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devel 1.9

If

Then

Ref

passed the pl_module argument to distributed module wrappers

passed the (required) forward_module argument

PR16386

used DataParallel and the LightningParallelModule wrapper

use DDP or DeepSpeed instead

PR16748 DDP

used pl_module argument from the distributed module wrappers

use DDP or DeepSpeed instead

PR16386 DDP

called pl.overrides.base.unwrap_lightning_module function

use DDP or DeepSpeed instead

PR16386 DDP

used or derived from pl.overrides.distributed.LightningDistributedModule class

use DDP instead

PR16386 DDP

used the pl.plugins.ApexMixedPrecisionPlugin`` plugin

use PyTorch native mixed precision

PR16039

used the pl.plugins.NativeMixedPrecisionPlugin plugin

switch to the pl.plugins.MixedPrecisionPlugin plugin

PR16039

used the fit_loop.min_steps setters

implement your training loop with Fabric

PR16803

used the fit_loop.max_steps setters

implement your training loop with Fabric

PR16803

used the data_parallel attribute in Trainer

check the same using isinstance(trainer.strategy, ParallelStrategy)

PR16703

used any function from pl.utilities.xla_device

switch to pl.accelerators.TPUAccelerator.is_available()

PR14514 PR14550

imported functions from pl.utilities.device_parser.*

import them from lightning_fabric.utilities.device_parser.*

PR14492 PR14753

imported functions from pl.utilities.cloud_io.*

import them from lightning_fabric.utilities.cloud_io.*

PR14515

imported functions from pl.utilities.apply_func.*

import them from lightning_utilities.core.apply_func.*

PR14516 PR14537

used any code from pl.core.mixins

use the base classes

PR16424

used any code from pl.utilities.distributed

rely on Pytorch’s native functions

PR16390

used any code from pl.utilities.data

it was removed

PR16440

used any code from pl.utilities.optimizer

it was removed

PR16439

used any code from pl.utilities.seed

it was removed

PR16422

were using truncated backpropagation through time (TBPTT) with LightningModule.truncated_bptt_steps

use manual optimization

PR16172 Manual Optimization

were using truncated backpropagation through time (TBPTT) with LightningModule.tbptt_split_batch

use manual optimization

PR16172 Manual Optimization

were using truncated backpropagation through time (TBPTT) and passing hidden to LightningModule.training_step

use manual optimization

PR16172 Manual Optimization

used pl.utilities.finite_checks.print_nan_gradients function

it was removed

used pl.utilities.finite_checks.detect_nan_parameters function

it was removed

used pl.utilities.parsing.flatten_dict function

it was removed

used pl.utilities.metrics.metrics_to_scalars function

it was removed

used pl.utilities.memory.get_model_size_mb function

it was removed

used pl.strategies.utils.on_colab_kaggle function

it was removed

PR16437

used LightningDataModule.add_argparse_args() method

switch to using LightningCLI

PR16708

used LightningDataModule.parse_argparser() method

switch to using LightningCLI

PR16708

used LightningDataModule.from_argparse_args() method

switch to using LightningCLI

PR16708

used LightningDataModule.get_init_arguments_and_types() method

switch to using LightningCLI

PR16708

used Trainer.default_attributes() method

switch to using LightningCLI

PR16708

used Trainer.from_argparse_args() method

switch to using LightningCLI

PR16708

used Trainer.parse_argparser() method

switch to using LightningCLI

PR16708

used Trainer.match_env_arguments() method

switch to using LightningCLI

PR16708

used Trainer.add_argparse_args() method

switch to using LightningCLI

PR16708

used pl.utilities.argparse.from_argparse_args() function

switch to using LightningCLI

PR16708

used pl.utilities.argparse.parse_argparser() function

switch to using LightningCLI

PR16708

used pl.utilities.argparseparse_env_variables() function

switch to using LightningCLI

PR16708

used get_init_arguments_and_types() function

switch to using LightningCLI

PR16708

used pl.utilities.argparse.add_argparse_args() function

switch to using LightningCLI

PR16708

used pl.utilities.parsing.str_to_bool() function

switch to using LightningCLI

PR16708

used pl.utilities.parsing.str_to_bool_or_int() function

switch to using LightningCLI

PR16708

used pl.utilities.parsing.str_to_bool_or_str() function

switch to using LightningCLI

PR16708

derived from pl.utilities.distributed.AllGatherGrad class

switch to PyTorch native equivalent

PR15364

used PL_RECONCILE_PROCESS=1 env. variable

customize your logger

PR16204

if you derived from mixin’s method pl.core.saving.ModelIO.load_from_checkpoint

rely on pl.core.module.LightningModule

PR16999

used Accelerator.setup_environment method

switch to Accelerator.setup_device

PR16436

used PL_FAULT_TOLERANT_TRAINING env. variable

implement own logic with Fabric

PR16516 PR16533

used or derived from public pl.overrides.distributed.IndexBatchSamplerWrapper class

it is set as protected

PR16826

used the DataLoaderLoop class

use manual optimization

PR16726 Manual Optimization

used the EvaluationEpochLoop class

use manual optimization

PR16726 Manual Optimization

used the PredictionEpochLoop class

use manual optimization

PR16726 Manual Optimization

used trainer.reset_*_dataloader() methods

use Loop.setup_data() for the top-level loops

PR16726

used LightningModule.precision attribute

rely on Trainer precision attribute

PR16203

used Trainer.model setter

you shall pass the model in fit/test/predict method

PR16462

relied on pl.utilities.supporters.CombinedLoaderIterator class

pass dataloders directly

PR16714

relied on pl.utilities.supporters.CombinedLoaderIterator class

pass dataloders directly

PR16714

accessed ProgressBarBase.train_batch_idx property

rely on Trainer internal loops’ properties

PR16760

accessed ProgressBarBase.val_batch_idx property

rely on Trainer internal loops’ properties

PR16760

accessed ProgressBarBase.test_batch_idx property

rely on Trainer internal loops’ properties

PR16760

accessed ProgressBarBase.predict_batch_idx property

rely on Trainer internal loops’ properties

PR16760

used Trainer.prediction_writer_callbacks property

rely on precision plugin

PR16759

used PrecisionPlugin.dispatch

it was removed

PR16618

used Strategy.dispatch

it was removed

PR16618


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