Centralize rank_zero_only utilities into their own module

Fixes Lightning-AI#11746

pytorch_lightning/utilities/distributed.py

@@ -15,8 +15,6 @@
 
 import logging
 import os
-from functools import wraps
-from platform import python_version
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 import torch
@@ -25,6 +23,7 @@
 
 import pytorch_lightning as pl
 from pytorch_lightning.utilities.imports import _TORCH_GREATER_EQUAL_1_8, _TORCH_GREATER_EQUAL_1_9, _TPU_AVAILABLE
+from pytorch_lightning.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only  # noqa: F401
 
 if _TPU_AVAILABLE:
     import torch_xla.core.xla_model as xm
@@ -44,56 +43,6 @@ class group:  # type: ignore
 log = logging.getLogger(__name__)
 
 
-def rank_zero_only(fn: Callable) -> Callable:
-    """Function that can be used as a decorator to enable a function/method being called only on rank 0."""
-
-    @wraps(fn)
-    def wrapped_fn(*args: Any, **kwargs: Any) -> Optional[Any]:
-        if rank_zero_only.rank == 0:
-            return fn(*args, **kwargs)
-        return None
-
-    return wrapped_fn
-
-
-# TODO: this should be part of the cluster environment
-def _get_rank() -> int:
-    rank_keys = ("RANK", "SLURM_PROCID", "LOCAL_RANK")
-    for key in rank_keys:
-        rank = os.environ.get(key)
-        if rank is not None:
-            return int(rank)
-    return 0
-
-
-# add the attribute to the function but don't overwrite in case Trainer has already set it
-rank_zero_only.rank = getattr(rank_zero_only, "rank", _get_rank())
-
-
-def _info(*args: Any, stacklevel: int = 2, **kwargs: Any) -> None:
-    if python_version() >= "3.8.0":
-        kwargs["stacklevel"] = stacklevel
-    log.info(*args, **kwargs)
-
-
-def _debug(*args: Any, stacklevel: int = 2, **kwargs: Any) -> None:
-    if python_version() >= "3.8.0":
-        kwargs["stacklevel"] = stacklevel
-    log.debug(*args, **kwargs)
-
-
-@rank_zero_only
-def rank_zero_debug(*args: Any, stacklevel: int = 4, **kwargs: Any) -> None:
-    """Function used to log debug-level messages only on rank 0."""
-    _debug(*args, stacklevel=stacklevel, **kwargs)
-
-
-@rank_zero_only
-def rank_zero_info(*args: Any, stacklevel: int = 4, **kwargs: Any) -> None:
-    """Function used to log info-level messages only on rank 0."""
-    _info(*args, stacklevel=stacklevel, **kwargs)
-
-
 def gather_all_tensors(result: torch.Tensor, group: Optional[Any] = None) -> List[torch.Tensor]:
     """Function to gather all tensors from several ddp processes onto a list that is broadcasted to all processes.
 

pytorch_lightning/utilities/rank_zero.py

@@ -0,0 +1,101 @@
+# Copyright The PyTorch Lightning team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Utilities that can be used for calling functions on a particular rank."""
+import logging
+import os
+import warnings
+from functools import partial, wraps
+from platform import python_version
+from typing import Any, Callable, Optional, Union
+
+log = logging.getLogger(__name__)
+
+
+def rank_zero_only(fn: Callable) -> Callable:
+    """Function that can be used as a decorator to enable a function/method being called only on rank 0."""
+
+    @wraps(fn)
+    def wrapped_fn(*args: Any, **kwargs: Any) -> Optional[Any]:
+        if rank_zero_only.rank == 0:
+            return fn(*args, **kwargs)
+        return None
+
+    return wrapped_fn
+
+
+# TODO: this should be part of the cluster environment
+def _get_rank() -> int:
+    rank_keys = ("RANK", "SLURM_PROCID", "LOCAL_RANK")
+    for key in rank_keys:
+        rank = os.environ.get(key)
+        if rank is not None:
+            return int(rank)
+    return 0
+
+
+# add the attribute to the function but don't overwrite in case Trainer has already set it
+rank_zero_only.rank = getattr(rank_zero_only, "rank", _get_rank())
+
+
+def _info(*args: Any, stacklevel: int = 2, **kwargs: Any) -> None:
+    if python_version() >= "3.8.0":
+        kwargs["stacklevel"] = stacklevel
+    log.info(*args, **kwargs)
+
+
+def _debug(*args: Any, stacklevel: int = 2, **kwargs: Any) -> None:
+    if python_version() >= "3.8.0":
+        kwargs["stacklevel"] = stacklevel
+    log.debug(*args, **kwargs)
+
+
+@rank_zero_only
+def rank_zero_debug(*args: Any, stacklevel: int = 4, **kwargs: Any) -> None:
+    """Function used to log debug-level messages only on rank 0."""
+    _debug(*args, stacklevel=stacklevel, **kwargs)
+
+
+@rank_zero_only
+def rank_zero_info(*args: Any, stacklevel: int = 4, **kwargs: Any) -> None:
+    """Function used to log info-level messages only on rank 0."""
+    _info(*args, stacklevel=stacklevel, **kwargs)
+
+
+def _warn(message: Union[str, Warning], stacklevel: int = 2, **kwargs: Any) -> None:
+    if type(stacklevel) is type and issubclass(stacklevel, Warning):
+        rank_zero_deprecation(
+            "Support for passing the warning category positionally is deprecated in v1.6 and will be removed in v1.8"
+            f" Please, use `category={stacklevel.__name__}`."
+        )
+        kwargs["category"] = stacklevel
+        stacklevel = kwargs.pop("stacklevel", 2)
+    warnings.warn(message, stacklevel=stacklevel, **kwargs)
+
+
+@rank_zero_only
+def rank_zero_warn(message: Union[str, Warning], stacklevel: int = 4, **kwargs: Any) -> None:
+    """Function used to log warn-level messages only on rank 0."""
+    _warn(message, stacklevel=stacklevel, **kwargs)
+
+
+class PossibleUserWarning(UserWarning):
+    """Warnings that could be false positives."""
+
+
+class LightningDeprecationWarning(DeprecationWarning):
+    """Deprecation warnings raised by PyTorch Lightning."""
+
+
+rank_zero_deprecation = partial(rank_zero_warn, category=LightningDeprecationWarning)

pytorch_lightning/utilities/warnings.py

@@ -14,42 +14,18 @@
 """Warning-related utilities."""
 
 import warnings
-from functools import partial
-from typing import Any, Union
-
-from pytorch_lightning.utilities.distributed import rank_zero_only
-
-
-def _warn(message: Union[str, Warning], stacklevel: int = 2, **kwargs: Any) -> None:
-    if type(stacklevel) is type and issubclass(stacklevel, Warning):
-        rank_zero_deprecation(
-            "Support for passing the warning category positionally is deprecated in v1.6 and will be removed in v1.8"
-            f" Please, use `category={stacklevel.__name__}`."
-        )
-        kwargs["category"] = stacklevel
-        stacklevel = kwargs.pop("stacklevel", 2)
-    warnings.warn(message, stacklevel=stacklevel, **kwargs)
-
-
-@rank_zero_only
-def rank_zero_warn(message: Union[str, Warning], stacklevel: int = 4, **kwargs: Any) -> None:
-    """Function used to log warn-level messages only on rank 0."""
-    _warn(message, stacklevel=stacklevel, **kwargs)
-
-
-class PossibleUserWarning(UserWarning):
-    """Warnings that could be false positives."""
-
-
-class LightningDeprecationWarning(DeprecationWarning):
-    """Deprecation warnings raised by PyTorch Lightning."""
+from typing import Any
 
+from pytorch_lightning.utilities.rank_zero import (  # noqa: F401
+    LightningDeprecationWarning,
+    rank_zero_deprecation,
+    rank_zero_only,
+    rank_zero_warn,
+)
 
 # enable our warnings
 warnings.simplefilter("default", category=LightningDeprecationWarning)
 
-rank_zero_deprecation = partial(rank_zero_warn, category=LightningDeprecationWarning)
-
 
 class WarningCache(set):
     def warn(self, message: str, stacklevel: int = 5, **kwargs: Any) -> None: