.comet.CometLogger method) (pytorch_lightning.loggers.CometLogger method) (pytorch_lightning.loggers.csv_logs.CSVLogger method) (pytorch_lightning.loggers.csv_logs.ExperimentWriter method) (pytorch_lightning.loggers.CSVLogger method) (pytorch_lightning.loggers.mlflow.MLFlowLogger method) (pytorch_lightning.loggers.MLFlowLogger method) (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger method) (pytorch_lightning.loggers.TensorBoardLogger method) (pytorch_lightning.loggers.test_tube.TestTubeLogger method) (pytorch_lightning.loggers.TestTubeLogger method) (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) log_model (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] log_model_checkpoints (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] log_momentum (pytorch_lightning.callbacks.LearningRateMonitor parameter), [1] (pytorch_lightning.callbacks.lr_monitor.LearningRateMonitor parameter), [1] log_table() (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) log_text() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) logger (pytorch_lightning.core.lightning.LightningModule property) (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] (pytorch_lightning.core.lightning.LightningModule.save_hyperparameters parameter) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] logger_iterable (pytorch_lightning.loggers.base.LoggerCollection parameter), [1] LoggerCollection (class in pytorch_lightning.loggers.base) logging_batch_size_per_gpu (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] logging_interval (pytorch_lightning.callbacks.LearningRateMonitor parameter), [1] (pytorch_lightning.callbacks.lr_monitor.LearningRateMonitor parameter), [1] logging_level (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] Loop (class in pytorch_lightning.loops.base) loss (pytorch_lightning.core.hooks.ModelHooks.on_before_backward parameter), [1] (pytorch_lightning.core.lightning.LightningModule.backward parameter), [1] (pytorch_lightning.core.lightning.LightningModule.manual_backward parameter), [1] loss_scale (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] loss_scale_window (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] lr (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) lr_find() (pytorch_lightning.tuner.tuning.Tuner method) lr_find_kwargs (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.tune parameter) lr_scheduler_class (pytorch_lightning.utilities.cli.LightningArgumentParser.add_lr_scheduler_args parameter) lr_schedulers() (pytorch_lightning.core.lightning.LightningModule method) LSFEnvironment (class in pytorch_lightning.plugins.environments)

M

main_params() (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) make_pruning_permanent (pytorch_lightning.callbacks.ModelPruning parameter), [1] make_pruning_permanent() (pytorch_lightning.callbacks.ModelPruning method) make_trainable() (pytorch_lightning.callbacks.BaseFinetuning static method) manual_backward() (pytorch_lightning.core.lightning.LightningModule method) ManualOptimization (class in pytorch_lightning.loops.optimization) map_location (pytorch_lightning.core.lightning.LightningModule.load_from_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.load_checkpoint parameter) master_address() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) master_params() (pytorch_lightning.plugins.precision.PrecisionPlugin method) master_port() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) max_batches (pytorch_lightning.loops.dataloader.PredictionLoop property) max_depth (pytorch_lightning.callbacks.ModelSummary parameter), [1] (pytorch_lightning.callbacks.RichModelSummary parameter), [1] (pytorch_lightning.core.lightning.LightningModule.summarize parameter) max_epochs (pytorch_lightning.loops.FitLoop parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] max_in_cpu (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] max_lr (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) max_steps (pytorch_lightning.loops.epoch.TrainingEpochLoop parameter), [1] (pytorch_lightning.loops.FitLoop property) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] max_time (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] max_trials (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) memory_utilization (pytorch_lightning.callbacks.gpu_stats_monitor.GPUStatsMonitor parameter), [1] (pytorch_lightning.callbacks.GPUStatsMonitor parameter), [1] merge_dicts() (in module pytorch_lightning.loggers.base) method (pytorch_lightning.core.lightning.LightningModule.to_torchscript parameter), [1] metric_attribute (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] metrics (pytorch_lightning.loggers.base.DummyLogger.log_metrics parameter) (pytorch_lightning.loggers.base.LightningLoggerBase.agg_and_log_metrics parameter) (pytorch_lightning.loggers.base.LightningLoggerBase.log_metrics parameter) (pytorch_lightning.loggers.base.LoggerCollection.agg_and_log_metrics parameter) (pytorch_lightning.loggers.base.LoggerCollection.log_metrics parameter) (pytorch_lightning.loggers.comet.CometLogger.log_metrics parameter) (pytorch_lightning.loggers.CometLogger.log_metrics parameter) (pytorch_lightning.loggers.csv_logs.CSVLogger.log_metrics parameter) (pytorch_lightning.loggers.CSVLogger.log_metrics parameter) (pytorch_lightning.loggers.mlflow.MLFlowLogger.log_metrics parameter) (pytorch_lightning.loggers.MLFlowLogger.log_metrics parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.log_metrics parameter) (pytorch_lightning.loggers.NeptuneLogger.log_metrics parameter) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger.log_hyperparams parameter) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger.log_metrics parameter) (pytorch_lightning.loggers.TensorBoardLogger.log_hyperparams parameter) (pytorch_lightning.loggers.TensorBoardLogger.log_metrics parameter) (pytorch_lightning.loggers.test_tube.TestTubeLogger.log_metrics parameter) (pytorch_lightning.loggers.TestTubeLogger.log_metrics parameter) (pytorch_lightning.loggers.wandb.WandbLogger.log_metrics parameter) (pytorch_lightning.loggers.WandbLogger.log_metrics parameter) min_delta (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] min_epochs (pytorch_lightning.loops.FitLoop parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] min_loss_scale (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] min_lr (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) min_steps (pytorch_lightning.loops.epoch.TrainingEpochLoop parameter), [1] (pytorch_lightning.loops.FitLoop property) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] MixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) MLFlowLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.mlflow) mode (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] (pytorch_lightning.core.lightning.LightningModule.summarize parameter) (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) model (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.accelerators.Accelerator.optimizer_step parameter) (pytorch_lightning.lite.LightningLite.backward parameter), [1] (pytorch_lightning.lite.LightningLite.setup parameter), [1] (pytorch_lightning.loggers.base.LightningLoggerBase.log_graph parameter) (pytorch_lightning.loggers.base.LoggerCollection.log_graph parameter) (pytorch_lightning.loggers.comet.CometLogger.log_graph parameter) (pytorch_lightning.loggers.CometLogger.log_graph parameter) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger.log_graph parameter) (pytorch_lightning.loggers.TensorBoardLogger.log_graph parameter) (pytorch_lightning.loggers.test_tube.TestTubeLogger.log_graph parameter) (pytorch_lightning.loggers.TestTubeLogger.log_graph parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.pre_backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.post_backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.pre_backward parameter) (pytorch_lightning.plugins.training_type.ParallelPlugin.configure_sync_batchnorm parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) (pytorch_lightning.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.Trainer.test parameter), [1] (pytorch_lightning.trainer.trainer.Trainer property) (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.test parameter) (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.trainer.Trainer.validate parameter) (pytorch_lightning.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.validate parameter) (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter)

model_class (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] model_sharded_context() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.training_type.DeepSpeedPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) model_size (pytorch_lightning.core.lightning.LightningModule property) model_to_device() (pytorch_lightning.plugins.training_type.DataParallelPlugin method) (pytorch_lightning.plugins.training_type.DDP2Plugin method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.SingleDevicePlugin method) (pytorch_lightning.plugins.training_type.SingleTPUPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) ModelCheckpoint (class in pytorch_lightning.callbacks) (class in pytorch_lightning.callbacks.model_checkpoint) ModelHooks (class in pytorch_lightning.core.hooks) ModelPruning (class in pytorch_lightning.callbacks) ModelSummary (class in pytorch_lightning.callbacks) module pytorch_lightning.callbacks.base pytorch_lightning.callbacks.early_stopping pytorch_lightning.callbacks.gpu_stats_monitor pytorch_lightning.callbacks.gradient_accumulation_scheduler pytorch_lightning.callbacks.lr_monitor pytorch_lightning.callbacks.model_checkpoint pytorch_lightning.callbacks.progress pytorch_lightning.core.datamodule pytorch_lightning.core.decorators pytorch_lightning.core.hooks pytorch_lightning.core.lightning pytorch_lightning.loggers.base pytorch_lightning.loggers.comet pytorch_lightning.loggers.csv_logs pytorch_lightning.loggers.mlflow pytorch_lightning.loggers.neptune pytorch_lightning.loggers.tensorboard pytorch_lightning.loggers.test_tube pytorch_lightning.loggers.wandb pytorch_lightning.trainer.trainer pytorch_lightning.utilities.argparse pytorch_lightning.utilities.cli pytorch_lightning.utilities.seed modules (pytorch_lightning.callbacks.BaseFinetuning.filter_params parameter) (pytorch_lightning.callbacks.BaseFinetuning.flatten_modules parameter) (pytorch_lightning.callbacks.BaseFinetuning.freeze parameter) (pytorch_lightning.callbacks.BaseFinetuning.make_trainable parameter) (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) modules_to_fuse (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1] monitor (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] move_metrics_to_cpu (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] move_to_device (pytorch_lightning.lite.LightningLite.setup parameter), [1] (pytorch_lightning.lite.LightningLite.setup_dataloaders parameter), [1] multifile (pytorch_lightning.utilities.cli.SaveConfigCallback parameter), [1] multiple_trainloader_mode (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1]

N

name (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.loggers.base.DummyLogger property) (pytorch_lightning.loggers.base.LightningLoggerBase property) (pytorch_lightning.loggers.base.LoggerCollection property) (pytorch_lightning.loggers.comet.CometLogger property) (pytorch_lightning.loggers.CometLogger property) (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger property) (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.neptune.NeptuneLogger property) (pytorch_lightning.loggers.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger property) (pytorch_lightning.loggers.test_tube.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.test_tube.TestTubeLogger property) (pytorch_lightning.loggers.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.TestTubeLogger property) (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger property) (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger property) (pytorch_lightning.plugins.training_type.DataParallelPlugin.barrier parameter) (pytorch_lightning.plugins.training_type.DDPPlugin.barrier parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.barrier parameter) (pytorch_lightning.plugins.training_type.HorovodPlugin.barrier parameter) (pytorch_lightning.plugins.training_type.SingleDevicePlugin.barrier parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.barrier parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.barrier parameter)

NativeMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) NeptuneLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.neptune) nested_key (pytorch_lightning.utilities.cli.LightningArgumentParser.add_lightning_class_args parameter) (pytorch_lightning.utilities.cli.LightningArgumentParser.add_lr_scheduler_args parameter) (pytorch_lightning.utilities.cli.LightningArgumentParser.add_optimizer_args parameter) (pytorch_lightning.utilities.cli.LightningArgumentParser.set_choices parameter) node_rank (pytorch_lightning.lite.LightningLite property) node_rank() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) num_dataloaders (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) (pytorch_lightning.loops.dataloader.EvaluationLoop property) (pytorch_lightning.loops.dataloader.PredictionLoop property) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.on_run_start parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) num_nodes (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] num_processes (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] num_sanity_val_steps (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] num_training (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) num_workers (pytorch_lightning.core.datamodule.LightningDataModule.from_datasets parameter) nvme_path (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2]

O

obj (pytorch_lightning.accelerators.Accelerator.broadcast parameter) (pytorch_lightning.lite.LightningLite.to_device parameter), [1] (pytorch_lightning.plugins.training_type.DataParallelPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.DDPPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.HorovodPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.SingleDevicePlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.broadcast parameter) observer_enabled_stages (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1] observer_type (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1] offline (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] offload_optimizer (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] offload_optimizer_device (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] offload_parameters (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] offload_params_device (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] on_advance_end() (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) on_advance_start() (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop method) (pytorch_lightning.loops.FitLoop method) on_after_backward() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_after_batch_transfer() (pytorch_lightning.core.hooks.DataHooks method) on_batch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) on_batch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) on_before_accelerator_backend_setup() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) on_before_backward() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_before_batch_transfer() (pytorch_lightning.core.hooks.DataHooks method) on_before_optimizer_step() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_before_zero_grad() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_configure_sharded_model() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) on_epoch (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] on_epoch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_epoch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_exception() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) on_fit_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.core.hooks.ModelHooks method) on_fit_start() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.core.hooks.ModelHooks method) on_gpu (pytorch_lightning.core.lightning.LightningModule property) (pytorch_lightning.plugins.training_type.ParallelPlugin property) (pytorch_lightning.plugins.training_type.SingleDevicePlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) on_init_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.early_stopping.EarlyStopping method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.ProgressBarBase method) on_init_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) on_keyboard_interrupt() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) on_load_checkpoint() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.early_stopping.EarlyStopping method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.core.hooks.CheckpointHooks method) (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) on_post_move_to_device() (pytorch_lightning.core.hooks.ModelHooks method) on_predict_batch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.BasePredictionWriter method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_predict_batch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_predict_dataloader() (pytorch_lightning.core.hooks.DataHooks method) on_predict_end() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) on_predict_epoch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.BasePredictionWriter method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_predict_epoch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_predict_model_eval() (pytorch_lightning.core.hooks.ModelHooks method) on_predict_start() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) on_pretrain_routine_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_pretrain_routine_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelSummary method) (pytorch_lightning.core.hooks.ModelHooks method) on_run_end() (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.ManualOptimization method) (pytorch_lightning.loops.optimization.OptimizerLoop method) on_run_start() (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.OptimizerLoop method) on_sanity_check_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) on_sanity_check_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) on_save_checkpoint() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.early_stopping.EarlyStopping method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.core.hooks.CheckpointHooks method) (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) on_skip() (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) on_step (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] on_test_batch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method)

on_test_batch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_test_dataloader() (pytorch_lightning.core.hooks.DataHooks method) on_test_end() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) on_test_epoch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_test_epoch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_test_model_eval() (pytorch_lightning.core.hooks.ModelHooks method) on_test_model_train() (pytorch_lightning.core.hooks.ModelHooks method) on_test_start() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) on_tpu (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1] (pytorch_lightning.plugins.training_type.ParallelPlugin property) (pytorch_lightning.plugins.training_type.SingleDevicePlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) on_train_batch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) 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(pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.callbacks.XLAStatsMonitor method) (pytorch_lightning.core.hooks.ModelHooks method) on_train_epoch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.gpu_stats_monitor.GPUStatsMonitor method) (pytorch_lightning.callbacks.GPUStatsMonitor method) (pytorch_lightning.callbacks.gradient_accumulation_scheduler.GradientAccumulationScheduler method) (pytorch_lightning.callbacks.GradientAccumulationScheduler method) (pytorch_lightning.callbacks.LearningRateMonitor method) (pytorch_lightning.callbacks.lr_monitor.LearningRateMonitor method) (pytorch_lightning.callbacks.ProgressBarBase method) 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(pytorch_lightning.plugins.training_type.TrainingTypePlugin method) on_val_dataloader() (pytorch_lightning.core.hooks.DataHooks method) on_validation_batch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_batch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_end() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.early_stopping.EarlyStopping method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) on_validation_epoch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_epoch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_model_eval() (pytorch_lightning.core.hooks.ModelHooks method) on_validation_model_train() (pytorch_lightning.core.hooks.ModelHooks method) on_validation_start() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) opt_idx (pytorch_lightning.accelerators.Accelerator.optimizer_step parameter) optimizer (pytorch_lightning.accelerators.Accelerator.optimizer_step parameter) (pytorch_lightning.callbacks.BaseFinetuning.filter_on_optimizer parameter) (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) (pytorch_lightning.core.hooks.ModelHooks.on_before_optimizer_step parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_before_zero_grad parameter), [1] (pytorch_lightning.core.lightning.LightningModule.backward parameter), [1] (pytorch_lightning.core.lightning.LightningModule.clip_gradients parameter) (pytorch_lightning.core.lightning.LightningModule.configure_gradient_clipping parameter), [1] (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.optimizer_zero_grad parameter), [1] (pytorch_lightning.core.lightning.LightningModule.toggle_optimizer parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) optimizer_buffer_count (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] optimizer_class (pytorch_lightning.utilities.cli.LightningArgumentParser.add_optimizer_args parameter) optimizer_closure (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1] optimizer_idx (pytorch_lightning.core.hooks.ModelHooks.on_before_optimizer_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.backward parameter), [1] (pytorch_lightning.core.lightning.LightningModule.configure_gradient_clipping parameter), [1] (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.optimizer_zero_grad parameter), [1] (pytorch_lightning.core.lightning.LightningModule.toggle_optimizer parameter) (pytorch_lightning.core.lightning.LightningModule.training_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.untoggle_optimizer parameter) optimizer_state() (pytorch_lightning.accelerators.Accelerator method) optimizer_step() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin method) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.precision.TPUPrecisionPlugin method) optimizer_zero_grad() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) OptimizerLoop (class in pytorch_lightning.loops.optimization) optimizers() (pytorch_lightning.core.lightning.LightningModule method) output (pytorch_lightning.accelerators.Accelerator.test_step_end parameter) (pytorch_lightning.accelerators.Accelerator.training_step_end parameter) (pytorch_lightning.accelerators.Accelerator.validation_step_end parameter) output_result_cls (pytorch_lightning.loops.optimization.ManualOptimization attribute) (pytorch_lightning.loops.optimization.OptimizerLoop attribute) outputs (pytorch_lightning.core.hooks.ModelHooks.on_predict_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_end parameter), [1] (pytorch_lightning.core.lightning.LightningModule.test_epoch_end parameter), [1] (pytorch_lightning.core.lightning.LightningModule.training_epoch_end parameter), [1] (pytorch_lightning.core.lightning.LightningModule.validation_epoch_end parameter), [1] overfit_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] overlap_comm (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] overlap_events (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] overwrite (pytorch_lightning.utilities.cli.SaveConfigCallback parameter), [1]

P

ParallelPlugin (class in pytorch_lightning.plugins.training_type) parameter_names (pytorch_lightning.callbacks.ModelPruning parameter), [1] parameter_validation() (in module pytorch_lightning.core.decorators) parameters_to_prune (pytorch_lightning.callbacks.ModelPruning parameter), [1] params (pytorch_lightning.callbacks.BaseFinetuning.filter_on_optimizer parameter) (pytorch_lightning.loggers.base.DummyLogger.log_hyperparams parameter) (pytorch_lightning.loggers.base.LightningLoggerBase.log_hyperparams parameter) (pytorch_lightning.loggers.base.LoggerCollection.log_hyperparams parameter) (pytorch_lightning.loggers.comet.CometLogger.log_hyperparams parameter) (pytorch_lightning.loggers.CometLogger.log_hyperparams parameter) (pytorch_lightning.loggers.csv_logs.CSVLogger.log_hyperparams parameter) (pytorch_lightning.loggers.CSVLogger.log_hyperparams parameter) (pytorch_lightning.loggers.mlflow.MLFlowLogger.log_hyperparams parameter) (pytorch_lightning.loggers.MLFlowLogger.log_hyperparams parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.log_hyperparams parameter) (pytorch_lightning.loggers.NeptuneLogger.log_hyperparams parameter) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger.log_hyperparams parameter) (pytorch_lightning.loggers.TensorBoardLogger.log_hyperparams parameter) (pytorch_lightning.loggers.test_tube.TestTubeLogger.log_hyperparams parameter) (pytorch_lightning.loggers.TestTubeLogger.log_hyperparams parameter) (pytorch_lightning.loggers.wandb.WandbLogger.log_hyperparams parameter) (pytorch_lightning.loggers.WandbLogger.log_hyperparams parameter) params_buffer_count (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] params_buffer_size (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] parent_parser (pytorch_lightning.utilities.argparse.add_argparse_args parameter), [1] parse_argparser() (in module pytorch_lightning.utilities.argparse) parse_arguments() (pytorch_lightning.utilities.cli.LightningCLI method) parse_env_variables() (in module pytorch_lightning.utilities.argparse) ParseArgparserDataType (class in pytorch_lightning.utilities.argparse) parser (pytorch_lightning.utilities.cli.LightningCLI.add_arguments_to_parser parameter) (pytorch_lightning.utilities.cli.SaveConfigCallback parameter), [1] parser_kwargs (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] partition_activations (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] PassThroughProfiler (class in pytorch_lightning.profiler) path (pytorch_lightning.plugins.io.CheckpointIO.load_checkpoint parameter) (pytorch_lightning.plugins.io.CheckpointIO.remove_checkpoint parameter) (pytorch_lightning.plugins.io.CheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.load_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.remove_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.XLACheckpointIO.save_checkpoint parameter) patience (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] pin_memory (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] pl_module (pytorch_lightning.callbacks.BackboneFinetuning.on_load_checkpoint parameter) (pytorch_lightning.callbacks.BackboneFinetuning.on_save_checkpoint parameter) (pytorch_lightning.callbacks.base.Callback.on_load_checkpoint parameter) (pytorch_lightning.callbacks.base.Callback.on_save_checkpoint parameter) (pytorch_lightning.callbacks.BaseFinetuning.on_load_checkpoint parameter) (pytorch_lightning.callbacks.BaseFinetuning.on_save_checkpoint parameter) (pytorch_lightning.callbacks.Callback.on_load_checkpoint parameter), [1] (pytorch_lightning.callbacks.Callback.on_save_checkpoint parameter), [1] (pytorch_lightning.callbacks.early_stopping.EarlyStopping.on_load_checkpoint parameter) (pytorch_lightning.callbacks.early_stopping.EarlyStopping.on_save_checkpoint parameter) (pytorch_lightning.callbacks.EarlyStopping.on_load_checkpoint parameter) (pytorch_lightning.callbacks.EarlyStopping.on_save_checkpoint parameter) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint.on_load_checkpoint parameter) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint.on_save_checkpoint parameter) (pytorch_lightning.callbacks.ModelCheckpoint.on_load_checkpoint parameter) (pytorch_lightning.callbacks.ModelCheckpoint.on_save_checkpoint parameter) (pytorch_lightning.callbacks.ModelPruning.on_save_checkpoint parameter) pl_worker_init_function() (in module pytorch_lightning.utilities.seed) plugins (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] post_backward() (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) post_dispatch() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) post_training_step() (pytorch_lightning.accelerators.Accelerator method) pre_backward() (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DDPShardedPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnShardedPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) pre_dispatch() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DeepSpeedPlugin method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.SingleTPUPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) precision (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin parameter), [1], [2] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] precision_plugin (pytorch_lightning.accelerators.Accelerator parameter), [1], [2] (pytorch_lightning.accelerators.CPUAccelerator parameter), [1], [2] (pytorch_lightning.accelerators.GPUAccelerator parameter), [1], [2] (pytorch_lightning.accelerators.IPUAccelerator parameter), [1], [2] (pytorch_lightning.accelerators.TPUAccelerator parameter), [1], [2] PrecisionPlugin (class in pytorch_lightning.plugins.precision) predict() (pytorch_lightning.trainer.trainer.Trainer method) predict_batch_idx (pytorch_lightning.callbacks.ProgressBarBase property)

predict_dataloader() (pytorch_lightning.core.hooks.DataHooks method) predict_step() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) predict_step_context() (pytorch_lightning.plugins.precision.PrecisionPlugin method) prediction_writer_callbacks (pytorch_lightning.trainer.trainer.Trainer property) PredictionEpochLoop (class in pytorch_lightning.loops.epoch) PredictionLoop (class in pytorch_lightning.loops.dataloader) prefix (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger parameter), [1] (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.test_tube.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.loops.base.Loop.state_dict parameter) prepare_data() (pytorch_lightning.core.hooks.DataHooks method) prepare_data_per_node (pytorch_lightning.core.hooks.DataHooks attribute) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] print() (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.core.lightning.LightningModule method) (pytorch_lightning.lite.LightningLite method) process_dataloader() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) process_position (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] profile() (pytorch_lightning.profiler.BaseProfiler method) profiler (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] profiler_kwargs (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] prog_bar (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] progress_bar_dict (pytorch_lightning.trainer.trainer.Trainer property) progress_bar_refresh_rate (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] ProgressBar (class in pytorch_lightning.callbacks) ProgressBarBase (class in pytorch_lightning.callbacks) project (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] project_name (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] prune_on_train_epoch_end (pytorch_lightning.callbacks.ModelPruning parameter), [1] pruning_dim (pytorch_lightning.callbacks.ModelPruning parameter), [1] pruning_fn (pytorch_lightning.callbacks.ModelPruning parameter), [1] pruning_norm (pytorch_lightning.callbacks.ModelPruning parameter), [1] pytorch_lightning.callbacks.base module pytorch_lightning.callbacks.early_stopping module pytorch_lightning.callbacks.gpu_stats_monitor module pytorch_lightning.callbacks.gradient_accumulation_scheduler module pytorch_lightning.callbacks.lr_monitor module pytorch_lightning.callbacks.model_checkpoint module pytorch_lightning.callbacks.progress module pytorch_lightning.core.datamodule module pytorch_lightning.core.decorators module pytorch_lightning.core.hooks module pytorch_lightning.core.lightning module pytorch_lightning.loggers.base module pytorch_lightning.loggers.comet module pytorch_lightning.loggers.csv_logs module pytorch_lightning.loggers.mlflow module pytorch_lightning.loggers.neptune module pytorch_lightning.loggers.tensorboard module pytorch_lightning.loggers.test_tube module pytorch_lightning.loggers.wandb module pytorch_lightning.trainer.trainer module pytorch_lightning.utilities.argparse module pytorch_lightning.utilities.cli module pytorch_lightning.utilities.seed module PyTorchProfiler (class in pytorch_lightning.profiler)

Q

qconfig (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1] QuantizationAwareTraining (class in pytorch_lightning.callbacks) quantize_on_fit_end (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1] queue (pytorch_lightning.core.lightning.LightningModule.add_to_queue parameter), [1] (pytorch_lightning.core.lightning.LightningModule.get_from_queue parameter), [1] (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.add_to_queue parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.get_from_queue parameter)

queue_depth (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2]

R

rank_zero_experiment() (in module pytorch_lightning.loggers.base) rank_zero_only (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] reconciliate_processes() (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.ParallelPlugin method) record_functions (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] record_module_names (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] reduce() (pytorch_lightning.plugins.training_type.DataParallelPlugin method) (pytorch_lightning.plugins.training_type.DDP2Plugin method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.SingleDevicePlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) reduce_boolean_decision() (pytorch_lightning.plugins.training_type.DataParallelPlugin method) (pytorch_lightning.plugins.training_type.ParallelPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) reduce_bucket_size (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] reduce_fx (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] reduce_op (pytorch_lightning.plugins.training_type.DDPPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.HorovodPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.reduce parameter) reduce_scatter (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] refresh_rate_per_second (pytorch_lightning.callbacks.RichProgressBar parameter), [1] (pytorch_lightning.callbacks.RichProgressBar property) reload_dataloaders_every_epoch (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] reload_dataloaders_every_n_epochs (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] remote_device (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] remove_checkpoint() (pytorch_lightning.plugins.io.CheckpointIO method) (pytorch_lightning.plugins.io.TorchCheckpointIO method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) replace_sampler (pytorch_lightning.lite.LightningLite.setup_dataloaders parameter), [1] replace_sampler_ddp (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] required (pytorch_lightning.utilities.cli.LightningArgumentParser.add_lightning_class_args parameter) requires_grad (pytorch_lightning.callbacks.BaseFinetuning.filter_params parameter) resample_parameters (pytorch_lightning.callbacks.ModelPruning parameter), [1] reset() (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.ManualOptimization method) (pytorch_lightning.loops.optimization.OptimizerLoop method)

reset_batch_norm_and_save_state() (pytorch_lightning.callbacks.StochasticWeightAveraging method) reset_momenta() (pytorch_lightning.callbacks.StochasticWeightAveraging method) reset_seed() (in module pytorch_lightning.utilities.seed) rest_api_key (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] restore_checkpoint_after_pre_dispatch (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.plugins.training_type.DeepSpeedPlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) results (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) resume_from_checkpoint (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] return_predictions (pytorch_lightning.loops.dataloader.PredictionLoop property) (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) (pytorch_lightning.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.predict parameter) return_result (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.spawn parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.spawn parameter) RichModelSummary (class in pytorch_lightning.callbacks) RichProgressBar (class in pytorch_lightning.callbacks) root_device (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.plugins.training_type.DataParallelPlugin property) (pytorch_lightning.plugins.training_type.DDP2Plugin property) (pytorch_lightning.plugins.training_type.DDPPlugin property) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin property) (pytorch_lightning.plugins.training_type.HorovodPlugin property) (pytorch_lightning.plugins.training_type.ParallelPlugin property) (pytorch_lightning.plugins.training_type.SingleDevicePlugin property) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) root_dir (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger property) rounding (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] row_limit (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] run (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] run() (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.loops.base.Loop method) run_id (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger property) run_name (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] running_loss (pytorch_lightning.loops.FitLoop property)

S

sanitize_parameters_to_prune() (pytorch_lightning.callbacks.ModelPruning static method) save() (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method) (pytorch_lightning.loggers.csv_logs.CSVLogger method) (pytorch_lightning.loggers.csv_logs.ExperimentWriter method) (pytorch_lightning.loggers.CSVLogger method) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger method) (pytorch_lightning.loggers.TensorBoardLogger method) (pytorch_lightning.loggers.test_tube.TestTubeLogger method) (pytorch_lightning.loggers.TestTubeLogger method) save_checkpoint() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.plugins.io.CheckpointIO method) (pytorch_lightning.plugins.io.TorchCheckpointIO method) (pytorch_lightning.plugins.io.XLACheckpointIO method) (pytorch_lightning.plugins.training_type.DeepSpeedPlugin method) (pytorch_lightning.plugins.training_type.SingleTPUPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) save_config_callback (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_config_filename (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_config_multifile (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_config_overwrite (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_dir (pytorch_lightning.loggers.base.LightningLoggerBase property) (pytorch_lightning.loggers.base.LoggerCollection property) (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.comet.CometLogger property) (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger property) (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger property) (pytorch_lightning.loggers.neptune.NeptuneLogger property) (pytorch_lightning.loggers.NeptuneLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger property) (pytorch_lightning.loggers.test_tube.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.test_tube.TestTubeLogger property) (pytorch_lightning.loggers.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.TestTubeLogger property) (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger property) (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger property) save_last (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] save_on_train_epoch_end (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] save_top_k (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] save_weights_only (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] SaveConfigCallback (class in pytorch_lightning.utilities.cli) scale_batch_size() (pytorch_lightning.tuner.tuning.Tuner method) scale_batch_size_kwargs (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.tune parameter) scaler (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin parameter), [1], [2] scheduling (pytorch_lightning.callbacks.gradient_accumulation_scheduler.GradientAccumulationScheduler parameter), [1] (pytorch_lightning.callbacks.GradientAccumulationScheduler parameter), [1] seed (pytorch_lightning.utilities.seed.seed_everything parameter), [1] seed_everything() (in module pytorch_lightning.utilities.seed) (pytorch_lightning.lite.LightningLite static method) seed_everything_default (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] set_choices() (pytorch_lightning.utilities.cli.LightningArgumentParser method) setup() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.CPUAccelerator method) (pytorch_lightning.accelerators.GPUAccelerator method) (pytorch_lightning.accelerators.TPUAccelerator method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.DeviceStatsMonitor method) (pytorch_lightning.callbacks.gpu_stats_monitor.GPUStatsMonitor method) (pytorch_lightning.callbacks.GPUStatsMonitor method) (pytorch_lightning.core.hooks.DataHooks method) (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.plugins.training_type.DataParallelPlugin method) (pytorch_lightning.plugins.training_type.DDP2Plugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.SingleDevicePlugin method) (pytorch_lightning.plugins.training_type.SingleTPUPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) (pytorch_lightning.profiler.AbstractProfiler method) (pytorch_lightning.profiler.BaseProfiler method) (pytorch_lightning.utilities.cli.SaveConfigCallback method) setup_dataloaders() (pytorch_lightning.lite.LightningLite method) setup_environment() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.GPUAccelerator method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) setup_optimizers() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.IPUAccelerator method) setup_optimizers_in_pre_dispatch (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) setup_parser() (pytorch_lightning.utilities.cli.LightningCLI method) setup_precision_plugin() (pytorch_lightning.accelerators.Accelerator method) setup_training_type_plugin() (pytorch_lightning.accelerators.Accelerator method) ShardedNativeMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) should_align (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] should_rank_save_checkpoint (pytorch_lightning.plugins.training_type.TPUSpawnPlugin property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) should_store_predictions (pytorch_lightning.loops.epoch.PredictionEpochLoop property) SimpleProfiler (class in pytorch_lightning.profiler) single_submit (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] SingleDevicePlugin (class in pytorch_lightning.plugins.training_type) SingleTPUPlugin (class in pytorch_lightning.plugins.training_type) size() (pytorch_lightning.core.datamodule.LightningDataModule method) skip (pytorch_lightning.loops.base.Loop property) (pytorch_lightning.loops.dataloader.EvaluationLoop property) (pytorch_lightning.loops.dataloader.PredictionLoop property) (pytorch_lightning.loops.FitLoop property)

SLURMEnvironment (class in pytorch_lightning.plugins.environments) sort_by_key (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] spawn() (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) split_idx (pytorch_lightning.loops.FitLoop property) split_size (pytorch_lightning.core.lightning.LightningModule.tbptt_split_batch parameter), [1] src (pytorch_lightning.accelerators.Accelerator.broadcast parameter) (pytorch_lightning.plugins.training_type.DataParallelPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.DDPPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.HorovodPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.SingleDevicePlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.broadcast parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.broadcast parameter) stage (pytorch_lightning.core.hooks.DataHooks.setup parameter), [1] (pytorch_lightning.core.hooks.DataHooks.teardown parameter), [1] (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] start() (pytorch_lightning.profiler.AbstractProfiler method) (pytorch_lightning.profiler.AdvancedProfiler method) (pytorch_lightning.profiler.BaseProfiler method) (pytorch_lightning.profiler.PassThroughProfiler method) (pytorch_lightning.profiler.PyTorchProfiler method) (pytorch_lightning.profiler.SimpleProfiler method) (pytorch_lightning.profiler.XLAProfiler method) start_evaluating() (pytorch_lightning.accelerators.Accelerator method) start_predicting() (pytorch_lightning.accelerators.Accelerator method) start_training() (pytorch_lightning.accelerators.Accelerator method) state_dict() (pytorch_lightning.loops.base.Loop method) state_key (pytorch_lightning.callbacks.base.Callback property) (pytorch_lightning.callbacks.Callback property) (pytorch_lightning.callbacks.early_stopping.EarlyStopping property) (pytorch_lightning.callbacks.EarlyStopping property) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint property) (pytorch_lightning.callbacks.ModelCheckpoint property) status (pytorch_lightning.loggers.base.LightningLoggerBase.finalize parameter) (pytorch_lightning.loggers.base.LoggerCollection.finalize parameter) (pytorch_lightning.loggers.csv_logs.CSVLogger.finalize parameter) (pytorch_lightning.loggers.CSVLogger.finalize parameter) (pytorch_lightning.loggers.mlflow.MLFlowLogger.finalize parameter) (pytorch_lightning.loggers.MLFlowLogger.finalize parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.finalize parameter) (pytorch_lightning.loggers.NeptuneLogger.finalize parameter) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger.finalize parameter) (pytorch_lightning.loggers.TensorBoardLogger.finalize parameter) (pytorch_lightning.loggers.test_tube.TestTubeLogger.finalize parameter) (pytorch_lightning.loggers.TestTubeLogger.finalize parameter) (pytorch_lightning.loggers.wandb.WandbLogger.finalize parameter) (pytorch_lightning.loggers.WandbLogger.finalize parameter) step (pytorch_lightning.loggers.base.DummyLogger.log_metrics parameter) (pytorch_lightning.loggers.base.LightningLoggerBase.agg_and_log_metrics parameter) (pytorch_lightning.loggers.base.LightningLoggerBase.log_metrics parameter) (pytorch_lightning.loggers.base.LoggerCollection.agg_and_log_metrics parameter) (pytorch_lightning.loggers.base.LoggerCollection.log_metrics parameter) (pytorch_lightning.loggers.comet.CometLogger.log_metrics parameter) (pytorch_lightning.loggers.CometLogger.log_metrics parameter) (pytorch_lightning.loggers.csv_logs.CSVLogger.log_metrics parameter) (pytorch_lightning.loggers.CSVLogger.log_metrics parameter) (pytorch_lightning.loggers.mlflow.MLFlowLogger.log_metrics parameter) (pytorch_lightning.loggers.MLFlowLogger.log_metrics parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.log_metrics parameter) (pytorch_lightning.loggers.NeptuneLogger.log_metrics parameter) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger.log_metrics parameter) (pytorch_lightning.loggers.TensorBoardLogger.log_metrics parameter) (pytorch_lightning.loggers.test_tube.TestTubeLogger.log_metrics parameter) (pytorch_lightning.loggers.TestTubeLogger.log_metrics parameter) (pytorch_lightning.loggers.wandb.WandbLogger.log_metrics parameter) (pytorch_lightning.loggers.WandbLogger.log_metrics parameter) steps_per_trial (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) stochastic_weight_avg (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] StochasticWeightAveraging (class in pytorch_lightning.callbacks) stop() (pytorch_lightning.profiler.AbstractProfiler method) (pytorch_lightning.profiler.AdvancedProfiler method) (pytorch_lightning.profiler.BaseProfiler method) (pytorch_lightning.profiler.PassThroughProfiler method) (pytorch_lightning.profiler.PyTorchProfiler method) (pytorch_lightning.profiler.SimpleProfiler method) (pytorch_lightning.profiler.XLAProfiler method) stopping_threshold (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] storage_options (pytorch_lightning.plugins.io.CheckpointIO.load_checkpoint parameter) (pytorch_lightning.plugins.io.CheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.XLACheckpointIO.save_checkpoint parameter) strategy (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] strict (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] (pytorch_lightning.core.lightning.LightningModule.load_from_checkpoint parameter) sub_dir (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger property) sub_group_size (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] subclass_mode (pytorch_lightning.utilities.cli.LightningArgumentParser.add_lightning_class_args parameter) subclass_mode_data (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] subclass_mode_model (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] subcommands() (pytorch_lightning.utilities.cli.LightningCLI static method) summarize() (pytorch_lightning.core.lightning.LightningModule method) summary() (pytorch_lightning.profiler.AbstractProfiler method) (pytorch_lightning.profiler.AdvancedProfiler method) (pytorch_lightning.profiler.BaseProfiler method) (pytorch_lightning.profiler.PassThroughProfiler method) (pytorch_lightning.profiler.PyTorchProfiler method) (pytorch_lightning.profiler.SimpleProfiler method) (pytorch_lightning.profiler.XLAProfiler method) swa_epoch_start (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1] swa_lrs (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1] sync_batchnorm (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] sync_dist (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] sync_dist_group (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] sync_grads (pytorch_lightning.accelerators.Accelerator.all_gather parameter) (pytorch_lightning.core.lightning.LightningModule.all_gather parameter) (pytorch_lightning.lite.LightningLite.all_gather parameter), [1] (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.all_gather parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.all_gather parameter) synchronize_checkpoint_boundary (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2]

T

tags (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] tbptt_split_batch() (pytorch_lightning.core.lightning.LightningModule method) teardown() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.GPUAccelerator method) (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.DataHooks method) (pytorch_lightning.loops.base.Loop method) (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.training_type.DataParallelPlugin method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) (pytorch_lightning.plugins.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.SingleDevicePlugin method) (pytorch_lightning.plugins.training_type.SingleTPUPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) (pytorch_lightning.profiler.AbstractProfiler method) (pytorch_lightning.profiler.AdvancedProfiler method) (pytorch_lightning.profiler.BaseProfiler method) (pytorch_lightning.profiler.PyTorchProfiler method) temperature (pytorch_lightning.callbacks.gpu_stats_monitor.GPUStatsMonitor parameter), [1] (pytorch_lightning.callbacks.GPUStatsMonitor parameter), [1] tensor (pytorch_lightning.accelerators.Accelerator.all_gather parameter) (pytorch_lightning.lite.LightningLite.backward parameter), [1] (pytorch_lightning.plugins.training_type.DDPPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.HorovodPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.SingleDevicePlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.all_gather parameter) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.all_gather parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.reduce parameter) TensorBoardLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.tensorboard) terminate_on_nan (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] test() (pytorch_lightning.trainer.trainer.Trainer method) test_batch_idx (pytorch_lightning.callbacks.ProgressBarBase property) test_dataloader() (pytorch_lightning.core.hooks.DataHooks method) test_dataset (pytorch_lightning.core.datamodule.LightningDataModule.from_datasets parameter) test_epoch_end() (pytorch_lightning.core.lightning.LightningModule method) test_step() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) test_step_context() (pytorch_lightning.plugins.precision.PrecisionPlugin method) test_step_end() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) test_transforms (pytorch_lightning.core.datamodule.LightningDataModule property) TestTubeLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.test_tube) theme (pytorch_lightning.callbacks.RichProgressBar parameter), [1] thread_count (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] to_device() (pytorch_lightning.lite.LightningLite method) to_onnx() (pytorch_lightning.core.lightning.LightningModule method) to_torchscript() (pytorch_lightning.core.lightning.LightningModule method) to_yaml() (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) toggle_optimizer() (pytorch_lightning.core.lightning.LightningModule method) TorchCheckpointIO (class in pytorch_lightning.plugins.io) TorchElasticEnvironment (class in pytorch_lightning.plugins.environments) total_batch_idx (pytorch_lightning.loops.epoch.TrainingEpochLoop property) (pytorch_lightning.loops.FitLoop property) total_predict_batches (pytorch_lightning.callbacks.ProgressBarBase property)

total_test_batches (pytorch_lightning.callbacks.ProgressBarBase property) total_train_batches (pytorch_lightning.callbacks.ProgressBarBase property) total_val_batches (pytorch_lightning.callbacks.ProgressBarBase property) tpu_cores (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] TPUAccelerator (class in pytorch_lightning.accelerators) TPUBf16PrecisionPlugin (class in pytorch_lightning.plugins.precision) TPUPrecisionPlugin (class in pytorch_lightning.plugins.precision) TPUSpawnPlugin (class in pytorch_lightning.plugins.training_type) track_grad_norm (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] tracking_uri (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] train_batch_idx (pytorch_lightning.callbacks.ProgressBarBase property) train_bn (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] (pytorch_lightning.callbacks.BaseFinetuning.filter_params parameter) (pytorch_lightning.callbacks.BaseFinetuning.freeze parameter) (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) train_dataloader() (pytorch_lightning.core.hooks.DataHooks method) train_dataloaders (pytorch_lightning.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.tune parameter) (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) train_dataset (pytorch_lightning.core.datamodule.LightningDataModule.from_datasets parameter) train_step_context() (pytorch_lightning.plugins.precision.PrecisionPlugin method) train_time_interval (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] train_transforms (pytorch_lightning.core.datamodule.LightningDataModule property) Trainer (class in pytorch_lightning.trainer.trainer) trainer (pytorch_lightning.accelerators.Accelerator.setup parameter) (pytorch_lightning.accelerators.Accelerator.setup_optimizers parameter) (pytorch_lightning.accelerators.GPUAccelerator.setup parameter) (pytorch_lightning.callbacks.BackboneFinetuning.on_load_checkpoint parameter) (pytorch_lightning.callbacks.BackboneFinetuning.on_save_checkpoint parameter) (pytorch_lightning.callbacks.base.Callback.on_load_checkpoint parameter) (pytorch_lightning.callbacks.base.Callback.on_save_checkpoint parameter) (pytorch_lightning.callbacks.BaseFinetuning.on_load_checkpoint parameter) (pytorch_lightning.callbacks.BaseFinetuning.on_save_checkpoint parameter) (pytorch_lightning.callbacks.Callback.on_load_checkpoint parameter), [1] (pytorch_lightning.callbacks.Callback.on_save_checkpoint parameter), [1] (pytorch_lightning.callbacks.early_stopping.EarlyStopping.on_load_checkpoint parameter) (pytorch_lightning.callbacks.early_stopping.EarlyStopping.on_save_checkpoint parameter) (pytorch_lightning.callbacks.EarlyStopping.on_load_checkpoint parameter) (pytorch_lightning.callbacks.EarlyStopping.on_save_checkpoint parameter) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint.on_load_checkpoint parameter) (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint.on_save_checkpoint parameter) (pytorch_lightning.callbacks.ModelCheckpoint.on_load_checkpoint parameter) (pytorch_lightning.callbacks.ModelCheckpoint.on_save_checkpoint parameter) (pytorch_lightning.callbacks.ModelPruning.on_save_checkpoint parameter) trainer_class (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] trainer_defaults (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] training_epoch_end() (pytorch_lightning.core.lightning.LightningModule method) training_step() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) training_step_end() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) training_type_plugin (pytorch_lightning.accelerators.Accelerator parameter), [1], [2] (pytorch_lightning.accelerators.CPUAccelerator parameter), [1], [2] (pytorch_lightning.accelerators.GPUAccelerator parameter), [1], [2] (pytorch_lightning.accelerators.IPUAccelerator parameter), [1], [2] (pytorch_lightning.accelerators.TPUAccelerator parameter), [1], [2] TrainingBatchLoop (class in pytorch_lightning.loops.batch) TrainingEpochLoop (class in pytorch_lightning.loops.epoch) TrainingTypePlugin (class in pytorch_lightning.plugins.training_type) transfer_batch_to_device() (pytorch_lightning.core.hooks.DataHooks method) truncated_bptt_steps (pytorch_lightning.core.lightning.LightningModule property) tune() (pytorch_lightning.trainer.trainer.Trainer method) Tuner (class in pytorch_lightning.tuner.tuning)

U

unfreeze() (pytorch_lightning.core.lightning.LightningModule method) unfreeze_and_add_param_group() (pytorch_lightning.callbacks.BaseFinetuning static method) unfreeze_backbone_at_epoch (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] untoggle_optimizer() (pytorch_lightning.core.lightning.LightningModule method) unused (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_end parameter), [1] (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_start parameter), [1] update_agg_funcs() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection method)

update_attr (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) update_lr_schedulers() (pytorch_lightning.loops.epoch.TrainingEpochLoop method) update_parameters() (pytorch_lightning.callbacks.StochasticWeightAveraging static method) use_argument_group (pytorch_lightning.utilities.argparse.add_argparse_args parameter), [1] use_global_unstructured (pytorch_lightning.callbacks.ModelPruning parameter), [1] use_lottery_ticket_hypothesis (pytorch_lightning.callbacks.ModelPruning parameter), [1] use_pl_optimizer (pytorch_lightning.core.lightning.LightningModule.optimizers parameter) using_lbfgs (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1] using_native_amp (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1]

V

val_batch_idx (pytorch_lightning.callbacks.ProgressBarBase property) val_check_interval (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] val_dataloader() (pytorch_lightning.core.hooks.DataHooks method) val_dataloaders (pytorch_lightning.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.tune parameter) (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) val_dataset (pytorch_lightning.core.datamodule.LightningDataModule.from_datasets parameter) val_step_context() (pytorch_lightning.plugins.precision.PrecisionPlugin method) val_transforms (pytorch_lightning.core.datamodule.LightningDataModule property) validate() (pytorch_lightning.trainer.trainer.Trainer method) validation_epoch_end() (pytorch_lightning.core.lightning.LightningModule method) validation_step() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) validation_step_end() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) value (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] verbose (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelPruning parameter), [1] (pytorch_lightning.callbacks.XLAStatsMonitor parameter), [1] (pytorch_lightning.trainer.Trainer.test parameter), [1] (pytorch_lightning.trainer.trainer.Trainer.test parameter) (pytorch_lightning.trainer.trainer.Trainer.validate parameter) (pytorch_lightning.trainer.Trainer.validate parameter)

version (pytorch_lightning.loggers.base.DummyLogger property) (pytorch_lightning.loggers.base.LightningLoggerBase property) (pytorch_lightning.loggers.base.LoggerCollection property) (pytorch_lightning.loggers.comet.CometLogger property) (pytorch_lightning.loggers.CometLogger property) (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger property) (pytorch_lightning.loggers.neptune.NeptuneLogger property) (pytorch_lightning.loggers.NeptuneLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger property) (pytorch_lightning.loggers.test_tube.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.test_tube.TestTubeLogger property) (pytorch_lightning.loggers.TestTubeLogger parameter), [1] (pytorch_lightning.loggers.TestTubeLogger property) (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger property) (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger property)

W

WandbLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.wandb) weights_save_path (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] (pytorch_lightning.trainer.trainer.Trainer property) weights_summary (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] workers (pytorch_lightning.utilities.seed.seed_everything parameter), [1] world_size (pytorch_lightning.lite.LightningLite property)

world_size() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) write_interval (pytorch_lightning.callbacks.BasePredictionWriter parameter), [1] write_on_batch_end() (pytorch_lightning.callbacks.BasePredictionWriter method) write_on_epoch_end() (pytorch_lightning.callbacks.BasePredictionWriter method)

X

XLACheckpointIO (class in pytorch_lightning.plugins.io)

XLAProfiler (class in pytorch_lightning.profiler) XLAStatsMonitor (class in pytorch_lightning.callbacks)

Z

zero_allow_untested_optimizer (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2]

zero_optimization (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2]