Index

Symbols

**kwargs (pytorch_lightning.callbacks.LambdaCallback parameter), [1], [2] (pytorch_lightning.core.LightningDataModule.from_argparse_args parameter) (pytorch_lightning.core.LightningDataModule.load_from_checkpoint parameter) (pytorch_lightning.core.LightningModule.forward parameter) (pytorch_lightning.core.LightningModule.manual_backward parameter) (pytorch_lightning.core.LightningModule.print parameter) (pytorch_lightning.core.LightningModule.to_onnx parameter) (pytorch_lightning.core.LightningModule.to_torchscript parameter) (pytorch_lightning.core.module.LightningModule.forward parameter) (pytorch_lightning.core.module.LightningModule.load_from_checkpoint parameter) (pytorch_lightning.core.module.LightningModule.manual_backward parameter) (pytorch_lightning.core.module.LightningModule.print parameter) (pytorch_lightning.core.module.LightningModule.to_onnx parameter) (pytorch_lightning.core.module.LightningModule.to_torchscript parameter) (pytorch_lightning.core.saving.ModelIO.load_from_checkpoint parameter) (pytorch_lightning.lite.LightningLite.backward parameter), [1] (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.strategies.DDPStrategy.optimizer_step parameter) (pytorch_lightning.strategies.SingleDeviceStrategy.reduce parameter) (pytorch_lightning.strategies.Strategy.optimizer_step parameter) (pytorch_lightning.utilities.apply_func.apply_to_collection parameter), [1] (pytorch_lightning.utilities.apply_func.apply_to_collections parameter), [1] (pytorch_lightning.utilities.argparse.from_argparse_args parameter), [1]

**neptune_run_kwargs (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] **optimizer_kwargs (pytorch_lightning.strategies.HivemindStrategy parameter), [1] *args (pytorch_lightning.core.LightningModule.forward parameter) (pytorch_lightning.core.LightningModule.manual_backward parameter) (pytorch_lightning.core.LightningModule.print parameter) (pytorch_lightning.core.module.LightningModule.forward parameter) (pytorch_lightning.core.module.LightningModule.manual_backward parameter) (pytorch_lightning.core.module.LightningModule.print parameter) (pytorch_lightning.lite.LightningLite.backward parameter), [1] (pytorch_lightning.strategies.SingleDeviceStrategy.reduce parameter) (pytorch_lightning.utilities.apply_func.apply_to_collection parameter), [1] (pytorch_lightning.utilities.apply_func.apply_to_collections parameter), [1] *dataloaders (pytorch_lightning.lite.LightningLite.setup_dataloaders parameter), [1] *optimizers (pytorch_lightning.lite.LightningLite.setup parameter), [1]

_

__init__() (pytorch_lightning.lite.LightningLite method)

A

Accelerator (class in pytorch_lightning.accelerators) accelerator (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] accumulate_grad_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] add_argparse_args() (in module pytorch_lightning.utilities.argparse) (pytorch_lightning.core.LightningDataModule class method) add_dataloader_idx (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) advance() (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.ManualOptimization method) (pytorch_lightning.loops.optimization.OptimizerLoop method) AdvancedProfiler (class in pytorch_lightning.profilers) after_save_checkpoint() (pytorch_lightning.loggers.neptune.NeptuneLogger method) (pytorch_lightning.loggers.NeptuneLogger method) (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) agg_default_func (pytorch_lightning.loggers.base.LightningLoggerBase parameter), [1] agg_key_funcs (pytorch_lightning.loggers.base.LightningLoggerBase parameter), [1] algorithm (pytorch_lightning.strategies.BaguaStrategy parameter), [1] all_gather() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.strategies.HivemindStrategy method) (pytorch_lightning.strategies.HorovodStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.ParallelStrategy method) (pytorch_lightning.strategies.SingleDeviceStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) all_gather_ddp_if_available() (in module pytorch_lightning.utilities.distributed) allgather_bucket_size (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] allgather_partitions (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] AllGatherGrad (class in pytorch_lightning.utilities.distributed) allow_zero_length_dataloader_with_multiple_devices (pytorch_lightning.core.hooks.DataHooks attribute) amount (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] amp_backend (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] amp_level (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin parameter), [1], [2] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] amp_type (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin parameter), [1], [2] annealing_epochs (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1], [2] annealing_strategy (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1], [2] anonymous (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1]

ApexMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) api_key (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] apply() (pytorch_lightning.plugins.LayerSync method) (pytorch_lightning.plugins.NativeSyncBatchNorm method) apply_lottery_ticket_hypothesis() (pytorch_lightning.callbacks.ModelPruning method) apply_pruning (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] apply_pruning() (pytorch_lightning.callbacks.ModelPruning method) apply_to_collection() (in module pytorch_lightning.utilities.apply_func) apply_to_collections() (in module pytorch_lightning.utilities.apply_func) args (pytorch_lightning.core.LightningDataModule.from_argparse_args parameter) (pytorch_lightning.core.mixins.HyperparametersMixin.save_hyperparameters parameter) (pytorch_lightning.core.module.LightningModule.save_hyperparameters 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.wandb.WandbLogger.log_hyperparams parameter) (pytorch_lightning.loggers.WandbLogger.log_hyperparams parameter) (pytorch_lightning.utilities.argparse.from_argparse_args parameter), [1] artifact_location (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] AsyncCheckpointIO (class in pytorch_lightning.plugins.io) atomic_save() (in module pytorch_lightning.utilities.cloud_io) AttributeDict (class in pytorch_lightning.utilities.parsing) auto_device_count() (pytorch_lightning.accelerators.Accelerator static method) (pytorch_lightning.accelerators.CPUAccelerator static method) (pytorch_lightning.accelerators.CUDAAccelerator static method) (pytorch_lightning.accelerators.HPUAccelerator static method) (pytorch_lightning.accelerators.IPUAccelerator static method) (pytorch_lightning.accelerators.TPUAccelerator static method) auto_insert_metric_name (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] auto_lr_find (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] auto_registry (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] auto_requeue (pytorch_lightning.plugins.environments.SLURMEnvironment parameter), [1], [2] auto_scale_batch_size (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] auto_select_gpus (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] autocast() (pytorch_lightning.lite.LightningLite method) automatic_optimization (pytorch_lightning.core.LightningModule property) autoreport (pytorch_lightning.strategies.IPUStrategy parameter), [1] autoreport_dir (pytorch_lightning.strategies.IPUStrategy parameter), [1] averager_opts (pytorch_lightning.strategies.HivemindStrategy parameter), [1] averaging_timeout (pytorch_lightning.strategies.HivemindStrategy parameter), [1] avg_fn (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1], [2] avg_fn() (pytorch_lightning.callbacks.StochasticWeightAveraging static method)

B

backbone_initial_lr (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] backbone_initial_ratio_lr (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] BackboneFinetuning (class in pytorch_lightning.callbacks) backward() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin method) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.utilities.distributed.AllGatherGrad static method) bagua_kwargs (pytorch_lightning.strategies.BaguaStrategy parameter), [1] BaguaStrategy (class in pytorch_lightning.strategies) barrier() (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.strategies.BaguaStrategy method) (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.HivemindStrategy method) (pytorch_lightning.strategies.HorovodStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.SingleDeviceStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) BaseFinetuning (class in pytorch_lightning.callbacks) BasePredictionWriter (class in pytorch_lightning.callbacks) batch (pytorch_lightning.core.datamodule.LightningDataModule.on_after_batch_transfer parameter) (pytorch_lightning.core.datamodule.LightningDataModule.on_before_batch_transfer parameter) (pytorch_lightning.core.datamodule.LightningDataModule.transfer_batch_to_device parameter) (pytorch_lightning.core.hooks.DataHooks.on_after_batch_transfer parameter) (pytorch_lightning.core.hooks.DataHooks.on_before_batch_transfer parameter) (pytorch_lightning.core.hooks.DataHooks.transfer_batch_to_device parameter) (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) (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_start parameter) (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_start parameter) (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_start parameter) (pytorch_lightning.core.LightningModule.predict_step parameter) (pytorch_lightning.core.LightningModule.tbptt_split_batch parameter) (pytorch_lightning.core.LightningModule.test_step parameter) (pytorch_lightning.core.LightningModule.training_step parameter) (pytorch_lightning.core.LightningModule.validation_step parameter) (pytorch_lightning.core.module.LightningModule.on_after_batch_transfer parameter) (pytorch_lightning.core.module.LightningModule.on_before_batch_transfer parameter) (pytorch_lightning.core.module.LightningModule.on_predict_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_predict_batch_start parameter) (pytorch_lightning.core.module.LightningModule.on_test_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_test_batch_start parameter) (pytorch_lightning.core.module.LightningModule.on_train_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_train_batch_start parameter) (pytorch_lightning.core.module.LightningModule.on_validation_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_validation_batch_start parameter) (pytorch_lightning.core.module.LightningModule.predict_step parameter) (pytorch_lightning.core.module.LightningModule.tbptt_split_batch parameter) (pytorch_lightning.core.module.LightningModule.test_step parameter) (pytorch_lightning.core.module.LightningModule.training_step parameter) (pytorch_lightning.core.module.LightningModule.transfer_batch_to_device parameter) (pytorch_lightning.core.module.LightningModule.validation_step parameter) (pytorch_lightning.strategies.DataParallelStrategy.batch_to_device parameter) (pytorch_lightning.strategies.DeepSpeedStrategy.batch_to_device parameter) (pytorch_lightning.strategies.IPUStrategy.batch_to_device parameter) (pytorch_lightning.strategies.Strategy.batch_to_device parameter) (pytorch_lightning.utilities.apply_func.move_data_to_device 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) (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_start parameter) (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_start parameter) (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_start parameter) (pytorch_lightning.core.LightningModule.optimizer_step parameter) (pytorch_lightning.core.LightningModule.optimizer_zero_grad parameter) (pytorch_lightning.core.LightningModule.predict_step parameter) (pytorch_lightning.core.LightningModule.test_step parameter) (pytorch_lightning.core.LightningModule.training_step parameter) (pytorch_lightning.core.LightningModule.validation_step parameter) (pytorch_lightning.core.module.LightningModule.on_predict_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_predict_batch_start parameter) (pytorch_lightning.core.module.LightningModule.on_test_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_test_batch_start parameter) (pytorch_lightning.core.module.LightningModule.on_train_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_train_batch_start parameter) (pytorch_lightning.core.module.LightningModule.on_validation_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_validation_batch_start parameter) (pytorch_lightning.core.module.LightningModule.optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_zero_grad parameter) (pytorch_lightning.core.module.LightningModule.predict_step parameter) (pytorch_lightning.core.module.LightningModule.test_step parameter) (pytorch_lightning.core.module.LightningModule.training_step parameter) (pytorch_lightning.core.module.LightningModule.validation_step parameter) (pytorch_lightning.loops.epoch.TrainingEpochLoop property) (pytorch_lightning.loops.FitLoop property) batch_size (pytorch_lightning.core.LightningDataModule.from_datasets parameter) (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) (pytorch_lightning.strategies.HivemindStrategy parameter), [1] batch_to_device() (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DeepSpeedStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) benchmark (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] bf16_file_path (pytorch_lightning.plugins.precision.HPUPrecisionPlugin parameter), [1], [2] block_backward_sync() (pytorch_lightning.strategies.DDPShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnShardedStrategy method) (pytorch_lightning.strategies.ParallelStrategy method) block_size (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] broadcast() (pytorch_lightning.strategies.BaguaStrategy method) (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.HivemindStrategy method) (pytorch_lightning.strategies.HorovodStrategy method) (pytorch_lightning.strategies.HPUParallelStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.SingleDeviceStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) bucket_cap_mb (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1]

C

call_hook() (pytorch_lightning.trainer.trainer.Trainer method) Callback (class in pytorch_lightning.callbacks) callback_state (pytorch_lightning.callbacks.Callback.on_load_checkpoint parameter), [1] callbacks (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] check_finite (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] check_on_train_epoch_end (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] check_val_every_n_epoch (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] checkpoint (pytorch_lightning.callbacks.Callback.on_save_checkpoint parameter), [1] (pytorch_lightning.callbacks.ModelPruning.on_save_checkpoint parameter) (pytorch_lightning.core.hooks.CheckpointHooks.on_load_checkpoint parameter) (pytorch_lightning.core.hooks.CheckpointHooks.on_save_checkpoint parameter) (pytorch_lightning.core.module.LightningModule.on_hpc_load parameter) (pytorch_lightning.core.module.LightningModule.on_hpc_save parameter) (pytorch_lightning.core.module.LightningModule.on_load_checkpoint parameter) (pytorch_lightning.core.module.LightningModule.on_save_checkpoint parameter) (pytorch_lightning.core.saving.ModelIO.on_hpc_load parameter) (pytorch_lightning.core.saving.ModelIO.on_hpc_save parameter) (pytorch_lightning.plugins.io.CheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.HPUCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.XLACheckpointIO.save_checkpoint parameter) (pytorch_lightning.strategies.DeepSpeedStrategy.save_checkpoint parameter) (pytorch_lightning.strategies.Strategy.save_checkpoint parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.save_checkpoint parameter) (pytorch_lightning.utilities.cloud_io.atomic_save parameter), [1] checkpoint_callback (pytorch_lightning.loggers.neptune.NeptuneLogger.after_save_checkpoint parameter) (pytorch_lightning.loggers.NeptuneLogger.after_save_checkpoint parameter) (pytorch_lightning.loggers.wandb.WandbLogger.after_save_checkpoint parameter) (pytorch_lightning.loggers.WandbLogger.after_save_checkpoint parameter) (pytorch_lightning.trainer.trainer.Trainer property) checkpoint_callbacks (pytorch_lightning.trainer.trainer.Trainer property) checkpoint_dir (pytorch_lightning.utilities.deepspeed.convert_zero_checkpoint_to_fp32_state_dict parameter), [1] checkpoint_io (pytorch_lightning.plugins.io.AsyncCheckpointIO parameter), [1], [2] checkpoint_path (pytorch_lightning.core.LightningDataModule.load_from_checkpoint parameter) (pytorch_lightning.core.module.LightningModule.load_from_checkpoint parameter) (pytorch_lightning.core.saving.ModelIO.load_from_checkpoint parameter) CheckpointHooks (class in pytorch_lightning.core.hooks) CheckpointIO (class in pytorch_lightning.plugins.io) ckpt_path (pytorch_lightning.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.Trainer.test parameter), [1] (pytorch_lightning.trainer.trainer.Trainer property) (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.test parameter) (pytorch_lightning.trainer.trainer.Trainer.validate parameter) (pytorch_lightning.trainer.Trainer.validate parameter), [1] classes (pytorch_lightning.utilities.parsing.collect_init_args parameter), [1] clean_namespace() (in module pytorch_lightning.utilities.parsing) clip_grad_by_norm() (pytorch_lightning.plugins.precision.FullyShardedNativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.FullyShardedNativeNativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.precision.ShardedNativeMixedPrecisionPlugin method) clip_grad_by_value() (pytorch_lightning.plugins.precision.PrecisionPlugin method) clip_gradients() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin method) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) closure (pytorch_lightning.core.optimizer.LightningOptimizer.step parameter) (pytorch_lightning.strategies.DDPStrategy.optimizer_step parameter) (pytorch_lightning.strategies.Strategy.optimizer_step parameter)

closure_loss (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.pre_backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.post_backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.pre_backward parameter) (pytorch_lightning.strategies.Strategy.backward parameter) cls (pytorch_lightning.utilities.argparse.add_argparse_args parameter), [1] (pytorch_lightning.utilities.argparse.from_argparse_args parameter), [1] cluster_environment (pytorch_lightning.utilities.distributed.init_dist_connection parameter), [1] ClusterEnvironment (class in pytorch_lightning.plugins.environments) collect_init_args() (in module pytorch_lightning.utilities.parsing) collect_quantization (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1], [2] collection (pytorch_lightning.strategies.DataParallelStrategy.reduce parameter) CometLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.comet) compute_dtype (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1] config (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] configure_callbacks() (pytorch_lightning.core.LightningModule method) configure_gradient_clipping() (pytorch_lightning.core.LightningModule method) configure_optimizers() (pytorch_lightning.core.LightningModule method) configure_sharded_model() (pytorch_lightning.core.hooks.ModelHooks method) connect() (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.OptimizerLoop method) (pytorch_lightning.plugins.precision.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.precision.TPUBf16PrecisionPlugin method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) console_kwargs (pytorch_lightning.callbacks.RichProgressBar parameter), [1], [2] content (pytorch_lightning.lite.LightningLite.save parameter), [1] contiguous_gradients (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] contiguous_memory_optimization (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] convert_zero_checkpoint_to_fp32_state_dict() (in module pytorch_lightning.utilities.deepspeed) cpu() (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin method) cpu_checkpointing (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] cpu_offload (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1] cpu_stats (pytorch_lightning.callbacks.DeviceStatsMonitor parameter), [1], [2] CPUAccelerator (class in pytorch_lightning.accelerators) creates_processes_externally (pytorch_lightning.plugins.environments.ClusterEnvironment property) (pytorch_lightning.plugins.environments.KubeflowEnvironment property) (pytorch_lightning.plugins.environments.LightningEnvironment property) (pytorch_lightning.plugins.environments.LSFEnvironment property) (pytorch_lightning.plugins.environments.SLURMEnvironment property) (pytorch_lightning.plugins.environments.TorchElasticEnvironment property) (pytorch_lightning.plugins.environments.XLAEnvironment property) CSVLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.csv_logs) cuda() (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin method) CUDAAccelerator (class in pytorch_lightning.accelerators) current_dataloader (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) current_dataloader_idx (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) current_epoch (pytorch_lightning.core.LightningModule property) (pytorch_lightning.trainer.trainer.Trainer property)

D

data (pytorch_lightning.core.LightningModule.all_gather parameter) (pytorch_lightning.core.module.LightningModule.all_gather parameter) (pytorch_lightning.lite.LightningLite.all_gather parameter), [1] (pytorch_lightning.utilities.apply_func.apply_to_collection parameter), [1] data1 (pytorch_lightning.utilities.apply_func.apply_to_collections parameter), [1] data2 (pytorch_lightning.utilities.apply_func.apply_to_collections parameter), [1] data_fetcher (pytorch_lightning.loops.epoch.EvaluationEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.on_run_start parameter) DataHooks (class in pytorch_lightning.core.hooks) dataloader (pytorch_lightning.strategies.Strategy.process_dataloader parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.process_dataloader parameter) dataloader_id (pytorch_lightning.core.LightningModule.test_step parameter) (pytorch_lightning.core.module.LightningModule.test_step parameter) dataloader_idx (pytorch_lightning.core.datamodule.LightningDataModule.on_after_batch_transfer parameter) (pytorch_lightning.core.datamodule.LightningDataModule.on_before_batch_transfer parameter) (pytorch_lightning.core.datamodule.LightningDataModule.transfer_batch_to_device parameter) (pytorch_lightning.core.hooks.DataHooks.on_after_batch_transfer parameter) (pytorch_lightning.core.hooks.DataHooks.on_before_batch_transfer parameter) (pytorch_lightning.core.hooks.DataHooks.transfer_batch_to_device parameter) (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) (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_start parameter) (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_start parameter) (pytorch_lightning.core.LightningModule.predict_step parameter) (pytorch_lightning.core.LightningModule.validation_step parameter) (pytorch_lightning.core.module.LightningModule.on_after_batch_transfer parameter) (pytorch_lightning.core.module.LightningModule.on_before_batch_transfer parameter) (pytorch_lightning.core.module.LightningModule.on_predict_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_predict_batch_start parameter) (pytorch_lightning.core.module.LightningModule.on_test_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_test_batch_start parameter) (pytorch_lightning.core.module.LightningModule.on_validation_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_validation_batch_start parameter) (pytorch_lightning.core.module.LightningModule.predict_step parameter) (pytorch_lightning.core.module.LightningModule.transfer_batch_to_device parameter) (pytorch_lightning.core.module.LightningModule.validation_step parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) (pytorch_lightning.strategies.DataParallelStrategy.batch_to_device parameter) (pytorch_lightning.strategies.DeepSpeedStrategy.batch_to_device parameter) (pytorch_lightning.strategies.IPUStrategy.batch_to_device parameter) (pytorch_lightning.strategies.Strategy.batch_to_device parameter) dataloader_iter (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) DataLoaderLoop (class in pytorch_lightning.loops.dataloader.dataloader_loop) dataloaders (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) (pytorch_lightning.loops.dataloader.EvaluationLoop property) (pytorch_lightning.loops.dataloader.PredictionLoop property) (pytorch_lightning.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.Trainer.test parameter), [1] (pytorch_lightning.trainer.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.test parameter) (pytorch_lightning.trainer.trainer.Trainer.validate parameter) (pytorch_lightning.trainer.Trainer.validate parameter), [1] 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), [1] (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] DataParallelStrategy (class in pytorch_lightning.strategies) ddp_comm_hook (pytorch_lightning.utilities.distributed.register_ddp_comm_hook parameter), [1] ddp_comm_state (pytorch_lightning.utilities.distributed.register_ddp_comm_hook parameter), [1] ddp_comm_wrapper (pytorch_lightning.utilities.distributed.register_ddp_comm_hook parameter), [1] DDPFullyShardedStrategy (class in pytorch_lightning.strategies) DDPShardedStrategy (class in pytorch_lightning.strategies) DDPSpawnShardedStrategy (class in pytorch_lightning.strategies) DDPSpawnStrategy (class in pytorch_lightning.strategies) DDPStrategy (class in pytorch_lightning.strategies) DeepSpeedPrecisionPlugin (class in pytorch_lightning.plugins.precision) DeepSpeedStrategy (class in pytorch_lightning.strategies)

default_hp_metric (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] default_root_dir (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] (pytorch_lightning.trainer.trainer.Trainer property) delay_grad_averaging (pytorch_lightning.strategies.HivemindStrategy parameter), [1] delay_optimizer_step (pytorch_lightning.strategies.HivemindStrategy parameter), [1] delay_state_averaging (pytorch_lightning.strategies.HivemindStrategy parameter), [1] deprecated (pytorch_lightning.loggers.base.LightningLoggerBase parameter), [1] describe() (pytorch_lightning.profilers.Profiler method) description (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] detect() (pytorch_lightning.plugins.environments.ClusterEnvironment static method) (pytorch_lightning.plugins.environments.KubeflowEnvironment static method) (pytorch_lightning.plugins.environments.LightningEnvironment static method) (pytorch_lightning.plugins.environments.LSFEnvironment static method) (pytorch_lightning.plugins.environments.SLURMEnvironment static method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment static method) (pytorch_lightning.plugins.environments.XLAEnvironment static method) detect_anomaly (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] detect_nan_parameters() (in module pytorch_lightning.utilities.finite_checks) deterministic (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] device (pytorch_lightning.accelerators.Accelerator.get_device_stats parameter) (pytorch_lightning.accelerators.CUDAAccelerator.get_device_stats parameter) (pytorch_lightning.accelerators.TPUAccelerator.get_device_stats parameter) (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1], [2] (pytorch_lightning.core.datamodule.LightningDataModule.transfer_batch_to_device parameter) (pytorch_lightning.core.hooks.DataHooks.transfer_batch_to_device parameter) (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin.cuda parameter) (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin.to parameter) (pytorch_lightning.core.module.LightningModule.transfer_batch_to_device parameter) (pytorch_lightning.lite.LightningLite property) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin parameter), [1], [2] (pytorch_lightning.strategies.DataParallelStrategy.batch_to_device parameter) (pytorch_lightning.strategies.DeepSpeedStrategy.batch_to_device parameter) (pytorch_lightning.strategies.IPUStrategy.batch_to_device parameter) (pytorch_lightning.strategies.Strategy.batch_to_device parameter) (pytorch_lightning.utilities.apply_func.move_data_to_device parameter), [1] device_ids (pytorch_lightning.trainer.trainer.Trainer property) device_iterations (pytorch_lightning.strategies.IPUStrategy parameter), [1] DeviceDtypeModuleMixin (class in pytorch_lightning.core.mixins) devices (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] DeviceStatsMonitor (class in pytorch_lightning.callbacks) dictionary (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) dirpath (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] (pytorch_lightning.profilers.AdvancedProfiler parameter), [1] (pytorch_lightning.profilers.PyTorchProfiler parameter), [1] (pytorch_lightning.profilers.SimpleProfiler parameter), [1] disable() (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) dispatch() (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.strategies.Strategy method) divergence_threshold (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] dl_max_batches (pytorch_lightning.loops.epoch.EvaluationEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.on_run_start parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) done (pytorch_lightning.loops.batch.TrainingBatchLoop property) (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) (pytorch_lightning.loops.dataloader.EvaluationLoop property) (pytorch_lightning.loops.epoch.EvaluationEpochLoop property) (pytorch_lightning.loops.epoch.PredictionEpochLoop property) (pytorch_lightning.loops.epoch.TrainingEpochLoop property) (pytorch_lightning.loops.FitLoop property) (pytorch_lightning.loops.optimization.ManualOptimization property) (pytorch_lightning.loops.optimization.OptimizerLoop property) double() (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin method) DoublePrecisionPlugin (class in pytorch_lightning.plugins.precision) dst_type (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin.type parameter) dtype (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin.to parameter) (pytorch_lightning.utilities.apply_func.apply_to_collection parameter), [1] (pytorch_lightning.utilities.apply_func.apply_to_collections parameter), [1] DummyExperiment (class in pytorch_lightning.loggers.base) DummyLogger (class in pytorch_lightning.loggers.base) duration (pytorch_lightning.callbacks.Timer parameter), [1], [2]

E

early_stop_threshold (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) early_stopping_callback (pytorch_lightning.trainer.trainer.Trainer property) early_stopping_callbacks (pytorch_lightning.trainer.trainer.Trainer property) EarlyStopping (class in pytorch_lightning.callbacks) emit_nvtx (pytorch_lightning.profilers.PyTorchProfiler parameter), [1] enable() (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) enable_checkpointing (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] enable_graph (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) enable_model_summary (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] enable_progress_bar (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] enable_validation (pytorch_lightning.trainer.trainer.Trainer property) end_time() (pytorch_lightning.callbacks.Timer method) env_parse (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] env_prefix (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] epoch (pytorch_lightning.core.LightningModule.optimizer_step parameter) (pytorch_lightning.core.LightningModule.optimizer_zero_grad parameter) (pytorch_lightning.core.module.LightningModule.optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_zero_grad parameter) estimated_stepping_batches (pytorch_lightning.trainer.trainer.Trainer property) EvaluationEpochLoop (class in pytorch_lightning.loops.epoch) EvaluationLoop (class in pytorch_lightning.loops.dataloader)

every_n_epochs (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] every_n_train_steps (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] example_input_array (pytorch_lightning.core.LightningModule property) example_inputs (pytorch_lightning.core.LightningModule.to_torchscript parameter) (pytorch_lightning.core.module.LightningModule.to_torchscript parameter) experiment (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.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger property) (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger property) experiment_id (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger property) experiment_key (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] experiment_name (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] ExperimentWriter (class in pytorch_lightning.loggers.csv_logs) export_to_chrome (pytorch_lightning.profilers.PyTorchProfiler parameter), [1] extended (pytorch_lightning.profilers.SimpleProfiler parameter), [1]

F

fast_dev_run (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] file_exists() (pytorch_lightning.callbacks.ModelCheckpoint method) file_path (pytorch_lightning.core.LightningModule.to_onnx parameter) (pytorch_lightning.core.LightningModule.to_torchscript parameter) (pytorch_lightning.core.module.LightningModule.to_onnx parameter) (pytorch_lightning.core.module.LightningModule.to_torchscript parameter) filename (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] (pytorch_lightning.profilers.AdvancedProfiler parameter), [1] (pytorch_lightning.profilers.PyTorchProfiler parameter), [1] (pytorch_lightning.profilers.SimpleProfiler parameter), [1] filepath (pytorch_lightning.lite.LightningLite.load parameter), [1] (pytorch_lightning.lite.LightningLite.save parameter), [1] (pytorch_lightning.strategies.DeepSpeedStrategy.save_checkpoint parameter) (pytorch_lightning.strategies.Strategy.remove_checkpoint parameter) (pytorch_lightning.strategies.Strategy.save_checkpoint parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.remove_checkpoint parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.save_checkpoint parameter) (pytorch_lightning.trainer.trainer.Trainer.save_checkpoint parameter) (pytorch_lightning.utilities.cloud_io.atomic_save parameter), [1] filter_on_optimizer() (pytorch_lightning.callbacks.BaseFinetuning static method) filter_parameters_to_prune() (pytorch_lightning.callbacks.ModelPruning method) filter_params() (pytorch_lightning.callbacks.BaseFinetuning static method) finalize() (pytorch_lightning.loggers.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.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method)

finetune_function() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.BaseFinetuning method) fit() (pytorch_lightning.trainer.trainer.Trainer method) FitLoop (class in pytorch_lightning.loops) flatten (pytorch_lightning.strategies.BaguaStrategy parameter), [1] flatten_modules() (pytorch_lightning.callbacks.BaseFinetuning static method) flatten_parameters (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1] float() (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin method) flush_logs_every_n_steps (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger parameter), [1] format_checkpoint_name() (pytorch_lightning.callbacks.ModelCheckpoint method) forward() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.utilities.distributed.AllGatherGrad static method) forward_context() (pytorch_lightning.plugins.precision.DoublePrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) fp32_file_path (pytorch_lightning.plugins.precision.HPUPrecisionPlugin parameter), [1], [2] fp32_reduce_scatter (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1] frame (pytorch_lightning.core.mixins.HyperparametersMixin.save_hyperparameters parameter) (pytorch_lightning.core.module.LightningModule.save_hyperparameters parameter) (pytorch_lightning.utilities.parsing.collect_init_args parameter), [1] freeze() (pytorch_lightning.callbacks.BaseFinetuning static method) (pytorch_lightning.core.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.LightningDataModule class method) from_datasets() (pytorch_lightning.core.LightningDataModule class method) FullyShardedNativeMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) FullyShardedNativeNativeMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) function (pytorch_lightning.utilities.apply_func.apply_to_collection parameter), [1] (pytorch_lightning.utilities.apply_func.apply_to_collections parameter), [1]

G

garbage_collection_cuda() (in module pytorch_lightning.utilities.memory) gather_all_tensors() (in module pytorch_lightning.utilities.distributed) get_deprecated_arg_names() (pytorch_lightning.trainer.trainer.Trainer class method) get_device_name() (pytorch_lightning.accelerators.HPUAccelerator static method) get_device_stats() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.CPUAccelerator method) (pytorch_lightning.accelerators.CUDAAccelerator method) (pytorch_lightning.accelerators.HPUAccelerator method) (pytorch_lightning.accelerators.IPUAccelerator method) (pytorch_lightning.accelerators.TPUAccelerator method) get_gpu_memory_map() (in module pytorch_lightning.utilities.memory) get_init_arguments_and_types() (in module pytorch_lightning.utilities.argparse) (pytorch_lightning.core.LightningDataModule class method) get_metrics() (pytorch_lightning.callbacks.ProgressBarBase method) get_model_size_mb() (in module pytorch_lightning.utilities.memory) get_parallel_devices() (pytorch_lightning.accelerators.Accelerator static method) (pytorch_lightning.accelerators.CPUAccelerator static method) (pytorch_lightning.accelerators.CUDAAccelerator static method) (pytorch_lightning.accelerators.HPUAccelerator static method) (pytorch_lightning.accelerators.IPUAccelerator static method) (pytorch_lightning.accelerators.TPUAccelerator static method) global_rank (pytorch_lightning.core.LightningModule property) (pytorch_lightning.lite.LightningLite property) (pytorch_lightning.utilities.distributed.init_dist_connection parameter), [1] global_rank() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) (pytorch_lightning.plugins.environments.XLAEnvironment method) global_step (pytorch_lightning.core.LightningModule property) (pytorch_lightning.trainer.trainer.Trainer property) gpus (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1]

grad_norm_dict (pytorch_lightning.core.LightningModule.log_grad_norm parameter) gradient_clip_algorithm (pytorch_lightning.core.LightningModule.clip_gradients parameter) (pytorch_lightning.core.LightningModule.configure_gradient_clipping parameter) (pytorch_lightning.core.module.LightningModule.configure_gradient_clipping parameter) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] gradient_clip_val (pytorch_lightning.core.LightningModule.clip_gradients parameter) (pytorch_lightning.core.LightningModule.configure_gradient_clipping parameter) (pytorch_lightning.core.module.LightningModule.configure_gradient_clipping parameter) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] GradientAccumulationScheduler (class in pytorch_lightning.callbacks) group (pytorch_lightning.core.LightningModule.all_gather parameter) (pytorch_lightning.core.module.LightningModule.all_gather parameter) (pytorch_lightning.lite.LightningLite.all_gather parameter), [1] (pytorch_lightning.strategies.BaguaStrategy.reduce parameter) (pytorch_lightning.strategies.DataParallelStrategy.reduce parameter) (pytorch_lightning.strategies.DDPSpawnStrategy.reduce parameter) (pytorch_lightning.strategies.DDPStrategy.reduce parameter) (pytorch_lightning.strategies.HivemindStrategy.all_gather parameter) (pytorch_lightning.strategies.HivemindStrategy.reduce parameter) (pytorch_lightning.strategies.HorovodStrategy.reduce parameter) (pytorch_lightning.strategies.IPUStrategy.reduce parameter) (pytorch_lightning.strategies.Strategy.all_gather parameter) (pytorch_lightning.strategies.Strategy.reduce parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.all_gather parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.reduce parameter) (pytorch_lightning.utilities.distributed.all_gather_ddp_if_available parameter), [1] (pytorch_lightning.utilities.distributed.gather_all_tensors parameter), [1] (pytorch_lightning.utilities.distributed.sync_ddp parameter), [1] (pytorch_lightning.utilities.distributed.sync_ddp_if_available parameter), [1] group_by_input_shapes (pytorch_lightning.profilers.PyTorchProfiler parameter), [1]

H

half() (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin method) handles_gradient_accumulation (pytorch_lightning.strategies.DeepSpeedStrategy property) (pytorch_lightning.strategies.HorovodStrategy property) (pytorch_lightning.strategies.Strategy property) hiddens (pytorch_lightning.core.LightningModule.training_step parameter) (pytorch_lightning.core.module.LightningModule.training_step parameter) HivemindStrategy (class in pytorch_lightning.strategies) HorovodStrategy (class in pytorch_lightning.strategies) host_maddrs (pytorch_lightning.strategies.HivemindStrategy parameter), [1] hparams (pytorch_lightning.core.mixins.HyperparametersMixin property)

hparams_file (pytorch_lightning.core.LightningDataModule.load_from_checkpoint parameter) (pytorch_lightning.core.module.LightningModule.load_from_checkpoint parameter) (pytorch_lightning.core.saving.ModelIO.load_from_checkpoint parameter) hparams_initial (pytorch_lightning.core.mixins.HyperparametersMixin property) HPUAccelerator (class in pytorch_lightning.accelerators) HPUCheckpointIO (class in pytorch_lightning.plugins.io) HPUParallelStrategy (class in pytorch_lightning.strategies) HPUPrecisionPlugin (class in pytorch_lightning.plugins.precision) HyperparametersMixin (class in pytorch_lightning.core.mixins) hysteresis (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1]

I

id (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] ignore (pytorch_lightning.core.mixins.HyperparametersMixin.save_hyperparameters parameter) (pytorch_lightning.core.module.LightningModule.save_hyperparameters parameter) in_dict (pytorch_lightning.utilities.memory.recursive_detach parameter), [1] include_none (pytorch_lightning.utilities.apply_func.apply_to_collection parameter), [1] inference_opts (pytorch_lightning.strategies.IPUStrategy parameter), [1] init_dist_connection() (in module pytorch_lightning.utilities.distributed) init_predict_tqdm() (pytorch_lightning.callbacks.TQDMProgressBar method) init_sanity_tqdm() (pytorch_lightning.callbacks.TQDMProgressBar method) init_test_tqdm() (pytorch_lightning.callbacks.TQDMProgressBar method) init_train_tqdm() (pytorch_lightning.callbacks.TQDMProgressBar method) init_val (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) init_validation_tqdm() (pytorch_lightning.callbacks.TQDMProgressBar method) initial_denom_lr (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) initial_peers (pytorch_lightning.strategies.HivemindStrategy parameter), [1] initial_scale_power (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] input_array (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) input_compatible (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1], [2]

input_sample (pytorch_lightning.core.LightningModule.to_onnx parameter) (pytorch_lightning.core.module.LightningModule.to_onnx parameter) inside (pytorch_lightning.utilities.parsing.collect_init_args parameter), [1] interval (pytorch_lightning.callbacks.Timer parameter), [1], [2] IPUAccelerator (class in pytorch_lightning.accelerators) IPUPrecisionPlugin (class in pytorch_lightning.plugins.precision) ipus (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] IPUStrategy (class in pytorch_lightning.strategies) is_available() (pytorch_lightning.accelerators.Accelerator static method) (pytorch_lightning.accelerators.CPUAccelerator static method) (pytorch_lightning.accelerators.CUDAAccelerator static method) (pytorch_lightning.accelerators.HPUAccelerator static method) (pytorch_lightning.accelerators.IPUAccelerator static method) (pytorch_lightning.accelerators.TPUAccelerator static method) is_global_zero (pytorch_lightning.lite.LightningLite property) (pytorch_lightning.strategies.HivemindStrategy property) (pytorch_lightning.strategies.IPUStrategy property) (pytorch_lightning.strategies.ParallelStrategy property) (pytorch_lightning.strategies.SingleDeviceStrategy property) (pytorch_lightning.strategies.Strategy property) is_last_batch (pytorch_lightning.trainer.trainer.Trainer property) is_picklable() (in module pytorch_lightning.utilities.parsing) isolate_rng() (in module pytorch_lightning.utilities.seed)

K

KubeflowEnvironment (class in pytorch_lightning.plugins.environments) kwargs (pytorch_lightning.core.optimizer.LightningOptimizer.step 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.wandb.WandbLogger.log_hyperparams parameter) (pytorch_lightning.loggers.WandbLogger.log_hyperparams parameter) (pytorch_lightning.loops.batch.TrainingBatchLoop.advance parameter) (pytorch_lightning.loops.batch.TrainingBatchLoop.on_run_start parameter) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.EvaluationEpochLoop.on_run_start parameter) (pytorch_lightning.loops.optimization.ManualOptimization.advance parameter) (pytorch_lightning.utilities.distributed.init_dist_connection parameter), [1]

L

lambda_func (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] LambdaCallback (class in pytorch_lightning.callbacks) LayerSync (class in pytorch_lightning.plugins) LearningRateMonitor (class in pytorch_lightning.callbacks) leave (pytorch_lightning.callbacks.RichProgressBar parameter), [1], [2] lightning_getattr() (in module pytorch_lightning.utilities.parsing) lightning_hasattr() (in module pytorch_lightning.utilities.parsing) lightning_module (pytorch_lightning.strategies.BaguaStrategy property) (pytorch_lightning.strategies.DDPShardedStrategy property) (pytorch_lightning.strategies.DDPSpawnShardedStrategy property) (pytorch_lightning.strategies.DeepSpeedStrategy property) (pytorch_lightning.strategies.ParallelStrategy property) (pytorch_lightning.strategies.Strategy property) lightning_module_state_dict() (pytorch_lightning.strategies.Strategy method) lightning_restore_optimizer (pytorch_lightning.strategies.DeepSpeedStrategy property) (pytorch_lightning.strategies.Strategy property) lightning_setattr() (in module pytorch_lightning.utilities.parsing) LightningArgumentParser (class in pytorch_lightning.utilities.cli) LightningCLI (class in pytorch_lightning.utilities.cli) LightningDataModule (class in pytorch_lightning.core) LightningDeprecationWarning, [1] LightningEnvironment (class in pytorch_lightning.plugins.environments) LightningLite (class in pytorch_lightning.lite) LightningLoggerBase (class in pytorch_lightning.loggers.base) LightningModule (class in pytorch_lightning.core) LightningOptimizer (class in pytorch_lightning.core.optimizer) limit_predict_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] limit_test_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] limit_train_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] limit_val_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] line_count_restriction (pytorch_lightning.profilers.AdvancedProfiler parameter), [1] load() (in module pytorch_lightning.utilities.cloud_io) (pytorch_lightning.lite.LightningLite method) load_checkpoint() (pytorch_lightning.plugins.io.CheckpointIO method) (pytorch_lightning.plugins.io.TorchCheckpointIO method) load_from_checkpoint() (pytorch_lightning.core.LightningDataModule class method) (pytorch_lightning.core.saving.ModelIO class method) load_full_weights (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] load_state_dict() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.core.LightningDataModule method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) local_rank (pytorch_lightning.core.LightningModule property) (pytorch_lightning.lite.LightningLite property) local_rank() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) (pytorch_lightning.plugins.environments.XLAEnvironment method) log() (pytorch_lightning.core.LightningModule method) log_dict() (pytorch_lightning.core.LightningModule method) log_dir (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.csv_logs.ExperimentWriter parameter), [1] (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger property) log_every_n_steps (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] log_grad_norm() (pytorch_lightning.core.LightningModule method) log_graph (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1]

log_graph() (pytorch_lightning.loggers.comet.CometLogger method) (pytorch_lightning.loggers.CometLogger method) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger method) (pytorch_lightning.loggers.TensorBoardLogger method) log_hparams() (pytorch_lightning.loggers.csv_logs.ExperimentWriter method) log_hyperparams() (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.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) log_image() (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) log_metrics() (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.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) log_model (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] log_model_checkpoints (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] log_momentum (pytorch_lightning.callbacks.LearningRateMonitor parameter), [1], [2] log_rank_zero_only (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] log_table() (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) log_text() (pytorch_lightning.loggers.wandb.WandbLogger method) (pytorch_lightning.loggers.WandbLogger method) logger (pytorch_lightning.core.LightningModule property) (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.mixins.HyperparametersMixin.save_hyperparameters parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.save_hyperparameters parameter) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] LoggerCollection (class in pytorch_lightning.loggers.base) loggers (pytorch_lightning.core.LightningModule property) logging_batch_size_per_gpu (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] logging_interval (pytorch_lightning.callbacks.LearningRateMonitor parameter), [1], [2] logging_level (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] Loop (class in pytorch_lightning.loops.base) loss (pytorch_lightning.core.hooks.ModelHooks.on_before_backward parameter) (pytorch_lightning.core.LightningModule.backward parameter) (pytorch_lightning.core.LightningModule.manual_backward parameter) (pytorch_lightning.core.module.LightningModule.backward parameter) (pytorch_lightning.core.module.LightningModule.manual_backward parameter) (pytorch_lightning.core.module.LightningModule.on_before_backward parameter) loss_scale (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] loss_scale_window (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] lr (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) lr_find() (pytorch_lightning.tuner.tuning.Tuner method) lr_find_kwargs (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.tune parameter) lr_scheduler_step() (pytorch_lightning.core.LightningModule method) lr_schedulers() (pytorch_lightning.core.LightningModule method) LSFEnvironment (class in pytorch_lightning.plugins.environments)

M

main_address (pytorch_lightning.plugins.environments.ClusterEnvironment property) (pytorch_lightning.plugins.environments.KubeflowEnvironment property) (pytorch_lightning.plugins.environments.LightningEnvironment property) (pytorch_lightning.plugins.environments.LSFEnvironment property) (pytorch_lightning.plugins.environments.SLURMEnvironment property) (pytorch_lightning.plugins.environments.TorchElasticEnvironment property) (pytorch_lightning.plugins.environments.XLAEnvironment property) main_params() (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) main_port (pytorch_lightning.plugins.environments.ClusterEnvironment property) (pytorch_lightning.plugins.environments.KubeflowEnvironment property) (pytorch_lightning.plugins.environments.LightningEnvironment property) (pytorch_lightning.plugins.environments.LSFEnvironment property) (pytorch_lightning.plugins.environments.SLURMEnvironment property) (pytorch_lightning.plugins.environments.TorchElasticEnvironment property) (pytorch_lightning.plugins.environments.XLAEnvironment property) make_pruning_permanent (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] make_pruning_permanent() (pytorch_lightning.callbacks.ModelPruning method) make_trainable() (pytorch_lightning.callbacks.BaseFinetuning static method) manual_backward() (pytorch_lightning.core.LightningModule method) ManualOptimization (class in pytorch_lightning.loops.optimization) map_location (pytorch_lightning.core.module.LightningModule.load_from_checkpoint parameter) (pytorch_lightning.core.saving.ModelIO.load_from_checkpoint parameter) (pytorch_lightning.plugins.io.CheckpointIO.load_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.load_checkpoint parameter) (pytorch_lightning.utilities.cloud_io.load parameter), [1] matchmaking_time (pytorch_lightning.strategies.HivemindStrategy parameter), [1] max_batches (pytorch_lightning.loops.dataloader.PredictionLoop property) max_depth (pytorch_lightning.callbacks.ModelSummary parameter), [1], [2] (pytorch_lightning.callbacks.RichModelSummary parameter), [1], [2] max_epochs (pytorch_lightning.loops.FitLoop parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] max_in_cpu (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] max_lr (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) max_steps (pytorch_lightning.loops.epoch.TrainingEpochLoop parameter), [1] (pytorch_lightning.loops.FitLoop property) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] max_time (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] max_trials (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) method (pytorch_lightning.core.LightningModule.to_torchscript parameter) (pytorch_lightning.core.module.LightningModule.to_torchscript parameter) metric (pytorch_lightning.core.LightningModule.lr_scheduler_step parameter) metric_attribute (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log parameter) metrics (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.wandb.WandbLogger.log_metrics parameter) (pytorch_lightning.loggers.WandbLogger.log_metrics parameter) min_delta (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] min_epochs (pytorch_lightning.loops.FitLoop parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] min_loss_scale (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] min_lr (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) min_num_params (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1] min_steps (pytorch_lightning.loops.epoch.TrainingEpochLoop parameter), [1] (pytorch_lightning.loops.FitLoop property) (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] MixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) MLFlowLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.mlflow) mode (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) model (pytorch_lightning.lite.LightningLite.backward parameter), [1] (pytorch_lightning.lite.LightningLite.setup parameter), [1] (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.plugins.NativeSyncBatchNorm.apply parameter) (pytorch_lightning.plugins.NativeSyncBatchNorm.revert parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.pre_backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.post_backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.pre_backward parameter) (pytorch_lightning.strategies.DDPStrategy.optimizer_step parameter) (pytorch_lightning.strategies.Strategy property) (pytorch_lightning.strategies.Strategy.optimizer_step 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 property) (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.reset_predict_dataloader parameter) (pytorch_lightning.trainer.trainer.Trainer.reset_test_dataloader parameter) (pytorch_lightning.trainer.trainer.Trainer.reset_train_dataloader parameter) (pytorch_lightning.trainer.trainer.Trainer.reset_train_val_dataloaders parameter) (pytorch_lightning.trainer.trainer.Trainer.reset_val_dataloader 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), [1] (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) (pytorch_lightning.utilities.distributed.register_ddp_comm_hook parameter), [1]

model_class (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] model_sharded_context() (pytorch_lightning.strategies.DDPFullyShardedStrategy method) (pytorch_lightning.strategies.DeepSpeedStrategy method) (pytorch_lightning.strategies.Strategy method) model_to_device() (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPFullyShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.HivemindStrategy method) (pytorch_lightning.strategies.HorovodStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.SingleDeviceStrategy method) (pytorch_lightning.strategies.SingleHPUStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) ModelCheckpoint (class in pytorch_lightning.callbacks) ModelHooks (class in pytorch_lightning.core.hooks) ModelIO (class in pytorch_lightning.core.saving) ModelPruning (class in pytorch_lightning.callbacks) ModelSummary (class in pytorch_lightning.callbacks) module 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.wandb pytorch_lightning.utilities.apply_func pytorch_lightning.utilities.argparse pytorch_lightning.utilities.cli pytorch_lightning.utilities.cloud_io pytorch_lightning.utilities.deepspeed pytorch_lightning.utilities.distributed pytorch_lightning.utilities.finite_checks pytorch_lightning.utilities.memory pytorch_lightning.utilities.model_summary pytorch_lightning.utilities.optimizer pytorch_lightning.utilities.parsing pytorch_lightning.utilities.rank_zero pytorch_lightning.utilities.seed pytorch_lightning.utilities.warnings 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], [2] monitor (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] move_data_to_device() (in module pytorch_lightning.utilities.apply_func) move_grads_to_cpu (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1] move_metrics_to_cpu (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] move_to_device (pytorch_lightning.lite.LightningLite.setup parameter), [1] (pytorch_lightning.lite.LightningLite.setup_dataloaders parameter), [1] multiple_trainloader_mode (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1]

N

name (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.loggers.comet.CometLogger property) (pytorch_lightning.loggers.CometLogger property) (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger property) (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.neptune.NeptuneLogger property) (pytorch_lightning.loggers.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger property) (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger property) (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger property) (pytorch_lightning.strategies.BaguaStrategy.barrier parameter) (pytorch_lightning.strategies.DataParallelStrategy.barrier parameter) (pytorch_lightning.strategies.DDPSpawnStrategy.barrier parameter) (pytorch_lightning.strategies.DDPStrategy.barrier parameter) (pytorch_lightning.strategies.HivemindStrategy.barrier parameter) (pytorch_lightning.strategies.HorovodStrategy.barrier parameter) (pytorch_lightning.strategies.IPUStrategy.barrier parameter) (pytorch_lightning.strategies.SingleDeviceStrategy.barrier parameter) (pytorch_lightning.strategies.Strategy.barrier parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.barrier parameter)

NativeMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) NativeSyncBatchNorm (class in pytorch_lightning.plugins) NeptuneLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.neptune) node_rank (pytorch_lightning.lite.LightningLite property) node_rank() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) (pytorch_lightning.plugins.environments.XLAEnvironment method) num_dataloaders (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop property) (pytorch_lightning.loops.dataloader.EvaluationLoop property) (pytorch_lightning.loops.dataloader.PredictionLoop property) (pytorch_lightning.loops.epoch.PredictionEpochLoop.advance parameter) (pytorch_lightning.loops.epoch.PredictionEpochLoop.on_run_start parameter) num_devices (pytorch_lightning.trainer.trainer.Trainer property) num_nodes (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] num_processes (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] num_sanity_val_steps (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] num_training (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) num_workers (pytorch_lightning.core.LightningDataModule.from_datasets parameter) nvme_path (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1]

O

obj (pytorch_lightning.lite.LightningLite.to_device parameter), [1] (pytorch_lightning.strategies.BaguaStrategy.broadcast parameter) (pytorch_lightning.strategies.DataParallelStrategy.broadcast parameter) (pytorch_lightning.strategies.DDPSpawnStrategy.broadcast parameter) (pytorch_lightning.strategies.DDPStrategy.broadcast parameter) (pytorch_lightning.strategies.HivemindStrategy.broadcast parameter) (pytorch_lightning.strategies.HorovodStrategy.broadcast parameter) (pytorch_lightning.strategies.HPUParallelStrategy.broadcast parameter) (pytorch_lightning.strategies.IPUStrategy.broadcast parameter) (pytorch_lightning.strategies.SingleDeviceStrategy.broadcast parameter) (pytorch_lightning.strategies.Strategy.broadcast parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.broadcast parameter) observer_enabled_stages (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1], [2] observer_type (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1], [2] offline (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] offload_optimizer (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] (pytorch_lightning.strategies.HivemindStrategy parameter), [1] offload_optimizer_device (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] offload_parameters (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] offload_params_device (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] on_advance_end() (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) on_advance_start() (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.FitLoop method) on_after_backward() (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.Callback method) on_batch_start() (pytorch_lightning.callbacks.Callback method) on_before_accelerator_backend_setup() (pytorch_lightning.callbacks.Callback method) on_before_backward() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_before_batch_transfer() (pytorch_lightning.core.hooks.DataHooks method) on_before_optimizer_step() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_before_zero_grad() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_configure_sharded_model() (pytorch_lightning.callbacks.Callback method) on_epoch (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) on_epoch_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_epoch_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_exception() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) on_fit_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.core.hooks.ModelHooks method) on_fit_start() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ModelSummary method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.core.hooks.ModelHooks method) on_gpu (pytorch_lightning.core.LightningModule property) on_hpc_load() (pytorch_lightning.core.saving.ModelIO method) on_hpc_save() (pytorch_lightning.core.saving.ModelIO method) on_init_end() (pytorch_lightning.callbacks.Callback method) on_init_start() (pytorch_lightning.callbacks.Callback method) on_load_checkpoint() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.CheckpointHooks method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) on_predict_batch_end() (pytorch_lightning.callbacks.BasePredictionWriter method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_predict_batch_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_predict_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) on_predict_epoch_end() (pytorch_lightning.callbacks.BasePredictionWriter method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_predict_epoch_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_predict_model_eval() (pytorch_lightning.core.hooks.ModelHooks method) on_predict_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) on_pretrain_routine_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_pretrain_routine_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_run_end() (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.ManualOptimization method) (pytorch_lightning.loops.optimization.OptimizerLoop method) on_run_start() (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.ManualOptimization method) (pytorch_lightning.loops.optimization.OptimizerLoop method) on_sanity_check_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) on_sanity_check_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) on_save_checkpoint() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.core.hooks.CheckpointHooks method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) on_skip() (pytorch_lightning.loops.dataloader.EvaluationLoop method) on_step (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) on_test_batch_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_test_batch_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_test_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) on_test_epoch_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_test_epoch_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.core.hooks.ModelHooks method) on_test_model_eval() (pytorch_lightning.core.hooks.ModelHooks method) on_test_model_train() (pytorch_lightning.core.hooks.ModelHooks method) on_test_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method)

on_tpu (pytorch_lightning.core.LightningModule.optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_step parameter) on_train_batch_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.DeviceStatsMonitor method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_train_batch_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.DeviceStatsMonitor method) (pytorch_lightning.callbacks.LearningRateMonitor method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.HivemindStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) on_train_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) on_train_epoch_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_train_epoch_start() (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.GradientAccumulationScheduler method) (pytorch_lightning.callbacks.LearningRateMonitor method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_train_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.LearningRateMonitor method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) on_validation_batch_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_batch_start() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) on_validation_epoch_end() (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) on_validation_epoch_start() (pytorch_lightning.callbacks.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.Callback method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.hooks.ModelHooks method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) opt_idx (pytorch_lightning.strategies.DDPStrategy.optimizer_step parameter) (pytorch_lightning.strategies.Strategy.optimizer_step parameter) opt_level (pytorch_lightning.plugins.precision.HPUPrecisionPlugin parameter), [1], [2] optimizer (pytorch_lightning.callbacks.BaseFinetuning.filter_on_optimizer parameter) (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) (pytorch_lightning.core.hooks.ModelHooks.on_before_optimizer_step parameter) (pytorch_lightning.core.hooks.ModelHooks.on_before_zero_grad parameter) (pytorch_lightning.core.LightningModule.backward parameter) (pytorch_lightning.core.LightningModule.clip_gradients parameter) (pytorch_lightning.core.LightningModule.configure_gradient_clipping parameter) (pytorch_lightning.core.LightningModule.optimizer_step parameter) (pytorch_lightning.core.LightningModule.optimizer_zero_grad parameter) (pytorch_lightning.core.LightningModule.toggle_optimizer parameter) (pytorch_lightning.core.module.LightningModule.backward parameter) (pytorch_lightning.core.module.LightningModule.configure_gradient_clipping parameter) (pytorch_lightning.core.module.LightningModule.on_before_optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.on_before_zero_grad parameter) (pytorch_lightning.core.module.LightningModule.optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_zero_grad parameter) (pytorch_lightning.core.module.LightningModule.toggle_optimizer parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin.backward parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.backward parameter) (pytorch_lightning.strategies.DDPStrategy.optimizer_step parameter) (pytorch_lightning.strategies.Strategy.optimizer_step parameter) optimizer_buffer_count (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] optimizer_closure (pytorch_lightning.core.LightningModule.optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_step parameter) optimizer_idx (pytorch_lightning.core.hooks.ModelHooks.on_before_optimizer_step parameter) (pytorch_lightning.core.LightningModule.backward parameter) (pytorch_lightning.core.LightningModule.configure_gradient_clipping parameter) (pytorch_lightning.core.LightningModule.lr_scheduler_step parameter) (pytorch_lightning.core.LightningModule.optimizer_step parameter) (pytorch_lightning.core.LightningModule.optimizer_zero_grad parameter) (pytorch_lightning.core.LightningModule.toggle_optimizer parameter) (pytorch_lightning.core.LightningModule.training_step parameter) (pytorch_lightning.core.LightningModule.untoggle_optimizer parameter) (pytorch_lightning.core.module.LightningModule.backward parameter) (pytorch_lightning.core.module.LightningModule.configure_gradient_clipping parameter) (pytorch_lightning.core.module.LightningModule.on_before_optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_zero_grad parameter) (pytorch_lightning.core.module.LightningModule.toggle_optimizer parameter) (pytorch_lightning.core.module.LightningModule.training_step parameter) (pytorch_lightning.core.module.LightningModule.untoggle_optimizer parameter) optimizer_state() (pytorch_lightning.strategies.DDPShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnShardedStrategy method) (pytorch_lightning.strategies.Strategy method) optimizer_step() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin method) (pytorch_lightning.plugins.precision.IPUPrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.precision.TPUPrecisionPlugin method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.Strategy method) optimizer_to_device() (in module pytorch_lightning.utilities.optimizer) optimizer_zero_grad() (pytorch_lightning.core.LightningModule method) OptimizerLoop (class in pytorch_lightning.loops.optimization) optimizers() (pytorch_lightning.core.LightningModule method) optimizers_to_device() (in module pytorch_lightning.utilities.optimizer) output_file (pytorch_lightning.utilities.deepspeed.convert_zero_checkpoint_to_fp32_state_dict parameter), [1] output_result_cls (pytorch_lightning.loops.optimization.ManualOptimization attribute) (pytorch_lightning.loops.optimization.OptimizerLoop attribute) outputs (pytorch_lightning.core.hooks.ModelHooks.on_predict_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_test_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_train_batch_end parameter) (pytorch_lightning.core.hooks.ModelHooks.on_validation_batch_end parameter) (pytorch_lightning.core.LightningModule.test_epoch_end parameter) (pytorch_lightning.core.LightningModule.training_epoch_end parameter) (pytorch_lightning.core.LightningModule.validation_epoch_end parameter) (pytorch_lightning.core.module.LightningModule.on_predict_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_test_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_train_batch_end parameter) (pytorch_lightning.core.module.LightningModule.on_validation_batch_end parameter) (pytorch_lightning.core.module.LightningModule.test_epoch_end parameter) (pytorch_lightning.core.module.LightningModule.training_epoch_end parameter) (pytorch_lightning.core.module.LightningModule.validation_epoch_end parameter) overfit_batches (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] overlap_comm (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] overlap_events (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1]

P

ParallelStrategy (class in pytorch_lightning.strategies) parameter_names (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] parameters_to_prune (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] params (pytorch_lightning.callbacks.BaseFinetuning.filter_on_optimizer 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.wandb.WandbLogger.log_hyperparams parameter) (pytorch_lightning.loggers.WandbLogger.log_hyperparams parameter) params_buffer_count (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] params_buffer_size (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] parent_parser (pytorch_lightning.utilities.argparse.add_argparse_args parameter), [1] parse_argparser() (in module pytorch_lightning.utilities.argparse) parse_class_init_keys() (in module pytorch_lightning.utilities.parsing) parse_devices() (pytorch_lightning.accelerators.Accelerator static method) (pytorch_lightning.accelerators.CPUAccelerator static method) (pytorch_lightning.accelerators.CUDAAccelerator static method) (pytorch_lightning.accelerators.HPUAccelerator static method) (pytorch_lightning.accelerators.IPUAccelerator static method) (pytorch_lightning.accelerators.TPUAccelerator static method) parse_env_variables() (in module pytorch_lightning.utilities.argparse) ParseArgparserDataType (class in pytorch_lightning.utilities.argparse) parser_kwargs (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] partition_activations (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] PassThroughProfiler (class in pytorch_lightning.profilers) path (pytorch_lightning.plugins.io.CheckpointIO.load_checkpoint parameter) (pytorch_lightning.plugins.io.CheckpointIO.remove_checkpoint parameter) (pytorch_lightning.plugins.io.CheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.HPUCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.load_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.remove_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.XLACheckpointIO.save_checkpoint parameter) path_args (pytorch_lightning.utilities.parsing.collect_init_args parameter), [1] path_or_url (pytorch_lightning.utilities.cloud_io.load parameter), [1] patience (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] pin_memory (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] pl_module (pytorch_lightning.callbacks.Callback.on_load_checkpoint parameter), [1] (pytorch_lightning.callbacks.Callback.on_save_checkpoint parameter), [1] (pytorch_lightning.callbacks.ModelPruning.on_save_checkpoint parameter) pl_worker_init_function() (in module pytorch_lightning.utilities.seed) plugins (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] port (pytorch_lightning.profilers.XLAProfiler parameter), [1] PossibleUserWarning post_backward() (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.strategies.HorovodStrategy method) (pytorch_lightning.strategies.Strategy method) pre_backward() (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.strategies.DDPShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.Strategy method) precision (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.plugins.precision.DeepSpeedPrecisionPlugin parameter), [1], [2] (pytorch_lightning.plugins.precision.HPUPrecisionPlugin parameter), [1], [2] (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin parameter), [1], [2] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] PrecisionPlugin (class in pytorch_lightning.plugins.precision) predict() (pytorch_lightning.trainer.trainer.Trainer method) predict_batch_idx (pytorch_lightning.callbacks.ProgressBarBase property) predict_dataloader() (pytorch_lightning.core.hooks.DataHooks method) predict_dataset (pytorch_lightning.core.LightningDataModule.from_datasets parameter) predict_step() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPFullyShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.DeepSpeedStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) predict_step_context() (pytorch_lightning.plugins.precision.PrecisionPlugin method) prediction_writer_callbacks (pytorch_lightning.trainer.trainer.Trainer property) PredictionEpochLoop (class in pytorch_lightning.loops.epoch) PredictionLoop (class in pytorch_lightning.loops.dataloader)

prefix (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger parameter), [1] (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] prepare_data() (pytorch_lightning.core.hooks.DataHooks method) prepare_data_per_node (pytorch_lightning.core.hooks.DataHooks attribute) print() (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.TQDMProgressBar method) (pytorch_lightning.core.LightningModule method) (pytorch_lightning.lite.LightningLite method) print_nan_gradients() (in module pytorch_lightning.utilities.finite_checks) process_dataloader() (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) process_position (pytorch_lightning.callbacks.TQDMProgressBar parameter), [1], [2] profile() (pytorch_lightning.profilers.Profiler method) profile_iterable() (pytorch_lightning.profilers.Profiler method) Profiler (class in pytorch_lightning.profilers) profiler (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] profiler_kwargs (pytorch_lightning.profilers.PyTorchProfiler parameter), [1] prog_bar (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) progress_bar_callback (pytorch_lightning.trainer.trainer.Trainer property) ProgressBarBase (class in pytorch_lightning.callbacks) project (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger parameter), [1] project_name (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] prune_on_train_epoch_end (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] pruning_dim (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] pruning_fn (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] pruning_norm (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] 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.wandb module pytorch_lightning.utilities.apply_func module pytorch_lightning.utilities.argparse module pytorch_lightning.utilities.cli module pytorch_lightning.utilities.cloud_io module pytorch_lightning.utilities.deepspeed module pytorch_lightning.utilities.distributed module pytorch_lightning.utilities.finite_checks module pytorch_lightning.utilities.memory module pytorch_lightning.utilities.model_summary module pytorch_lightning.utilities.optimizer module pytorch_lightning.utilities.parsing module pytorch_lightning.utilities.rank_zero module pytorch_lightning.utilities.seed module pytorch_lightning.utilities.warnings module PyTorchProfiler (class in pytorch_lightning.profilers)

Q

qconfig (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1], [2] QuantizationAwareTraining (class in pytorch_lightning.callbacks)

quantize_on_fit_end (pytorch_lightning.callbacks.QuantizationAwareTraining parameter), [1], [2] queue_depth (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1]

R

rank_zero_debug() (in module pytorch_lightning.utilities.rank_zero) rank_zero_deprecation() (in module pytorch_lightning.utilities.rank_zero) rank_zero_info() (in module pytorch_lightning.utilities.rank_zero) rank_zero_only (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) rank_zero_only() (in module pytorch_lightning.utilities.rank_zero) rank_zero_warn() (in module pytorch_lightning.utilities.rank_zero) reconciliate_processes() (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.ParallelStrategy method) record_module_names (pytorch_lightning.profilers.PyTorchProfiler parameter), [1] recursive_detach() (in module pytorch_lightning.utilities.memory) reduce() (pytorch_lightning.strategies.BaguaStrategy method) (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.HivemindStrategy method) (pytorch_lightning.strategies.HorovodStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.SingleDeviceStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) reduce_boolean_decision() (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.ParallelStrategy method) (pytorch_lightning.strategies.Strategy method) reduce_bucket_size (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] reduce_fx (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) reduce_op (pytorch_lightning.strategies.BaguaStrategy.reduce parameter) (pytorch_lightning.strategies.DataParallelStrategy.reduce parameter) (pytorch_lightning.strategies.DDPSpawnStrategy.reduce parameter) (pytorch_lightning.strategies.DDPStrategy.reduce parameter) (pytorch_lightning.strategies.HivemindStrategy.reduce parameter) (pytorch_lightning.strategies.HorovodStrategy.reduce parameter) (pytorch_lightning.strategies.IPUStrategy.reduce parameter) (pytorch_lightning.strategies.Strategy.reduce parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.reduce parameter) (pytorch_lightning.utilities.distributed.sync_ddp parameter), [1] (pytorch_lightning.utilities.distributed.sync_ddp_if_available parameter), [1] reduce_scatter (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] refresh_rate (pytorch_lightning.callbacks.RichProgressBar parameter), [1], [2] (pytorch_lightning.callbacks.TQDMProgressBar parameter), [1], [2] register_ddp_comm_hook() (in module pytorch_lightning.utilities.distributed) reload_dataloaders_every_n_epochs (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] remote_device (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] remove_checkpoint() (pytorch_lightning.plugins.io.CheckpointIO method) (pytorch_lightning.plugins.io.TorchCheckpointIO method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) replace_sampler (pytorch_lightning.lite.LightningLite.setup_dataloaders parameter), [1] replace_sampler_ddp (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] requires_grad (pytorch_lightning.callbacks.BaseFinetuning.filter_params parameter) resample_parameters (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] reset() (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.dataloader_loop.DataLoaderLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.dataloader.PredictionLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.PredictionEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.loops.optimization.ManualOptimization method) (pytorch_lightning.loops.optimization.OptimizerLoop method)

reset_batch_norm_and_save_state() (pytorch_lightning.callbacks.StochasticWeightAveraging method) reset_momenta() (pytorch_lightning.callbacks.StochasticWeightAveraging method) reset_predict_dataloader() (pytorch_lightning.trainer.trainer.Trainer method) reset_seed() (in module pytorch_lightning.utilities.seed) reset_test_dataloader() (pytorch_lightning.trainer.trainer.Trainer method) reset_train_dataloader() (pytorch_lightning.trainer.trainer.Trainer method) reset_train_val_dataloaders() (pytorch_lightning.trainer.trainer.Trainer method) reset_val_dataloader() (pytorch_lightning.trainer.trainer.Trainer method) reshard_after_forward (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1] resolve_tags() (in module pytorch_lightning.loggers.mlflow) rest_api_key (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger parameter), [1] restarting (pytorch_lightning.loops.FitLoop property) restore_checkpoint_after_setup (pytorch_lightning.strategies.DeepSpeedStrategy property) (pytorch_lightning.strategies.Strategy property) result (pytorch_lightning.utilities.distributed.gather_all_tensors parameter), [1] (pytorch_lightning.utilities.distributed.sync_ddp parameter), [1] (pytorch_lightning.utilities.distributed.sync_ddp_if_available parameter), [1] resume_from_checkpoint (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] return_predictions (pytorch_lightning.loops.dataloader.PredictionLoop property) (pytorch_lightning.trainer.Trainer.predict parameter) (pytorch_lightning.trainer.trainer.Trainer.predict parameter) reuse_grad_buffers (pytorch_lightning.strategies.HivemindStrategy parameter), [1] revert() (pytorch_lightning.plugins.LayerSync method) (pytorch_lightning.plugins.NativeSyncBatchNorm method) RichModelSummary (class in pytorch_lightning.callbacks) RichProgressBar (class in pytorch_lightning.callbacks) root_device (pytorch_lightning.strategies.DataParallelStrategy property) (pytorch_lightning.strategies.DDPSpawnStrategy property) (pytorch_lightning.strategies.DDPStrategy property) (pytorch_lightning.strategies.HivemindStrategy property) (pytorch_lightning.strategies.HorovodStrategy property) (pytorch_lightning.strategies.IPUStrategy property) (pytorch_lightning.strategies.ParallelStrategy property) (pytorch_lightning.strategies.SingleDeviceStrategy property) (pytorch_lightning.strategies.Strategy property) (pytorch_lightning.strategies.TPUSpawnStrategy property) root_dir (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger property) rounding (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] row_limit (pytorch_lightning.profilers.PyTorchProfiler parameter), [1] run (pytorch_lightning.loggers.neptune.NeptuneLogger parameter), [1] (pytorch_lightning.loggers.NeptuneLogger parameter), [1] (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] run() (pytorch_lightning.lite.LightningLite method) run_id (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger property) (pytorch_lightning.strategies.HivemindStrategy parameter), [1] run_name (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] running_loss (pytorch_lightning.loops.FitLoop property)

S

sanitize_parameters_to_prune() (pytorch_lightning.callbacks.ModelPruning static method) save() (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.loggers.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) save_checkpoint() (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.plugins.io.AsyncCheckpointIO method) (pytorch_lightning.plugins.io.CheckpointIO method) (pytorch_lightning.plugins.io.HPUCheckpointIO method) (pytorch_lightning.plugins.io.TorchCheckpointIO method) (pytorch_lightning.plugins.io.XLACheckpointIO method) (pytorch_lightning.strategies.DeepSpeedStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) (pytorch_lightning.trainer.trainer.Trainer method) save_config_callback (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_config_filename (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_config_multifile (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_config_overwrite (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] save_dir (pytorch_lightning.loggers.comet.CometLogger parameter), [1] (pytorch_lightning.loggers.comet.CometLogger property) (pytorch_lightning.loggers.CometLogger parameter), [1] (pytorch_lightning.loggers.CometLogger property) (pytorch_lightning.loggers.csv_logs.CSVLogger parameter), [1] (pytorch_lightning.loggers.csv_logs.CSVLogger property) (pytorch_lightning.loggers.CSVLogger parameter), [1] (pytorch_lightning.loggers.CSVLogger property) (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.mlflow.MLFlowLogger property) (pytorch_lightning.loggers.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger property) (pytorch_lightning.loggers.neptune.NeptuneLogger property) (pytorch_lightning.loggers.NeptuneLogger property) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger property) (pytorch_lightning.loggers.wandb.WandbLogger parameter), [1] (pytorch_lightning.loggers.wandb.WandbLogger property) (pytorch_lightning.loggers.WandbLogger parameter), [1] (pytorch_lightning.loggers.WandbLogger property) save_hyperparameters() (in module pytorch_lightning.utilities.parsing) (pytorch_lightning.core.mixins.HyperparametersMixin method) save_last (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] save_on_train_epoch_end (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] save_top_k (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] save_weights_only (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] SaveConfigCallback (class in pytorch_lightning.utilities.cli) scale_batch_size() (pytorch_lightning.tuner.tuning.Tuner method) scale_batch_size_kwargs (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.tune parameter) scaler (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin parameter), [1], [2] scheduler (pytorch_lightning.core.LightningModule.lr_scheduler_step parameter) scheduler_fn (pytorch_lightning.strategies.HivemindStrategy parameter), [1] scheduling (pytorch_lightning.callbacks.GradientAccumulationScheduler parameter), [1], [2] seed (pytorch_lightning.utilities.seed.seed_everything parameter), [1] seed_everything() (in module pytorch_lightning.utilities.seed) (pytorch_lightning.lite.LightningLite static method) seed_everything_default (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] setup() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.CUDAAccelerator method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.DeviceStatsMonitor method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.ModelPruning method) (pytorch_lightning.callbacks.ProgressBarBase method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.core.hooks.DataHooks method) (pytorch_lightning.lite.LightningLite method) (pytorch_lightning.profilers.Profiler method) (pytorch_lightning.strategies.BaguaStrategy method) (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPFullyShardedStrategy method) (pytorch_lightning.strategies.DDPShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.DeepSpeedStrategy method) (pytorch_lightning.strategies.HivemindStrategy method) (pytorch_lightning.strategies.HorovodStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.SingleDeviceStrategy method) (pytorch_lightning.strategies.SingleHPUStrategy method) (pytorch_lightning.strategies.SingleTPUStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) setup_dataloaders() (pytorch_lightning.lite.LightningLite method) setup_environment() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.CPUAccelerator method) (pytorch_lightning.accelerators.CUDAAccelerator method) (pytorch_lightning.accelerators.HPUAccelerator method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.HPUParallelStrategy method) (pytorch_lightning.strategies.Strategy method) setup_optimizers() (pytorch_lightning.strategies.DeepSpeedStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.SingleHPUStrategy method) (pytorch_lightning.strategies.Strategy method) setup_precision_plugin() (pytorch_lightning.strategies.Strategy method) ShardedNativeMixedPrecisionPlugin (class in pytorch_lightning.plugins.precision) should_align (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] should_store_predictions (pytorch_lightning.loops.epoch.PredictionEpochLoop property) SimpleProfiler (class in pytorch_lightning.profilers) single_submit (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] SingleDeviceStrategy (class in pytorch_lightning.strategies) SingleHPUStrategy (class in pytorch_lightning.strategies) SingleTPUStrategy (class in pytorch_lightning.strategies) skip (pytorch_lightning.loops.dataloader.EvaluationLoop property) (pytorch_lightning.loops.dataloader.PredictionLoop property) (pytorch_lightning.loops.FitLoop property) SLURMEnvironment (class in pytorch_lightning.plugins.environments) sort_by_key (pytorch_lightning.profilers.PyTorchProfiler parameter), [1] split_idx (pytorch_lightning.loops.FitLoop property) split_size (pytorch_lightning.core.LightningModule.tbptt_split_batch parameter) (pytorch_lightning.core.module.LightningModule.tbptt_split_batch parameter) src (pytorch_lightning.strategies.BaguaStrategy.broadcast parameter) (pytorch_lightning.strategies.DataParallelStrategy.broadcast parameter) (pytorch_lightning.strategies.DDPSpawnStrategy.broadcast parameter) (pytorch_lightning.strategies.DDPStrategy.broadcast parameter) (pytorch_lightning.strategies.HivemindStrategy.broadcast parameter) (pytorch_lightning.strategies.HorovodStrategy.broadcast parameter) (pytorch_lightning.strategies.HPUParallelStrategy.broadcast parameter) (pytorch_lightning.strategies.IPUStrategy.broadcast parameter) (pytorch_lightning.strategies.SingleDeviceStrategy.broadcast parameter) (pytorch_lightning.strategies.Strategy.broadcast parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.broadcast parameter)

stage (pytorch_lightning.core.datamodule.LightningDataModule.teardown parameter) (pytorch_lightning.core.hooks.DataHooks.setup parameter) (pytorch_lightning.core.hooks.DataHooks.teardown parameter) (pytorch_lightning.core.module.LightningModule.setup parameter) (pytorch_lightning.core.module.LightningModule.teardown parameter) (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] start() (pytorch_lightning.profilers.AdvancedProfiler method) (pytorch_lightning.profilers.PassThroughProfiler method) (pytorch_lightning.profilers.Profiler method) (pytorch_lightning.profilers.PyTorchProfiler method) (pytorch_lightning.profilers.SimpleProfiler method) (pytorch_lightning.profilers.XLAProfiler method) start_time() (pytorch_lightning.callbacks.Timer method) state_dict (pytorch_lightning.callbacks.BackboneFinetuning.load_state_dict parameter) (pytorch_lightning.callbacks.BaseFinetuning.load_state_dict parameter) (pytorch_lightning.callbacks.Callback.load_state_dict parameter), [1] (pytorch_lightning.callbacks.EarlyStopping.load_state_dict parameter) (pytorch_lightning.callbacks.ModelCheckpoint.load_state_dict parameter) (pytorch_lightning.callbacks.StochasticWeightAveraging.load_state_dict parameter) (pytorch_lightning.callbacks.Timer.load_state_dict parameter) (pytorch_lightning.core.datamodule.LightningDataModule.load_state_dict parameter) (pytorch_lightning.core.LightningDataModule.load_state_dict parameter) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin.load_state_dict parameter) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin.load_state_dict parameter) (pytorch_lightning.plugins.precision.PrecisionPlugin.load_state_dict parameter) state_dict() (pytorch_lightning.callbacks.BackboneFinetuning method) (pytorch_lightning.callbacks.BaseFinetuning method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.EarlyStopping method) (pytorch_lightning.callbacks.ModelCheckpoint method) (pytorch_lightning.callbacks.QuantizationAwareTraining method) (pytorch_lightning.callbacks.StochasticWeightAveraging method) (pytorch_lightning.callbacks.Timer method) (pytorch_lightning.core.LightningDataModule method) (pytorch_lightning.plugins.precision.ApexMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) state_dict_to_cpu (pytorch_lightning.strategies.DDPFullyShardedStrategy parameter), [1] state_key (pytorch_lightning.callbacks.Callback property) (pytorch_lightning.callbacks.EarlyStopping property) (pytorch_lightning.callbacks.ModelCheckpoint property) status (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.wandb.WandbLogger.finalize parameter) (pytorch_lightning.loggers.WandbLogger.finalize parameter) step (pytorch_lightning.loggers.comet.CometLogger.log_metrics parameter) (pytorch_lightning.loggers.CometLogger.log_metrics parameter) (pytorch_lightning.loggers.csv_logs.CSVLogger.log_metrics parameter) (pytorch_lightning.loggers.CSVLogger.log_metrics parameter) (pytorch_lightning.loggers.mlflow.MLFlowLogger.log_metrics parameter) (pytorch_lightning.loggers.MLFlowLogger.log_metrics parameter) (pytorch_lightning.loggers.neptune.NeptuneLogger.log_metrics parameter) (pytorch_lightning.loggers.NeptuneLogger.log_metrics parameter) (pytorch_lightning.loggers.tensorboard.TensorBoardLogger.log_metrics parameter) (pytorch_lightning.loggers.TensorBoardLogger.log_metrics parameter) (pytorch_lightning.loggers.wandb.WandbLogger.log_metrics parameter) (pytorch_lightning.loggers.WandbLogger.log_metrics parameter) step() (pytorch_lightning.core.optimizer.LightningOptimizer method) step_output (pytorch_lightning.core.LightningModule.test_step_end parameter) (pytorch_lightning.core.LightningModule.training_step_end parameter) (pytorch_lightning.core.LightningModule.validation_step_end parameter) (pytorch_lightning.core.module.LightningModule.test_step_end parameter) (pytorch_lightning.core.module.LightningModule.training_step_end parameter) (pytorch_lightning.core.module.LightningModule.validation_step_end parameter) steps_per_trial (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) StochasticWeightAveraging (class in pytorch_lightning.callbacks) stop() (pytorch_lightning.profilers.AdvancedProfiler method) (pytorch_lightning.profilers.PassThroughProfiler method) (pytorch_lightning.profilers.Profiler method) (pytorch_lightning.profilers.PyTorchProfiler method) (pytorch_lightning.profilers.SimpleProfiler method) (pytorch_lightning.profilers.XLAProfiler method) stopping_threshold (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] storage_options (pytorch_lightning.plugins.io.CheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.HPUCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.TorchCheckpointIO.save_checkpoint parameter) (pytorch_lightning.plugins.io.XLACheckpointIO.save_checkpoint parameter) (pytorch_lightning.strategies.DeepSpeedStrategy.save_checkpoint parameter) (pytorch_lightning.strategies.Strategy.save_checkpoint parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.save_checkpoint parameter) (pytorch_lightning.trainer.trainer.Trainer.save_checkpoint parameter) str_to_bool() (in module pytorch_lightning.utilities.parsing) str_to_bool_or_int() (in module pytorch_lightning.utilities.parsing) str_to_bool_or_str() (in module pytorch_lightning.utilities.parsing) Strategy (class in pytorch_lightning.strategies) strategy (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] strict (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] (pytorch_lightning.core.module.LightningModule.load_from_checkpoint parameter) (pytorch_lightning.core.saving.ModelIO.load_from_checkpoint parameter) sub_dir (pytorch_lightning.loggers.tensorboard.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.tensorboard.TensorBoardLogger property) (pytorch_lightning.loggers.TensorBoardLogger parameter), [1] (pytorch_lightning.loggers.TensorBoardLogger property) sub_group_size (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] subclass_mode_data (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] subclass_mode_model (pytorch_lightning.utilities.cli.LightningCLI parameter), [1] swa_epoch_start (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1], [2] swa_lrs (pytorch_lightning.callbacks.StochasticWeightAveraging parameter), [1], [2] sync_batchnorm (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] sync_ddp() (in module pytorch_lightning.utilities.distributed) sync_ddp_if_available() (in module pytorch_lightning.utilities.distributed) sync_dist (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) sync_dist_group (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.LightningModule.log_dict parameter) (pytorch_lightning.core.module.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log_dict parameter) sync_grads (pytorch_lightning.core.LightningModule.all_gather parameter) (pytorch_lightning.core.module.LightningModule.all_gather parameter) (pytorch_lightning.lite.LightningLite.all_gather parameter), [1] (pytorch_lightning.strategies.HivemindStrategy.all_gather parameter) (pytorch_lightning.strategies.Strategy.all_gather parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.all_gather parameter) (pytorch_lightning.utilities.distributed.all_gather_ddp_if_available parameter), [1] synchronize_checkpoint_boundary (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1]

T

tag (pytorch_lightning.utilities.deepspeed.convert_zero_checkpoint_to_fp32_state_dict parameter), [1] tags (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.mlflow.resolve_tags parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] target_batch_size (pytorch_lightning.strategies.HivemindStrategy parameter), [1] tbptt_split_batch() (pytorch_lightning.core.LightningModule method) teardown() (pytorch_lightning.accelerators.Accelerator method) (pytorch_lightning.accelerators.CUDAAccelerator method) (pytorch_lightning.callbacks.Callback method) (pytorch_lightning.callbacks.RichProgressBar method) (pytorch_lightning.core.hooks.DataHooks method) (pytorch_lightning.loops.batch.TrainingBatchLoop method) (pytorch_lightning.loops.dataloader.EvaluationLoop method) (pytorch_lightning.loops.epoch.EvaluationEpochLoop method) (pytorch_lightning.loops.epoch.TrainingEpochLoop method) (pytorch_lightning.loops.FitLoop method) (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.io.AsyncCheckpointIO method) (pytorch_lightning.plugins.io.CheckpointIO method) (pytorch_lightning.plugins.precision.PrecisionPlugin method) (pytorch_lightning.plugins.precision.TPUBf16PrecisionPlugin method) (pytorch_lightning.profilers.AdvancedProfiler method) (pytorch_lightning.profilers.Profiler method) (pytorch_lightning.profilers.PyTorchProfiler method) (pytorch_lightning.strategies.BaguaStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.HivemindStrategy method) (pytorch_lightning.strategies.HorovodStrategy method) (pytorch_lightning.strategies.HPUParallelStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.ParallelStrategy method) (pytorch_lightning.strategies.SingleTPUStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) tensor (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin.to parameter) (pytorch_lightning.lite.LightningLite.backward parameter), [1] (pytorch_lightning.strategies.BaguaStrategy.reduce parameter) (pytorch_lightning.strategies.DDPSpawnStrategy.reduce parameter) (pytorch_lightning.strategies.DDPStrategy.reduce parameter) (pytorch_lightning.strategies.HivemindStrategy.all_gather parameter) (pytorch_lightning.strategies.HivemindStrategy.reduce parameter) (pytorch_lightning.strategies.HorovodStrategy.reduce parameter) (pytorch_lightning.strategies.IPUStrategy.reduce parameter) (pytorch_lightning.strategies.SingleDeviceStrategy.reduce parameter) (pytorch_lightning.strategies.Strategy.all_gather parameter) (pytorch_lightning.strategies.Strategy.reduce parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.all_gather parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.reduce parameter) (pytorch_lightning.utilities.distributed.all_gather_ddp_if_available parameter), [1] TensorBoardLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.tensorboard) test() (pytorch_lightning.trainer.trainer.Trainer method) test_batch_idx (pytorch_lightning.callbacks.ProgressBarBase property) test_dataloader() (pytorch_lightning.core.hooks.DataHooks method) test_dataset (pytorch_lightning.core.LightningDataModule.from_datasets parameter) test_epoch_end() (pytorch_lightning.core.LightningModule method) test_step() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPFullyShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.DeepSpeedStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) test_step_context() (pytorch_lightning.plugins.precision.PrecisionPlugin method) test_step_end() (pytorch_lightning.core.LightningModule method) theme (pytorch_lightning.callbacks.RichProgressBar parameter), [1], [2] thread_count (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1] time_elapsed() (pytorch_lightning.callbacks.Timer method) time_remaining() (pytorch_lightning.callbacks.Timer method) Timer (class in pytorch_lightning.callbacks) to() (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin method) to_cpu (pytorch_lightning.utilities.memory.recursive_detach parameter), [1] to_device() (pytorch_lightning.lite.LightningLite method) to_onnx() (pytorch_lightning.core.LightningModule method) to_torchscript() (pytorch_lightning.core.LightningModule method) to_yaml() (pytorch_lightning.callbacks.ModelCheckpoint method) toggle_model() (pytorch_lightning.core.optimizer.LightningOptimizer method) toggle_optimizer() (pytorch_lightning.core.LightningModule method)

torch_distributed_backend (pytorch_lightning.strategies.ParallelStrategy property) (pytorch_lightning.utilities.distributed.init_dist_connection parameter), [1] TorchCheckpointIO (class in pytorch_lightning.plugins.io) TorchElasticEnvironment (class in pytorch_lightning.plugins.environments) total_batch_idx (pytorch_lightning.loops.epoch.TrainingEpochLoop property) (pytorch_lightning.loops.FitLoop property) total_predict_batches_current_dataloader (pytorch_lightning.callbacks.ProgressBarBase property) total_test_batches_current_dataloader (pytorch_lightning.callbacks.ProgressBarBase property) total_train_batches (pytorch_lightning.callbacks.ProgressBarBase property) total_val_batches (pytorch_lightning.callbacks.ProgressBarBase property) total_val_batches_current_dataloader (pytorch_lightning.callbacks.ProgressBarBase property) tpu_cores (pytorch_lightning.lite.LightningLite parameter), [1] (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] TPUAccelerator (class in pytorch_lightning.accelerators) TPUBf16PrecisionPlugin (class in pytorch_lightning.plugins.precision) TPUPrecisionPlugin (class in pytorch_lightning.plugins.precision) TPUSpawnStrategy (class in pytorch_lightning.strategies) TQDMProgressBar (class in pytorch_lightning.callbacks) track_grad_norm (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] tracking_uri (pytorch_lightning.loggers.mlflow.MLFlowLogger parameter), [1] (pytorch_lightning.loggers.MLFlowLogger parameter), [1] train_batch_idx (pytorch_lightning.callbacks.ProgressBarBase property) train_bn (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] (pytorch_lightning.callbacks.BaseFinetuning.filter_params parameter) (pytorch_lightning.callbacks.BaseFinetuning.freeze parameter) (pytorch_lightning.callbacks.BaseFinetuning.unfreeze_and_add_param_group parameter) train_dataloader() (pytorch_lightning.core.hooks.DataHooks method) train_dataloaders (pytorch_lightning.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.tune parameter) (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) train_dataset (pytorch_lightning.core.LightningDataModule.from_datasets parameter) train_step_context() (pytorch_lightning.plugins.precision.PrecisionPlugin method) train_time_interval (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] Trainer (class in pytorch_lightning.trainer.trainer) trainer (pytorch_lightning.accelerators.Accelerator.setup parameter) (pytorch_lightning.accelerators.CUDAAccelerator.setup parameter) (pytorch_lightning.callbacks.Callback.on_load_checkpoint parameter), [1] (pytorch_lightning.callbacks.Callback.on_save_checkpoint parameter), [1] (pytorch_lightning.callbacks.ModelPruning.on_save_checkpoint parameter) (pytorch_lightning.strategies.BaguaStrategy.setup parameter) (pytorch_lightning.strategies.DataParallelStrategy.setup parameter) (pytorch_lightning.strategies.DDPFullyShardedStrategy.setup parameter) (pytorch_lightning.strategies.DDPShardedStrategy.setup parameter) (pytorch_lightning.strategies.DDPSpawnStrategy.setup parameter) (pytorch_lightning.strategies.DDPStrategy.setup parameter) (pytorch_lightning.strategies.DeepSpeedStrategy.setup parameter) (pytorch_lightning.strategies.DeepSpeedStrategy.setup_optimizers parameter) (pytorch_lightning.strategies.HivemindStrategy.setup parameter) (pytorch_lightning.strategies.HorovodStrategy.setup parameter) (pytorch_lightning.strategies.IPUStrategy.setup parameter) (pytorch_lightning.strategies.IPUStrategy.setup_optimizers parameter) (pytorch_lightning.strategies.SingleDeviceStrategy.setup parameter) (pytorch_lightning.strategies.SingleHPUStrategy.setup parameter) (pytorch_lightning.strategies.SingleHPUStrategy.setup_optimizers parameter) (pytorch_lightning.strategies.SingleTPUStrategy.setup parameter) (pytorch_lightning.strategies.Strategy.setup parameter) (pytorch_lightning.strategies.Strategy.setup_optimizers parameter) (pytorch_lightning.strategies.TPUSpawnStrategy.setup 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.LightningModule method) training_opts (pytorch_lightning.strategies.IPUStrategy parameter), [1] training_step() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPFullyShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) training_step_end() (pytorch_lightning.core.LightningModule method) TrainingBatchLoop (class in pytorch_lightning.loops.batch) TrainingEpochLoop (class in pytorch_lightning.loops.epoch) transfer_batch_to_device() (pytorch_lightning.core.hooks.DataHooks method) TransferableDataType (class in pytorch_lightning.utilities.apply_func) truncated_bptt_steps (pytorch_lightning.core.LightningModule property) tune() (pytorch_lightning.trainer.trainer.Trainer method) Tuner (class in pytorch_lightning.tuner.tuning) type() (pytorch_lightning.core.mixins.DeviceDtypeModuleMixin method)

U

unfreeze() (pytorch_lightning.core.LightningModule method) unfreeze_and_add_param_group() (pytorch_lightning.callbacks.BaseFinetuning static method) unfreeze_backbone_at_epoch (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] untoggle_optimizer() (pytorch_lightning.core.LightningModule method) update_attr (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) update_lr_schedulers() (pytorch_lightning.loops.epoch.TrainingEpochLoop method) update_parameters() (pytorch_lightning.callbacks.StochasticWeightAveraging static method) use_amp (pytorch_lightning.core.LightningModule property)

use_argument_group (pytorch_lightning.utilities.argparse.add_argparse_args parameter), [1] use_global_unstructured (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] use_lottery_ticket_hypothesis (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] use_pl_optimizer (pytorch_lightning.core.LightningModule.optimizers parameter) (pytorch_lightning.core.module.LightningModule.optimizers parameter) using_lbfgs (pytorch_lightning.core.LightningModule.optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_step parameter) using_native_amp (pytorch_lightning.core.LightningModule.optimizer_step parameter) (pytorch_lightning.core.module.LightningModule.optimizer_step parameter)

V

val_batch_idx (pytorch_lightning.callbacks.ProgressBarBase property) val_check_interval (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] val_dataloader() (pytorch_lightning.core.hooks.DataHooks method) val_dataloaders (pytorch_lightning.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.fit parameter) (pytorch_lightning.trainer.trainer.Trainer.tune parameter) (pytorch_lightning.trainer.Trainer.tune parameter) (pytorch_lightning.tuner.tuning.Tuner.lr_find parameter) (pytorch_lightning.tuner.tuning.Tuner.scale_batch_size parameter) val_dataset (pytorch_lightning.core.LightningDataModule.from_datasets parameter) val_step_context() (pytorch_lightning.plugins.precision.PrecisionPlugin method) validate() (pytorch_lightning.trainer.trainer.Trainer method) validation_epoch_end() (pytorch_lightning.core.LightningModule method) validation_step() (pytorch_lightning.core.LightningModule method) (pytorch_lightning.strategies.DataParallelStrategy method) (pytorch_lightning.strategies.DDPFullyShardedStrategy method) (pytorch_lightning.strategies.DDPSpawnStrategy method) (pytorch_lightning.strategies.DDPStrategy method) (pytorch_lightning.strategies.DeepSpeedStrategy method) (pytorch_lightning.strategies.IPUStrategy method) (pytorch_lightning.strategies.Strategy method) (pytorch_lightning.strategies.TPUSpawnStrategy method) validation_step_end() (pytorch_lightning.core.LightningModule method) value (pytorch_lightning.core.LightningModule.log parameter) (pytorch_lightning.core.module.LightningModule.log parameter) verbose (pytorch_lightning.callbacks.BackboneFinetuning parameter), [1], [2] (pytorch_lightning.callbacks.EarlyStopping parameter), [1], [2] (pytorch_lightning.callbacks.ModelCheckpoint parameter), [1], [2] (pytorch_lightning.callbacks.ModelPruning parameter), [1], [2] (pytorch_lightning.callbacks.Timer parameter), [1], [2] (pytorch_lightning.plugins.precision.HPUPrecisionPlugin parameter), [1], [2] (pytorch_lightning.strategies.HivemindStrategy 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), [1]

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

W

WandbLogger (class in pytorch_lightning.loggers) (class in pytorch_lightning.loggers.wandb) WarningCache (class in pytorch_lightning.utilities.warnings) weights_only (pytorch_lightning.trainer.trainer.Trainer.save_checkpoint parameter) weights_save_path (pytorch_lightning.trainer.Trainer parameter) (pytorch_lightning.trainer.trainer.Trainer parameter), [1] (pytorch_lightning.trainer.trainer.Trainer property) workers (pytorch_lightning.utilities.seed.seed_everything parameter), [1] world_size (pytorch_lightning.lite.LightningLite property) (pytorch_lightning.utilities.distributed.init_dist_connection parameter), [1] world_size() (pytorch_lightning.plugins.environments.ClusterEnvironment method) (pytorch_lightning.plugins.environments.KubeflowEnvironment method) (pytorch_lightning.plugins.environments.LightningEnvironment method) (pytorch_lightning.plugins.environments.LSFEnvironment method) (pytorch_lightning.plugins.environments.SLURMEnvironment method) (pytorch_lightning.plugins.environments.TorchElasticEnvironment method) (pytorch_lightning.plugins.environments.XLAEnvironment method)

write_interval (pytorch_lightning.callbacks.BasePredictionWriter parameter), [1], [2] write_on_batch_end() (pytorch_lightning.callbacks.BasePredictionWriter method) write_on_epoch_end() (pytorch_lightning.callbacks.BasePredictionWriter method) wrong_dtype (pytorch_lightning.utilities.apply_func.apply_to_collection parameter), [1] (pytorch_lightning.utilities.apply_func.apply_to_collections parameter), [1]

X

XLACheckpointIO (class in pytorch_lightning.plugins.io)

XLAEnvironment (class in pytorch_lightning.plugins.environments) XLAProfiler (class in pytorch_lightning.profilers)

Z

zero_allow_untested_optimizer (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1]

zero_optimization (pytorch_lightning.strategies.DeepSpeedStrategy parameter), [1]