Remove deprecated DistributedType and DeviceType enum classes

src/pytorch_lightning/CHANGELOG.md

@@ -27,7 +27,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `amp_level` from `Trainer` in favour of passing it explictly via precision plugin ([#13898](https://github.com/Lightning-AI/lightning/pull/13898))
 
 
--
+- Deprecated the calls to `pytorch_lightning.utiltiies.meta` functions in favor of built-in https://github.com/pytorch/torchdistx support ([#13868](https://github.com/Lightning-AI/lightning/pull/13868))
 
 
 ### Removed
@@ -41,6 +41,12 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed the deprecated `DDP2Strategy` ([#14026](https://github.com/Lightning-AI/lightning/pull/14026))
 
 
+- Removed the deprecated `DistributedType` and `DeviceType` enum classes ([#14045](https://github.com/Lightning-AI/lightning/pull/14045))
+
+
+- Removed the experimental `pytorch_lightning.utiltiies.meta` functions in favor of built-in https://github.com/pytorch/torchdistx support ([#13868](https://github.com/Lightning-AI/lightning/pull/13868))
+
+
 ### Fixed
 
 - Casted only floating point tensors to fp16 with IPUs ([#13983](https://github.com/Lightning-AI/lightning/pull/13983))

src/pytorch_lightning/utilities/__init__.py

@@ -21,7 +21,6 @@
     _AcceleratorType,
     _StrategyType,
     AMPType,
-    DistributedType,
     GradClipAlgorithmType,
     LightningEnum,
 )

src/pytorch_lightning/utilities/enums.py

@@ -15,11 +15,9 @@
 from __future__ import annotations
 
 import os
-from enum import Enum, EnumMeta
-from typing import Any
+from enum import Enum
 
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
-from pytorch_lightning.utilities.warnings import rank_zero_deprecation
 
 
 class LightningEnum(str, Enum):
@@ -43,37 +41,6 @@ def __hash__(self) -> int:
         return hash(self.value.lower())
 
 
-class _DeprecatedEnumMeta(EnumMeta):
-    """Enum that calls `deprecate()` whenever a member is accessed.
-
-    Adapted from: https://stackoverflow.com/a/62309159/208880
-    """
-
-    def __getattribute__(cls, name: str) -> Any:
-        obj = super().__getattribute__(name)
-        # ignore __dunder__ names -- prevents potential recursion errors
-        if not (name.startswith("__") and name.endswith("__")) and isinstance(obj, Enum):
-            obj.deprecate()
-        return obj
-
-    def __getitem__(cls, name: str) -> Any:
-        member: _DeprecatedEnumMeta = super().__getitem__(name)
-        member.deprecate()
-        return member
-
-    def __call__(cls, *args: Any, **kwargs: Any) -> Any:
-        obj = super().__call__(*args, **kwargs)
-        if isinstance(obj, Enum):
-            obj.deprecate()
-        return obj
-
-
-class _DeprecatedEnum(LightningEnum, metaclass=_DeprecatedEnumMeta):
-    """_DeprecatedEnum calls an enum's `deprecate()` method on member access."""
-
-    pass
-
-
 class AMPType(LightningEnum):
     """Type of Automatic Mixed Precission used for training.
 
@@ -110,66 +77,6 @@ def supported_types() -> list[str]:
         return [x.value for x in PrecisionType]
 
 
-class DistributedType(_DeprecatedEnum):
-    """Define type of training strategy.
-
-    Deprecated since v1.6.0 and will be removed in v1.8.0.
-
-    Use `_StrategyType` instead.
-    """
-
-    DP = "dp"
-    DDP = "ddp"
-    DDP_SPAWN = "ddp_spawn"
-    TPU_SPAWN = "tpu_spawn"
-    DEEPSPEED = "deepspeed"
-    HOROVOD = "horovod"
-    DDP_SHARDED = "ddp_sharded"
-    DDP_SHARDED_SPAWN = "ddp_sharded_spawn"
-    DDP_FULLY_SHARDED = "ddp_fully_sharded"
-    HPU_PARALLEL = "hpu_parallel"
-
-    @staticmethod
-    def interactive_compatible_types() -> list[DistributedType]:
-        """Returns a list containing interactive compatible DistributeTypes."""
-        return [
-            DistributedType.DP,
-            DistributedType.DDP_SPAWN,
-            DistributedType.DDP_SHARDED_SPAWN,
-            DistributedType.TPU_SPAWN,
-        ]
-
-    def is_interactive_compatible(self) -> bool:
-        """Returns whether self is interactive compatible."""
-        return self in DistributedType.interactive_compatible_types()
-
-    def deprecate(self) -> None:
-        rank_zero_deprecation(
-            "`DistributedType` Enum has been deprecated in v1.6 and will be removed in v1.8."
-            f" Use the string value `{self.value!r}` instead."
-        )
-
-
-class DeviceType(_DeprecatedEnum):
-    """Define Device type by its nature - accelerators.
-
-    Deprecated since v1.6.0 and will be removed in v1.8.0.
-
-    Use `_AcceleratorType` instead.
-    """
-
-    CPU = "CPU"
-    GPU = "GPU"
-    IPU = "IPU"
-    TPU = "TPU"
-
-    def deprecate(self) -> None:
-        rank_zero_deprecation(
-            "`DeviceType` Enum has been deprecated in v1.6 and will be removed in v1.8."
-            f" Use the string value `{self.value!r}` instead."
-        )
-
-
 class GradClipAlgorithmType(LightningEnum):
     """Define gradient_clip_algorithm types - training-tricks.
     NORM type means "clipping gradients by norm". This computed over all model parameters together.

tests/tests_pytorch/deprecated_api/test_remove_1-8.py

@@ -36,26 +36,13 @@
 from pytorch_lightning.trainer.states import RunningStage
 from pytorch_lightning.utilities import device_parser
 from pytorch_lightning.utilities.apply_func import move_data_to_device
-from pytorch_lightning.utilities.enums import DeviceType, DistributedType
 from pytorch_lightning.utilities.imports import _TORCHTEXT_LEGACY
 from pytorch_lightning.utilities.rank_zero import rank_zero_only, rank_zero_warn
 from tests_pytorch.deprecated_api import no_deprecated_call
 from tests_pytorch.helpers.runif import RunIf
 from tests_pytorch.helpers.torchtext_utils import get_dummy_torchtext_data_iterator
 
 
-def test_v1_8_0_deprecated_distributed_type_enum():
-
-    with pytest.deprecated_call(match="has been deprecated in v1.6 and will be removed in v1.8."):
-        _ = DistributedType.DDP
-
-
-def test_v1_8_0_deprecated_device_type_enum():
-
-    with pytest.deprecated_call(match="has been deprecated in v1.6 and will be removed in v1.8."):
-        _ = DeviceType.CPU
-
-
 @pytest.mark.skipif(not _TORCHTEXT_LEGACY, reason="torchtext.legacy is deprecated.")
 def test_v1_8_0_deprecated_torchtext_batch():