Move the `CombinedLoader` to an utility file (#16819)

docs/source-pytorch/guides/data.rst

@@ -49,8 +49,8 @@ There are a few ways to pass multiple Datasets to Lightning:
 2. In the training loop, you can pass multiple DataLoaders as a dict or list/tuple, and Lightning will
    automatically combine the batches from different DataLoaders.
 3. In the validation, test, or prediction, you have the option to return multiple DataLoaders as list/tuple, which Lightning will call sequentially
-   or combine the DataLoaders using :class:`~pytorch_lightning.trainer.supporters.CombinedLoader`, which Lightning will
-   automatically combine the batches from different DataLoaders.
+   or combine the DataLoaders using :class:`~pytorch_lightning.utilities.CombinedLoader`, which is what Lightning uses
+   under the hood.
 
 
 Using LightningDataModule
@@ -174,11 +174,11 @@ Furthermore, Lightning also supports nested lists and dicts (or a combination).
             batch_c = batch_c_d["c"]
             batch_d = batch_c_d["d"]
 
-Alternatively, you can also pass in a :class:`~pytorch_lightning.trainer.supporters.CombinedLoader` containing multiple DataLoaders.
+Alternatively, you can also pass in a :class:`~pytorch_lightning.utilities.CombinedLoader` containing multiple DataLoaders.
 
 .. testcode::
 
-    from pytorch_lightning.trainer.supporters import CombinedLoader
+    from pytorch_lightning.utilities import CombinedLoader
 
 
     def train_dataloader(self):
@@ -222,18 +222,18 @@ Refer to the following for more details for the default sequential option:
         ...
 
 
-Evaluation DataLoaders are iterated over sequentially. If you want to iterate over them in parallel, PyTorch Lightning provides a :class:`~pytorch_lightning.trainer.supporters.CombinedLoader` object which supports collections of DataLoaders such as list, tuple, or dictionary. The DataLoaders can be accessed using in the same way as the provided structure:
+Evaluation DataLoaders are iterated over sequentially. The above is equivalent to:
 
 .. testcode::
 
-    from pytorch_lightning.trainer.supporters import CombinedLoader
+    from pytorch_lightning.utilities import CombinedLoader
 
 
     def val_dataloader(self):
         loader_a = DataLoader()
         loader_b = DataLoader()
         loaders = {"a": loader_a, "b": loader_b}
-        combined_loaders = CombinedLoader(loaders, mode="max_size_cycle")
+        combined_loaders = CombinedLoader(loaders, mode="sequential")
         return combined_loaders
 
 
@@ -279,12 +279,12 @@ In the case that you require access to the DataLoader or Dataset objects, DataLo
             # extract metadata, etc. from the dataset:
             ...
 
-If you are using a :class:`~pytorch_lightning.trainer.supporters.CombinedLoader` object which allows you to fetch batches from a collection of DataLoaders
+If you are using a :class:`~pytorch_lightning.utilities.CombinedLoader` object which allows you to fetch batches from a collection of DataLoaders
 simultaneously which supports collections of DataLoader such as list, tuple, or dictionary. The DataLoaders can be accessed using the same collection structure:
 
 .. code-block:: python
 
-    from pytorch_lightning.trainer.supporters import CombinedLoader
+    from pytorch_lightning.utilities import CombinedLoader
 
     test_dl1 = ...
     test_dl2 = ...
@@ -292,14 +292,14 @@ simultaneously which supports collections of DataLoader such as list, tuple, or
     # If you provided a list of DataLoaders:
 
     combined_loader = CombinedLoader([test_dl1, test_dl2])
-    list_of_loaders = combined_loader.loaders
+    list_of_loaders = combined_loader.iterables
     test_dl1 = list_of_loaders.loaders[0]
 
 
     # If you provided dictionary of DataLoaders:
 
     combined_loader = CombinedLoader({"dl1": test_dl1, "dl2": test_dl2})
-    dictionary_of_loaders = combined_loader.loaders
+    dictionary_of_loaders = combined_loader.iterables
     test_dl1 = dictionary_of_loaders["dl1"]
 
 --------------

src/lightning/pytorch/CHANGELOG.md

@@ -93,6 +93,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Renamed `CombinedLoader.loaders` to `CombinedLoader.iterables` ([#16743](https://github.com/Lightning-AI/lightning/pull/16743))
 
 
+- Moved the `CombinedLoader` class from `lightning.pytorch.trainer.supporters` to `lightning.pytorch.combined_loader` ([#16819](https://github.com/Lightning-AI/lightning/pull/16819))
+
+
 - The top-level loops now own the data sources and combined dataloaders ([#16726](https://github.com/Lightning-AI/lightning/pull/16726))
 
 

src/lightning/pytorch/loops/evaluation_loop.py

@@ -30,7 +30,7 @@ from lightning.pytorch.trainer import call
 from lightning.pytorch.trainer.connectors.data_connector import _DataLoaderSource
 from lightning.pytorch.trainer.connectors.logger_connector.result import _OUT_DICT, _ResultCollection
 from lightning.pytorch.trainer.states import TrainerFn
-from lightning.pytorch.trainer.supporters import _Sequential, CombinedLoader
+from lightning.pytorch.utilities.combined_loader import _Sequential, CombinedLoader
 from lightning.pytorch.utilities.exceptions import SIGTERMException
 from lightning.pytorch.utilities.model_helpers import is_overridden
 

src/lightning/pytorch/loops/fetchers.py

@@ -17,7 +17,11 @@ from typing import Any, Iterable, Iterator, List, Optional, Sized, Tuple, Union
 from torch.utils.data.dataloader import DataLoader
 
 from lightning.fabric.utilities.data import has_len
-from lightning.pytorch.trainer.supporters import _Sequential, _shutdown_workers_and_reset_iterator, CombinedLoader
+from lightning.pytorch.utilities.combined_loader import (
+    _Sequential,
+    _shutdown_workers_and_reset_iterator,
+    CombinedLoader,
+)
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
 
 

src/lightning/pytorch/loops/fit_loop.py

@@ -25,7 +25,7 @@ from lightning.pytorch.trainer import call
 from lightning.pytorch.trainer.connectors.data_connector import _DataLoaderSource
 from lightning.pytorch.trainer.connectors.logger_connector.result import _ResultCollection
 from lightning.pytorch.trainer.states import RunningStage
-from lightning.pytorch.trainer.supporters import CombinedLoader
+from lightning.pytorch.utilities.combined_loader import CombinedLoader
 from lightning.pytorch.utilities.data import has_len_all_ranks
 from lightning.pytorch.utilities.exceptions import MisconfigurationException, SIGTERMException
 from lightning.pytorch.utilities.model_helpers import is_overridden

src/lightning/pytorch/loops/prediction_loop.py

@@ -16,7 +16,7 @@ from lightning.pytorch.strategies import DDPSpawnStrategy
 from lightning.pytorch.trainer import call
 from lightning.pytorch.trainer.connectors.data_connector import _DataLoaderSource
 from lightning.pytorch.trainer.states import RunningStage
-from lightning.pytorch.trainer.supporters import _Sequential, CombinedLoader
+from lightning.pytorch.utilities.combined_loader import _Sequential, CombinedLoader
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
 from lightning.pytorch.utilities.types import _PREDICT_OUTPUT
 

src/lightning/pytorch/trainer/connectors/data_connector.py

@@ -28,7 +28,7 @@ from lightning.pytorch.overrides.distributed import UnrepeatedDistributedSampler
 from lightning.pytorch.strategies import DDPSpawnStrategy
 from lightning.pytorch.trainer import call
 from lightning.pytorch.trainer.states import RunningStage, TrainerFn
-from lightning.pytorch.trainer.supporters import CombinedLoader
+from lightning.pytorch.utilities.combined_loader import CombinedLoader
 from lightning.pytorch.utilities.data import _is_dataloader_shuffled, _update_dataloader, has_len_all_ranks
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
 from lightning.pytorch.utilities.model_helpers import is_overridden

src/lightning/pytorch/utilities/__init__.py

@@ -18,6 +18,7 @@ import numpy
 from lightning.fabric.utilities import LightningEnum  # noqa: F401
 from lightning.fabric.utilities import move_data_to_device  # noqa: F401
 from lightning.pytorch.accelerators.hpu import _HPU_AVAILABLE  # noqa: F401
+from lightning.pytorch.utilities.combined_loader import CombinedLoader  # noqa: F401
 from lightning.pytorch.utilities.enums import GradClipAlgorithmType  # noqa: F401
 from lightning.pytorch.utilities.grads import grad_norm  # noqa: F401
 from lightning.pytorch.utilities.imports import _OMEGACONF_AVAILABLE, _TORCHVISION_AVAILABLE  # noqa: F401

tests/tests_pytorch/loops/test_fetchers.py

@@ -22,7 +22,7 @@ from lightning.pytorch import LightningDataModule, Trainer
 from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
 from lightning.pytorch.loops.fetchers import _DataLoaderIterDataFetcher, _PrefetchDataFetcher
 from lightning.pytorch.profilers import SimpleProfiler
-from lightning.pytorch.trainer.supporters import CombinedLoader
+from lightning.pytorch.utilities.combined_loader import CombinedLoader
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
 from lightning.pytorch.utilities.types import STEP_OUTPUT
 from tests_pytorch.helpers.runif import RunIf

tests/tests_pytorch/trainer/connectors/test_data_connector.py

@@ -29,7 +29,7 @@ from lightning.pytorch.demos.boring_classes import BoringDataModule, BoringModel
 from lightning.pytorch.strategies import DDPSpawnStrategy
 from lightning.pytorch.trainer.connectors.data_connector import _DataHookSelector, _DataLoaderSource, warning_cache
 from lightning.pytorch.trainer.states import RunningStage, TrainerFn
-from lightning.pytorch.trainer.supporters import CombinedLoader
+from lightning.pytorch.utilities.combined_loader import CombinedLoader
 from lightning.pytorch.utilities.data import _update_dataloader
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
 from tests_pytorch.helpers.runif import RunIf

tests/tests_pytorch/trainer/test_dataloaders.py

@@ -34,7 +34,7 @@ from lightning.pytorch.demos.boring_classes import (
 )
 from lightning.pytorch.loggers import CSVLogger
 from lightning.pytorch.trainer.states import RunningStage
-from lightning.pytorch.trainer.supporters import CombinedLoader
+from lightning.pytorch.utilities.combined_loader import CombinedLoader
 from lightning.pytorch.utilities.data import has_len_all_ranks
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
 from tests_pytorch.helpers.dataloaders import CustomInfDataloader, CustomNotImplementedErrorDataloader

tests/tests_pytorch/utilities/test_combined_loader.py

@@ -25,7 +25,13 @@ from torch.utils.data.sampler import RandomSampler, SequentialSampler
 
 from lightning.pytorch import Trainer
 from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
-from lightning.pytorch.trainer.supporters import _MaxSizeCycle, _MinSize, _Sequential, _supported_modes, CombinedLoader
+from lightning.pytorch.utilities.combined_loader import (
+    _MaxSizeCycle,
+    _MinSize,
+    _Sequential,
+    _supported_modes,
+    CombinedLoader,
+)
 from tests_pytorch.helpers.runif import RunIf