Deprecate `AbstractProfiler` in favor of `BaseProfiler` (#12106)

CHANGELOG.md

@@ -454,6 +454,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated passing `weights_save_path` to the `Trainer` constructor in favor of adding the `ModelCheckpoint` callback with `dirpath` directly to the list of callbacks ([#12084](https://github.com/PyTorchLightning/pytorch-lightning/pull/12084))
 
 
+- Deprecated `pytorch_lightning.profiler.AbstractProfiler` in favor of `pytorch_lightning.profiler.BaseProfiler` ([#12106](https://github.com/PyTorchLightning/pytorch-lightning/pull/12106))
+
+
 - Deprecated `BaseProfiler.profile_iterable` ([#12102](https://github.com/PyTorchLightning/pytorch-lightning/pull/12102))
 
 

pytorch_lightning/profiler/base.py

@@ -26,7 +26,14 @@ log = logging.getLogger(__name__)
 
 
 class AbstractProfiler(ABC):
-    """Specification of a profiler."""
+    """Specification of a profiler.
+
+    See deprecation warning below
+
+    .. deprecated:: v1.6
+        `AbstractProfiler` was deprecated in v1.6 and will be removed in v1.8.
+        Please use `BaseProfiler` instead
+    """
 
     @abstractmethod
     def start(self, action_name: str) -> None:
@@ -49,7 +56,7 @@ class AbstractProfiler(ABC):
         """Execute arbitrary post-profiling tear-down steps as defined by subclass."""
 
 
-class BaseProfiler(AbstractProfiler):
+class BaseProfiler(ABC):
     """If you wish to write a custom profiler, you should inherit from this class."""
 
     def __init__(
@@ -65,6 +72,17 @@ class BaseProfiler(AbstractProfiler):
         self._local_rank: Optional[int] = None
         self._stage: Optional[str] = None
 
+    @abstractmethod
+    def start(self, action_name: str) -> None:
+        """Defines how to start recording an action."""
+
+    @abstractmethod
+    def stop(self, action_name: str) -> None:
+        """Defines how to record the duration once an action is complete."""
+
+    def summary(self) -> str:
+        return ""
+
     @contextmanager
     def profile(self, action_name: str) -> Generator:
         """Yields a context manager to encapsulate the scope of a profiled action.
@@ -180,15 +198,6 @@ class BaseProfiler(AbstractProfiler):
     def __del__(self) -> None:
         self.teardown(stage=self._stage)
 
-    def start(self, action_name: str) -> None:
-        raise NotImplementedError
-
-    def stop(self, action_name: str) -> None:
-        raise NotImplementedError
-
-    def summary(self) -> str:
-        raise NotImplementedError
-
     @property
     def local_rank(self) -> int:
         return 0 if self._local_rank is None else self._local_rank
@@ -205,6 +214,3 @@ class PassThroughProfiler(BaseProfiler):
 
     def stop(self, action_name: str) -> None:
         pass
-
-    def summary(self) -> str:
-        return ""

pytorch_lightning/profiler/xla.py

@@ -78,6 +78,3 @@ class XLAProfiler(BaseProfiler):
         else:
             self._step_recoding_map[action_name] += 1
         return self._step_recoding_map[action_name]
-
-    def summary(self) -> str:
-        return ""

tests/deprecated_api/test_remove_1-8.py

@@ -35,7 +35,7 @@ from pytorch_lightning.plugins.training_type.sharded_spawn import DDPSpawnSharde
 from pytorch_lightning.plugins.training_type.single_device import SingleDevicePlugin
 from pytorch_lightning.plugins.training_type.single_tpu import SingleTPUPlugin
 from pytorch_lightning.plugins.training_type.tpu_spawn import TPUSpawnPlugin
-from pytorch_lightning.profiler import AdvancedProfiler, SimpleProfiler
+from pytorch_lightning.profiler import AbstractProfiler, AdvancedProfiler, SimpleProfiler
 from pytorch_lightning.trainer.states import RunningStage
 from pytorch_lightning.utilities.apply_func import move_data_to_device
 from pytorch_lightning.utilities.enums import DeviceType, DistributedType
@@ -705,3 +705,7 @@ def test_v1_8_0_precision_plugin_checkpoint_hooks(tmpdir):
         " v1.6 and will be removed in v1.8. Use `load_state_dict` instead."
     ):
         trainer.fit(model)
+
+
+def test_v1_8_0_abstract_profiler():
+    assert "`AbstractProfiler` was deprecated in v1.6" in AbstractProfiler.__doc__