Index Symbols | A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Z Symbols **kwargs (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.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger 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.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.SingleDevicePlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.reduce parameter) (pytorch_lightning.utilities.argparse.from_argparse_args 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.plugins.training_type.DataParallelPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDP2Plugin.reduce parameter) (pytorch_lightning.plugins.training_type.SingleDevicePlugin.reduce parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.reduce parameter) A AbstractProfiler (class in pytorch_lightning.profiler) Accelerator (class in pytorch_lightning.accelerators) accelerator (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_configure_optimizers_method_to_model() (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_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) AdvancedProfiler (class in pytorch_lightning.profiler) after_fit() (pytorch_lightning.utilities.cli.LightningCLI method) after_save_checkpoint() (pytorch_lightning.loggers.base.LightningLoggerBase method) (pytorch_lightning.loggers.base.LoggerCollection 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.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] 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] append_tags() (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) 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.neptune.NeptuneLogger.log_hyperparams parameter) (pytorch_lightning.loggers.NeptuneLogger.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 (pytorch_lightning.loggers.neptune.NeptuneLogger.log_artifact parameter) (pytorch_lightning.loggers.NeptuneLogger.log_artifact parameter) artifact_location (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] 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_move_data() (in module pytorch_lightning.core.decorators) 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] 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.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) barrier() (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] 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] 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] batch_to_device() (pytorch_lightning.accelerators.Accelerator method) before_fit() (pytorch_lightning.utilities.cli.LightningCLI 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.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 call_configure_sharded_model_hook (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) 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.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.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] checkpoint_path (pytorch_lightning.core.lightning.LightningModule.load_from_checkpoint parameter) CheckpointHooks (class in pytorch_lightning.core.hooks) ckpt_path (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) clip_grad_by_norm() (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.accelerators.Accelerator method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin 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) close_after_fit (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] 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.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] configure_callbacks() (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.plugins.precision.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.precision.TPUHalfPrecisionPlugin method) (pytorch_lightning.plugins.training_type.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) connect_precision_plugin() (pytorch_lightning.accelerators.Accelerator method) connect_training_type_plugin() (pytorch_lightning.accelerators.Accelerator method) contiguous_gradients (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] contiguous_memory_optimization (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] convert_inf() (in module pytorch_lightning.callbacks.progress) 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) (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) CSVLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.csv_logs) current_epoch (pytorch_lightning.core.lightning.LightningModule property) current_global_step (pytorch_lightning.plugins.training_type.DeepSpeedPlugin.update_global_step parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.update_global_step parameter) D data (pytorch_lightning.core.lightning.LightningModule.all_gather 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_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.test_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.validation_step parameter), [1] dataloaders (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) 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(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.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] 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] (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger 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.core.lightning.LightningModule.write_prediction 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.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) filter_on_optimizer() 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(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) (pytorch_lightning.utilities.cli.LightningCLI method) flatten_modules() (pytorch_lightning.callbacks.BaseFinetuning static method) flush_logs_every_n_steps (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] fn (pytorch_lightning.core.decorators.auto_move_data parameter), [1] (pytorch_lightning.core.decorators.parameter_validation parameter), [1] format_checkpoint_name() (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelCheckpoint method) format_num() (pytorch_lightning.callbacks.progress.tqdm static method) forward() (pytorch_lightning.core.lightning.LightningModule method) frame 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(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) 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.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.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] gradient_clip_val (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.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) group_by_input_shapes (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] H 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(pytorch_lightning.callbacks.progress.ProgressBar method) (pytorch_lightning.callbacks.ProgressBar method) init_val (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) init_validation_tqdm() (pytorch_lightning.callbacks.progress.ProgressBar method) (pytorch_lightning.callbacks.ProgressBar method) 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) 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(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 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(pytorch_lightning.loggers.NeptuneLogger.log_image parameter) (pytorch_lightning.loggers.NeptuneLogger.log_text parameter) log_text() (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger 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] 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(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 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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] 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.core.lightning.LightningModule.write_prediction 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 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) 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(pytorch_lightning.core.hooks.ModelHooks.on_before_optimizer_step parameter), [1] (pytorch_lightning.core.lightning.LightningModule.backward 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) optimizer_zero_grad() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.core.lightning.LightningModule method) 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) 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] 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) parser (pytorch_lightning.utilities.cli.LightningCLI.add_arguments_to_parser parameter) 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) patience (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] period (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint 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.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.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.DDPSpawnPlugin method) post_optimizer_step() (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin 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.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) pre_optimizer_step() (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) precision (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.TPUAccelerator parameter), [1], [2] PrecisionPlugin (class in pytorch_lightning.plugins.precision) predict() (pytorch_lightning.trainer.trainer.Trainer method) predict_batch_idx (pytorch_lightning.callbacks.progress.ProgressBarBase property) (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.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) predictions_dict (pytorch_lightning.core.lightning.LightningModule.write_prediction_dict parameter), [1] 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] prepare_data() (pytorch_lightning.core.hooks.DataHooks method) prepare_data_per_node (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] prepare_fit_kwargs() (pytorch_lightning.utilities.cli.LightningCLI method) print() (pytorch_lightning.callbacks.progress.ProgressBar method) (pytorch_lightning.callbacks.progress.ProgressBarBase method) (pytorch_lightning.callbacks.ProgressBar method) (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.core.lightning.LightningModule 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.callbacks.progress.ProgressBar parameter), [1] (pytorch_lightning.callbacks.ProgressBar parameter), [1] (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_refresh_rate (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] ProgressBar (class in pytorch_lightning.callbacks) (class in pytorch_lightning.callbacks.progress) ProgressBarBase (class in pytorch_lightning.callbacks) (class in pytorch_lightning.callbacks.progress) project (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] (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger 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] 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] 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) reduce_scatter (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] refresh_rate (pytorch_lightning.callbacks.progress.ProgressBar parameter), [1] (pytorch_lightning.callbacks.ProgressBar parameter), [1] reinit_scheduler_properties() (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin static method) 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] replace_sampler_ddp (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] requires_grad (pytorch_lightning.callbacks.BaseFinetuning.filter_params parameter) resample_parameters (pytorch_lightning.callbacks.ModelPruning parameter), [1] reset() (in module pytorch_lightning.callbacks.progress) 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] 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.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.predict parameter) 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) round (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] row_limit (pytorch_lightning.profiler.PyTorchProfiler parameter), [1], [2] run_name (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] S sanitize_parameters_to_prune() (pytorch_lightning.callbacks.ModelPruning static method) save() (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.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_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_full_weights (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] 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) 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) seed_everything_default (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] set_property() (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger 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 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(pytorch_lightning.loggers.neptune.NeptuneLogger.log_text parameter) (pytorch_lightning.loggers.NeptuneLogger.log_image parameter) (pytorch_lightning.loggers.NeptuneLogger.log_metric parameter) (pytorch_lightning.loggers.NeptuneLogger.log_metrics parameter) (pytorch_lightning.loggers.NeptuneLogger.log_text 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) step_kwargs (pytorch_lightning.accelerators.Accelerator.predict_step parameter) (pytorch_lightning.accelerators.Accelerator.test_step parameter) (pytorch_lightning.accelerators.Accelerator.training_step parameter) 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(pytorch_lightning.core.lightning.LightningModule.load_from_checkpoint parameter) sub_dir (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] 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] 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) 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.plugins.training_type.TPUSpawnPlugin.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] (pytorch_lightning.loggers.neptune.NeptuneLogger.append_tags parameter) (pytorch_lightning.loggers.NeptuneLogger.append_tags parameter) 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.core.hooks.DataHooks method) (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.training_type.ParallelPlugin 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.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.reduce parameter) TensorBoardLogger (class in 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(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) text (pytorch_lightning.loggers.neptune.NeptuneLogger.log_text parameter) (pytorch_lightning.loggers.NeptuneLogger.log_text parameter) thread_count (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] 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) TorchElasticEnvironment (class in pytorch_lightning.plugins.environments) total_batch_idx (pytorch_lightning.plugins.training_type.DeepSpeedPlugin.update_global_step parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.update_global_step parameter) total_predict_batches (pytorch_lightning.callbacks.progress.ProgressBarBase property) (pytorch_lightning.callbacks.ProgressBarBase property) total_test_batches (pytorch_lightning.callbacks.progress.ProgressBarBase property) (pytorch_lightning.callbacks.ProgressBarBase property) total_train_batches (pytorch_lightning.callbacks.progress.ProgressBarBase property) (pytorch_lightning.callbacks.ProgressBarBase property) total_val_batches (pytorch_lightning.callbacks.progress.ProgressBarBase property) (pytorch_lightning.callbacks.ProgressBarBase property) tpu_cores (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] TPUAccelerator (class in pytorch_lightning.accelerators) TPUHalfPrecisionPlugin (class in pytorch_lightning.plugins.precision) TPUSpawnPlugin (class in pytorch_lightning.plugins.training_type) tqdm (class in 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(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.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin 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.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] 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(pytorch_lightning.loggers.base.LoggerCollection method) update_attr (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) update_global_step() (pytorch_lightning.plugins.training_type.DeepSpeedPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin 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.progress.ProgressBarBase property) (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.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin 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] (pytorch_lightning.core.lightning.LightningModule.write_prediction parameter), [1] (pytorch_lightning.loggers.neptune.NeptuneLogger.set_property parameter) (pytorch_lightning.loggers.NeptuneLogger.set_property parameter) 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] 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.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) write_prediction() (pytorch_lightning.core.lightning.LightningModule method) write_prediction_dict() (pytorch_lightning.core.lightning.LightningModule method) X 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]