Index Symbols | A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | V | W | 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.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.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) > 1` (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] A a potential deadlock in pytorch when using tensor parallelism (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] AbstractProfiler (class in pytorch_lightning.profiler.profilers) 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_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) AdvancedProfiler (class in pytorch_lightning.profiler.profilers) after_fit() (pytorch_lightning.utilities.cli.LightningCLI 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.accelerators.Accelerator.predict_step parameter) (pytorch_lightning.accelerators.Accelerator.test_step parameter) (pytorch_lightning.accelerators.Accelerator.training_step parameter) (pytorch_lightning.accelerators.Accelerator.validation_step parameter) (pytorch_lightning.core.datamodule.LightningDataModule.from_argparse_args parameter) (pytorch_lightning.core.lightning.LightningModule.save_hyperparameters parameter), [1] (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] 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_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.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) balance (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] balance_mode (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] 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.RPCSequentialPlugin 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.profilers) 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) 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) 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.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.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.training_type.DeepSpeedPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] (pytorch_lightning.plugins.training_type.TPUSpawnPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.save_checkpoint parameter) checkpoint_callback (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.plugins.training_type.DeepSpeedPlugin.restore_model_state_from_ckpt_path parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.restore_model_state_from_ckpt_path parameter) (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) 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.accelerators.TPUAccelerator 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.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.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] 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] cpu_offload (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] cpu_offload_params (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] cpu_offload_use_pin_memory (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.LightningEnvironment 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 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.core.hooks.DataHooks.on_after_batch_transfer parameter), [1] (pytorch_lightning.core.hooks.DataHooks.on_before_batch_transfer 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.Trainer.predict 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 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(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 property) (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) 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) (pytorch_lightning.profiler.profilers.AdvancedProfiler parameter), [1] (pytorch_lightning.profiler.profilers.SimpleProfiler parameter), [1] (pytorch_lightning.profiler.PyTorchProfiler parameter) (pytorch_lightning.profiler.SimpleProfiler parameter) filepath (pytorch_lightning.accelerators.Accelerator.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.DeepSpeedPlugin.save_checkpoint parameter) (pytorch_lightning.plugins.training_type.RPCPlugin.rpc_save_model parameter) (pytorch_lightning.plugins.training_type.RPCSequentialPlugin.rpc_save_model 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 (pytorch_lightning.core.lightning.LightningModule.save_hyperparameters parameter), [1] 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) G get_init_arguments_and_types() (in module pytorch_lightning.utilities.argparse) (pytorch_lightning.core.datamodule.LightningDataModule class method) get_progress_bar_dict() (pytorch_lightning.core.lightning.LightningModule method) global_rank() (pytorch_lightning.core.lightning.LightningModule property) (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment 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) 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) H 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), [1] image (pytorch_lightning.loggers.neptune.NeptuneLogger.log_image parameter) (pytorch_lightning.loggers.NeptuneLogger.log_image parameter) init_parser() (pytorch_lightning.utilities.cli.LightningCLI method) init_predict_tqdm() (pytorch_lightning.callbacks.progress.ProgressBar method) (pytorch_lightning.callbacks.ProgressBar method) init_sanity_tqdm() (pytorch_lightning.callbacks.progress.ProgressBar method) (pytorch_lightning.callbacks.ProgressBar method) init_test_tqdm() (pytorch_lightning.callbacks.progress.ProgressBar method) (pytorch_lightning.callbacks.ProgressBar method) init_train_tqdm() (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) (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] 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(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) L lambda_closure (pytorch_lightning.accelerators.Accelerator.optimizer_step parameter) 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) 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 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(pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] line_count_restriction (pytorch_lightning.profiler.AdvancedProfiler parameter) (pytorch_lightning.profiler.profilers.AdvancedProfiler parameter), [1] local_rank() (pytorch_lightning.core.lightning.LightningModule property) (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) log() (pytorch_lightning.core.lightning.LightningModule method) log_artifact() (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) log_dict() (pytorch_lightning.core.lightning.LightningModule method) log_dir (pytorch_lightning.loggers.csv_logs.ExperimentWriter parameter), [1] log_dir() (pytorch_lightning.loggers.csv_logs.CSVLogger property) (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_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.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) log_metric() (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger 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_momentum (pytorch_lightning.callbacks.LearningRateMonitor parameter), [1] (pytorch_lightning.callbacks.lr_monitor.LearningRateMonitor parameter), [1] log_name (pytorch_lightning.loggers.neptune.NeptuneLogger.log_image parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.log_text parameter) (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.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] logger() (pytorch_lightning.core.lightning.LightningModule property) 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] loss (pytorch_lightning.core.lightning.LightningModule.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) M 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) map_location (pytorch_lightning.core.lightning.LightningModule.load_from_checkpoint parameter) (pytorch_lightning.plugins.training_type.DeepSpeedPlugin.restore_model_state_from_ckpt_path parameter) (pytorch_lightning.plugins.training_type.TrainingTypePlugin.restore_model_state_from_ckpt_path parameter) master_address() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) master_params() (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) master_port() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) max_epochs (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] max_lr (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) max_steps (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_name (pytorch_lightning.loggers.neptune.NeptuneLogger.log_metric parameter) (pytorch_lightning.loggers.NeptuneLogger.log_metric parameter) metric_value (pytorch_lightning.loggers.neptune.NeptuneLogger.log_metric parameter) (pytorch_lightning.loggers.NeptuneLogger.log_metric parameter) 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) microbatches (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] min_delta (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping parameter), [1] min_epochs (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.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] 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.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) model (pytorch_lightning.accelerators.Accelerator.setup parameter) (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.NativeMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) (pytorch_lightning.plugins.training_type.ParallelPlugin.configure_sync_batchnorm parameter) (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) model() (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) 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_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) 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.profiler.profilers 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.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger 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] name() (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 property) (pytorch_lightning.loggers.WandbLogger property) 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) node_rank() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) not provided assumes user provides an input example array to find a balance on all GPUs. (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] num_nodes (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) O obj (pytorch_lightning.accelerators.Accelerator.broadcast parameter) 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] offline_mode (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] 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_batch_transfer() (pytorch_lightning.core.hooks.DataHooks 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_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() 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(pytorch_lightning.callbacks.ProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_epoch_end() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_epoch_start() (pytorch_lightning.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback 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.callbacks.base.Callback method) (pytorch_lightning.callbacks.Callback method) (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.hooks.ModelHooks method) opt_idx (pytorch_lightning.accelerators.Accelerator.optimizer_step parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward 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_zero_grad 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.plugins.precision.ApexMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) optimizer_closure (pytorch_lightning.core.lightning.LightningModule.optimizer_step parameter), [1] optimizer_idx (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) 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] 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 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parameter), [1] pipelined_backward (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] pl_module (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.training_type.HorovodPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) post_dispatch() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.precision.DoublePrecisionPlugin 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.RPCSequentialPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) pre_backward() (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.RPCSequentialPlugin 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.core.lightning.LightningModule attribute) (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.profilers.BaseProfiler method) profiler (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] profiler_kwargs (pytorch_lightning.profiler.PyTorchProfiler parameter) 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] 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.profiler.profilers module pytorch_lightning.trainer.trainer module pytorch_lightning.utilities.argparse module pytorch_lightning.utilities.cli module pytorch_lightning.utilities.seed module Q qconfig (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1] QuantizationAwareTraining (class in pytorch_lightning.callbacks) R rank_zero_experiment() (in module pytorch_lightning.loggers.base) reconciliate_processes() (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.ParallelPlugin method) record_functions (pytorch_lightning.profiler.PyTorchProfiler parameter) record_module_names (pytorch_lightning.profiler.PyTorchProfiler parameter) 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] 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] restore_model_state_from_ckpt_path() (pytorch_lightning.plugins.training_type.DeepSpeedPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) 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.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) rpc_save_model() (pytorch_lightning.plugins.training_type.RPCPlugin method) (pytorch_lightning.plugins.training_type.RPCSequentialPlugin method) RPCPlugin (class in pytorch_lightning.plugins.training_type) RPCSequentialPlugin (class in pytorch_lightning.plugins.training_type) 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.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) save_config_callback (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_dir (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.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] save_dir() (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 property) (pytorch_lightning.loggers.WandbLogger property) save_full_weights (pytorch_lightning.plugins.training_type.DeepSpeedPlugin parameter), [1], [2] save_hyperparameters() (pytorch_lightning.core.lightning.LightningModule method) save_last (pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint parameter), [1] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1] save_model_fn (pytorch_lightning.plugins.training_type.RPCPlugin.rpc_save_model parameter) (pytorch_lightning.plugins.training_type.RPCSequentialPlugin.rpc_save_model parameter) 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 method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.DataHooks 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.TPUSpawnPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) (pytorch_lightning.profiler.profilers.AbstractProfiler method) (pytorch_lightning.profiler.profilers.BaseProfiler method) setup_environment() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.plugins.training_type.DDPPlugin method) (pytorch_lightning.plugins.training_type.TrainingTypePlugin method) setup_optimizers() (pytorch_lightning.accelerators.Accelerator method) setup_optimizers_in_pre_dispatch() (pytorch_lightning.accelerators.Accelerator property) (pytorch_lightning.plugins.training_type.TrainingTypePlugin property) 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_accumulate (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.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) should_align (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1] SimpleProfiler (class in pytorch_lightning.profiler.profilers) SingleDevicePlugin (class in pytorch_lightning.plugins.training_type) SingleTPUPlugin (class in pytorch_lightning.plugins.training_type) size() (pytorch_lightning.core.datamodule.LightningDataModule method) SLURMEnvironment (class in pytorch_lightning.plugins.environments) sort_by_key (pytorch_lightning.profiler.PyTorchProfiler parameter) split_size (pytorch_lightning.core.lightning.LightningModule.tbptt_split_batch parameter), [1] splitting the batch into further smaller batches. (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] src (pytorch_lightning.accelerators.Accelerator.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.profilers.AbstractProfiler method) (pytorch_lightning.profiler.profilers.AdvancedProfiler method) (pytorch_lightning.profiler.profilers.BaseProfiler method) (pytorch_lightning.profiler.profilers.PassThroughProfiler method) (pytorch_lightning.profiler.profilers.SimpleProfiler method) 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_image parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.log_metric parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.log_metrics parameter) (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) 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.profilers.AbstractProfiler method) (pytorch_lightning.profiler.profilers.AdvancedProfiler method) (pytorch_lightning.profiler.profilers.BaseProfiler method) (pytorch_lightning.profiler.profilers.PassThroughProfiler method) (pytorch_lightning.profiler.profilers.SimpleProfiler method) stopping_threshold (pytorch_lightning.callbacks.early_stopping.EarlyStopping parameter), [1] (pytorch_lightning.callbacks.EarlyStopping 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) 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] summary() (pytorch_lightning.profiler.profilers.AbstractProfiler method) (pytorch_lightning.profiler.profilers.AdvancedProfiler method) (pytorch_lightning.profiler.profilers.BaseProfiler method) (pytorch_lightning.profiler.profilers.PassThroughProfiler method) (pytorch_lightning.profiler.profilers.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_dist_op (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_pad_token (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] tbptt_reduce_fx (pytorch_lightning.core.lightning.LightningModule.log parameter), [1] (pytorch_lightning.core.lightning.LightningModule.log_dict parameter), [1] tbptt_split_batch() (pytorch_lightning.core.lightning.LightningModule method) teardown() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.GPUAccelerator method) (pytorch_lightning.accelerators.TPUAccelerator 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.profiler.profilers.AbstractProfiler method) (pytorch_lightning.profiler.profilers.AdvancedProfiler method) (pytorch_lightning.profiler.profilers.BaseProfiler 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.core.lightning.LightningModule.all_gather parameter) (pytorch_lightning.plugins.training_type.DataParallelPlugin.reduce parameter) (pytorch_lightning.plugins.training_type.DDP2Plugin.reduce 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 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.progress.ProgressBarBase property) (pytorch_lightning.callbacks.ProgressBarBase property) test_dataloader() (pytorch_lightning.core.hooks.DataHooks method) test_dataloaders (pytorch_lightning.trainer.Trainer.test parameter), [1] (pytorch_lightning.trainer.trainer.Trainer.test parameter) 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.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin 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) text (pytorch_lightning.loggers.neptune.NeptuneLogger.log_text parameter) (pytorch_lightning.loggers.NeptuneLogger.log_text parameter) the same time. Defaults to `True` if (pytorch_lightning.plugins.training_type.RPCSequentialPlugin parameter), [1], [2] to_device() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.GPUAccelerator 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) 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 pytorch_lightning.callbacks.progress) 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.progress.ProgressBarBase property) (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.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_dataloader() (pytorch_lightning.core.hooks.DataHooks method) 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_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.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) (pytorch_lightning.core.lightning.LightningModule attribute) (pytorch_lightning.plugins.training_type.RPCPlugin.rpc_save_model parameter) (pytorch_lightning.plugins.training_type.RPCSequentialPlugin.rpc_save_model 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.TPUAccelerator parameter), [1], [2] TrainingTypePlugin (class in pytorch_lightning.plugins.training_type) transfer_batch_to_device() (pytorch_lightning.core.hooks.DataHooks method) truncated_bptt_steps (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] 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) 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_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_amp (pytorch_lightning.core.lightning.LightningModule attribute) 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] 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.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) 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.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.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger 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] 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 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 property) (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.LightningEnvironment 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) 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]