External callback registry through entry points for Fabric (#17756)

src/lightning/fabric/CHANGELOG.md

@@ -7,6 +7,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [UnReleased] - 2023-04-DD
 
+- Added support for `Callback` registration through entry points ([#17756](https://github.com/Lightning-AI/lightning/pull/17756))
+
+
 ### Changed
 
 -

src/lightning/fabric/fabric.py

@@ -43,6 +43,7 @@
     has_iterable_dataset,
 )
 from lightning.fabric.utilities.distributed import DistributedSamplerWrapper
+from lightning.fabric.utilities.registry import _load_external_callbacks
 from lightning.fabric.utilities.seed import seed_everything
 from lightning.fabric.utilities.types import ReduceOp
 from lightning.fabric.utilities.warnings import PossibleUserWarning
@@ -105,8 +106,7 @@ def __init__(
         self._strategy: Strategy = self._connector.strategy
         self._accelerator: Accelerator = self._connector.accelerator
         self._precision: Precision = self._strategy.precision
-        callbacks = callbacks if callbacks is not None else []
-        self._callbacks = callbacks if isinstance(callbacks, list) else [callbacks]
+        self._callbacks = self._configure_callbacks(callbacks)
         loggers = loggers if loggers is not None else []
         self._loggers = loggers if isinstance(loggers, list) else [loggers]
         self._models_setup: int = 0
@@ -846,6 +846,13 @@ def _validate_setup_dataloaders(dataloaders: Sequence[DataLoader]) -> None:
         if any(not isinstance(dl, DataLoader) for dl in dataloaders):
             raise TypeError("Only PyTorch DataLoader are currently supported in `setup_dataloaders`.")
 
+    @staticmethod
+    def _configure_callbacks(callbacks: Optional[Union[List[Any], Any]]) -> List[Any]:
+        callbacks = callbacks if callbacks is not None else []
+        callbacks = callbacks if isinstance(callbacks, list) else [callbacks]
+        callbacks.extend(_load_external_callbacks("lightning.fabric.callbacks_factory"))
+        return callbacks
+
 
 def _is_using_cli() -> bool:
     return bool(int(os.environ.get("LT_CLI_USED", "0")))

src/lightning/fabric/utilities/imports.py

@@ -30,3 +30,6 @@
 _TORCH_GREATER_EQUAL_2_0 = compare_version("torch", operator.ge, "2.0.0", use_base_version=True)
 _TORCH_GREATER_EQUAL_2_1 = compare_version("torch", operator.ge, "2.1.0", use_base_version=True)
 _TORCH_EQUAL_2_0 = _TORCH_GREATER_EQUAL_2_0 and not _TORCH_GREATER_EQUAL_2_1
+
+_PYTHON_GREATER_EQUAL_3_8_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 8)
+_PYTHON_GREATER_EQUAL_3_10_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 10)

src/lightning/fabric/utilities/registry.py

@@ -12,7 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import inspect
-from typing import Any
+import logging
+from typing import Any, List, Union
+
+from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
+
+_log = logging.getLogger(__name__)
 
 
 def _is_register_method_overridden(mod: type, base_cls: Any, method: str) -> bool:
@@ -25,3 +30,40 @@ def _is_register_method_overridden(mod: type, base_cls: Any, method: str) -> boo
         return False
 
     return mod_attr.__code__ is not super_attr.__code__
+
+
+def _load_external_callbacks(group: str) -> List[Any]:
+    """Collect external callbacks registered through entry points.
+
+    The entry points are expected to be functions returning a list of callbacks.
+
+    Args:
+        group: The entry point group name to load callbacks from.
+
+    Return:
+        A list of all callbacks collected from external factories.
+    """
+    if _PYTHON_GREATER_EQUAL_3_8_0:
+        from importlib.metadata import entry_points
+
+        factories = (
+            entry_points(group=group)
+            if _PYTHON_GREATER_EQUAL_3_10_0
+            else entry_points().get(group, {})  # type: ignore[arg-type]
+        )
+    else:
+        from pkg_resources import iter_entry_points
+
+        factories = iter_entry_points(group)  # type: ignore[assignment]
+
+    external_callbacks: List[Any] = []
+    for factory in factories:
+        callback_factory = factory.load()
+        callbacks_list: Union[List[Any], Any] = callback_factory()
+        callbacks_list = [callbacks_list] if not isinstance(callbacks_list, list) else callbacks_list
+        _log.info(
+            f"Adding {len(callbacks_list)} callbacks from entry point '{factory.name}':"
+            f" {', '.join(type(cb).__name__ for cb in callbacks_list)}"
+        )
+        external_callbacks.extend(callbacks_list)
+    return external_callbacks

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

@@ -18,6 +18,7 @@
 from typing import Dict, List, Optional, Sequence, Union
 
 import lightning.pytorch as pl
+from lightning.fabric.utilities.registry import _load_external_callbacks
 from lightning.pytorch.callbacks import (
     Callback,
     Checkpoint,
@@ -33,7 +34,6 @@
 from lightning.pytorch.callbacks.timer import Timer
 from lightning.pytorch.trainer import call
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
-from lightning.pytorch.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
 from lightning.pytorch.utilities.model_helpers import is_overridden
 from lightning.pytorch.utilities.rank_zero import rank_zero_info
 
@@ -75,7 +75,7 @@ def on_trainer_init(
         # configure the ModelSummary callback
         self._configure_model_summary_callback(enable_model_summary)
 
-        self.trainer.callbacks.extend(_configure_external_callbacks())
+        self.trainer.callbacks.extend(_load_external_callbacks("lightning.pytorch.callbacks_factory"))
         _validate_callbacks_list(self.trainer.callbacks)
 
         # push all model checkpoint callbacks to the end
@@ -213,42 +213,6 @@ def _reorder_callbacks(callbacks: List[Callback]) -> List[Callback]:
         return tuner_callbacks + other_callbacks + checkpoint_callbacks
 
 
-def _configure_external_callbacks() -> List[Callback]:
-    """Collect external callbacks registered through entry points.
-
-    The entry points are expected to be functions returning a list of callbacks.
-
-    Return:
-        A list of all callbacks collected from external factories.
-    """
-    group = "lightning.pytorch.callbacks_factory"
-
-    if _PYTHON_GREATER_EQUAL_3_8_0:
-        from importlib.metadata import entry_points
-
-        factories = (
-            entry_points(group=group)
-            if _PYTHON_GREATER_EQUAL_3_10_0
-            else entry_points().get(group, {})  # type: ignore[arg-type]
-        )
-    else:
-        from pkg_resources import iter_entry_points
-
-        factories = iter_entry_points(group)  # type: ignore[assignment]
-
-    external_callbacks: List[Callback] = []
-    for factory in factories:
-        callback_factory = factory.load()
-        callbacks_list: Union[List[Callback], Callback] = callback_factory()
-        callbacks_list = [callbacks_list] if isinstance(callbacks_list, Callback) else callbacks_list
-        _log.info(
-            f"Adding {len(callbacks_list)} callbacks from entry point '{factory.name}':"
-            f" {', '.join(type(cb).__name__ for cb in callbacks_list)}"
-        )
-        external_callbacks.extend(callbacks_list)
-    return external_callbacks
-
-
 def _validate_callbacks_list(callbacks: List[Callback]) -> None:
     stateful_callbacks = [cb for cb in callbacks if is_overridden("state_dict", instance=cb)]
     seen_callbacks = set()

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

@@ -11,8 +11,7 @@
 
 import lightning.pytorch as pl
 from lightning.fabric.plugins.environments import SLURMEnvironment
-from lightning.fabric.utilities.imports import _IS_WINDOWS
-from lightning.pytorch.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0
+from lightning.fabric.utilities.imports import _IS_WINDOWS, _PYTHON_GREATER_EQUAL_3_8_0
 from lightning.pytorch.utilities.rank_zero import rank_zero_info
 
 # copied from signal.pyi

src/lightning/pytorch/utilities/imports.py

@@ -17,8 +17,6 @@
 import torch
 from lightning_utilities.core.imports import package_available, RequirementCache
 
-_PYTHON_GREATER_EQUAL_3_8_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 8)
-_PYTHON_GREATER_EQUAL_3_10_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 10)
 _PYTHON_GREATER_EQUAL_3_11_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 11)
 _TORCHMETRICS_GREATER_EQUAL_0_9_1 = RequirementCache("torchmetrics>=0.9.1")
 _TORCHMETRICS_GREATER_EQUAL_0_11 = RequirementCache("torchmetrics>=0.11.0")  # using new API with task

tests/tests_fabric/utilities/test_registry.py

@@ -0,0 +1,64 @@
+import contextlib
+from unittest import mock
+from unittest.mock import Mock
+
+from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
+from lightning.fabric.utilities.registry import _load_external_callbacks
+
+
+class ExternalCallback:
+    """A callback in another library that gets registered through entry points."""
+
+    pass
+
+
+def test_load_external_callbacks():
+    """Test that the connector collects Callback instances from factories registered through entry points."""
+
+    def factory_no_callback():
+        return []
+
+    def factory_one_callback():
+        return ExternalCallback()
+
+    def factory_one_callback_list():
+        return [ExternalCallback()]
+
+    def factory_multiple_callbacks_list():
+        return [ExternalCallback(), ExternalCallback()]
+
+    with _make_entry_point_query_mock(factory_no_callback):
+        callbacks = _load_external_callbacks("lightning.pytorch.callbacks_factory")
+    assert callbacks == []
+
+    with _make_entry_point_query_mock(factory_one_callback):
+        callbacks = _load_external_callbacks("lightning.pytorch.callbacks_factory")
+    assert isinstance(callbacks[0], ExternalCallback)
+
+    with _make_entry_point_query_mock(factory_one_callback_list):
+        callbacks = _load_external_callbacks("lightning.pytorch.callbacks_factory")
+    assert isinstance(callbacks[0], ExternalCallback)
+
+    with _make_entry_point_query_mock(factory_multiple_callbacks_list):
+        callbacks = _load_external_callbacks("lightning.pytorch.callbacks_factory")
+    assert isinstance(callbacks[0], ExternalCallback)
+    assert isinstance(callbacks[1], ExternalCallback)
+
+
+@contextlib.contextmanager
+def _make_entry_point_query_mock(callback_factory):
+    query_mock = Mock()
+    entry_point = Mock()
+    entry_point.name = "mocked"
+    entry_point.load.return_value = callback_factory
+    if _PYTHON_GREATER_EQUAL_3_10_0:
+        query_mock.return_value = [entry_point]
+        import_path = "importlib.metadata.entry_points"
+    elif _PYTHON_GREATER_EQUAL_3_8_0:
+        query_mock().get.return_value = [entry_point]
+        import_path = "importlib.metadata.entry_points"
+    else:
+        query_mock.return_value = [entry_point]
+        import_path = "pkg_resources.iter_entry_points"
+    with mock.patch(import_path, query_mock):
+        yield

tests/tests_pytorch/trainer/connectors/test_callback_connector.py

@@ -19,6 +19,7 @@
 import pytest
 import torch
 
+from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
 from lightning.pytorch import Callback, LightningModule, Trainer
 from lightning.pytorch.callbacks import (
     EarlyStopping,
@@ -32,7 +33,6 @@
 from lightning.pytorch.callbacks.batch_size_finder import BatchSizeFinder
 from lightning.pytorch.demos.boring_classes import BoringModel
 from lightning.pytorch.trainer.connectors.callback_connector import _CallbackConnector
-from lightning.pytorch.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
 
 
 def test_checkpoint_callbacks_are_last(tmpdir):

tests/tests_pytorch/trainer/logging_/test_eval_loop_logging.py

@@ -25,14 +25,14 @@
 import torch
 from torch import Tensor
 
+from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0
 from lightning.pytorch import callbacks, Trainer
 from lightning.pytorch.callbacks.progress.rich_progress import _RICH_AVAILABLE
 from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
 from lightning.pytorch.loggers import TensorBoardLogger
 from lightning.pytorch.loops import _EvaluationLoop
 from lightning.pytorch.trainer.states import RunningStage
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
-from lightning.pytorch.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0
 from tests_pytorch.helpers.runif import RunIf
 
 if _RICH_AVAILABLE: