Remove deprecated automatic logging of gpu metrics

CHANGELOG.md

@@ -75,10 +75,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed the deprecated `terminate_on_nan` argument from the `Trainer` constructor ([#12553](https://github.com/PyTorchLightning/pytorch-lightning/pull/12553))
 
 
--
-
+- Removed the deprecated `log_gpu_memory` argument from the `Trainer` constructor ([#12657](https://github.com/PyTorchLightning/pytorch-lightning/pull/12657))
 
 -
+- Removed the deprecated automatic logging of GPU stats by the logger connector ([#12657](https://github.com/PyTorchLightning/pytorch-lightning/pull/12657))
 
 ### Fixed
 

pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py

@@ -11,38 +11,29 @@
 # 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.
-from typing import Any, Dict, Iterable, Optional, Union
+from typing import Any, Iterable, Optional, Union
 
 import torch
 
 import pytorch_lightning as pl
-from pytorch_lightning.accelerators import GPUAccelerator
 from pytorch_lightning.loggers import LightningLoggerBase, TensorBoardLogger
 from pytorch_lightning.plugins.environments.slurm_environment import SLURMEnvironment
 from pytorch_lightning.trainer.connectors.logger_connector.result import _METRICS, _OUT_DICT, _PBAR_DICT
 from pytorch_lightning.trainer.states import RunningStage
-from pytorch_lightning.utilities import memory
 from pytorch_lightning.utilities.apply_func import apply_to_collection, move_data_to_device
 from pytorch_lightning.utilities.metrics import metrics_to_scalars
 from pytorch_lightning.utilities.model_helpers import is_overridden
 from pytorch_lightning.utilities.rank_zero import rank_zero_deprecation
 
 
 class LoggerConnector:
-    def __init__(self, trainer: "pl.Trainer", log_gpu_memory: Optional[str] = None) -> None:
+    def __init__(self, trainer: "pl.Trainer") -> None:
         self.trainer = trainer
-        if log_gpu_memory is not None:
-            rank_zero_deprecation(
-                "Setting `log_gpu_memory` with the trainer flag is deprecated in v1.5 and will be removed in v1.7. "
-                "Please monitor GPU stats with the `DeviceStatsMonitor` callback directly instead."
-            )
-        self.log_gpu_memory = log_gpu_memory
         self._val_log_step: int = 0
         self._test_log_step: int = 0
         self._progress_bar_metrics: _PBAR_DICT = {}
         self._logged_metrics: _OUT_DICT = {}
         self._callback_metrics: _OUT_DICT = {}
-        self._gpus_metrics: Dict[str, float] = {}
         self._epoch_end_reached = False
         self._current_fx: Optional[str] = None
         self._batch_idx: Optional[int] = None
@@ -193,9 +184,6 @@ def update_train_step_metrics(self) -> None:
         if self.trainer.fit_loop._should_accumulate() and self.trainer.lightning_module.automatic_optimization:
             return
 
-        # TODO: remove this call in v1.7
-        self._log_gpus_metrics()
-
         # when metrics should be logged
         assert not self._epoch_end_reached
         if self.should_update_logs or self.trainer.fast_dev_run:
@@ -210,22 +198,6 @@ def update_train_epoch_metrics(self) -> None:
         assert self.trainer._results is not None
         self.trainer._results.reset(metrics=True)
 
-    def _log_gpus_metrics(self) -> None:
-        """
-        .. deprecated:: v1.5
-            This function was deprecated in v1.5 in favor of
-            `pytorch_lightning.accelerators.gpu._get_nvidia_gpu_stats` and will be removed in v1.7.
-        """
-        for key, mem in self.gpus_metrics.items():
-            if self.log_gpu_memory == "min_max":
-                self.trainer.lightning_module.log(key, mem, prog_bar=False, logger=True)
-            else:
-                gpu_id = int(key.split("/")[0].split(":")[1])
-                if gpu_id in self.trainer.device_ids:
-                    self.trainer.lightning_module.log(
-                        key, mem, prog_bar=False, logger=True, on_step=True, on_epoch=False
-                    )
-
     """
     Utilities and properties
     """
@@ -298,17 +270,6 @@ def metrics(self) -> _METRICS:
         assert self.trainer._results is not None
         return self.trainer._results.metrics(on_step)
 
-    @property
-    def gpus_metrics(self) -> Dict[str, float]:
-        """
-        .. deprecated:: v1.5
-            Will be removed in v1.7.
-        """
-        if isinstance(self.trainer.accelerator, GPUAccelerator) and self.log_gpu_memory:
-            mem_map = memory.get_memory_profile(self.log_gpu_memory)
-            self._gpus_metrics.update(mem_map)
-        return self._gpus_metrics
-
     @property
     def callback_metrics(self) -> _OUT_DICT:
         if self.trainer._results:

pytorch_lightning/trainer/trainer.py

@@ -145,7 +145,6 @@ def __init__(
         auto_select_gpus: bool = False,
         tpu_cores: Optional[Union[List[int], str, int]] = None,
         ipus: Optional[int] = None,
-        log_gpu_memory: Optional[str] = None,  # TODO: Remove in 1.7
         enable_progress_bar: bool = True,
         overfit_batches: Union[int, float] = 0.0,
         track_grad_norm: Union[int, float, str] = -1,
@@ -303,12 +302,6 @@ def __init__(
                 of the individual loggers.
                 Default: ``True``.
 
-            log_gpu_memory: None, 'min_max', 'all'. Might slow performance.
-
-                .. deprecated:: v1.5
-                    Deprecated in v1.5.0 and will be removed in v1.7.0
-                    Please use the ``DeviceStatsMonitor`` callback directly instead.
-
             log_every_n_steps: How often to log within steps.
                 Default: ``50``.
 
@@ -461,7 +454,7 @@ def __init__(
             amp_level=amp_level,
             plugins=plugins,
         )
-        self._logger_connector = LoggerConnector(self, log_gpu_memory)
+        self._logger_connector = LoggerConnector(self)
         self._callback_connector = CallbackConnector(self)
         self._checkpoint_connector = CheckpointConnector(self, resume_from_checkpoint)
         self._signal_connector = SignalConnector(self)

tests/deprecated_api/test_remove_1-7.py

@@ -337,13 +337,6 @@ def test_v1_7_0_weights_summary_trainer(tmpdir):
         t.weights_summary = "blah"
 
 
-def test_v1_7_0_trainer_log_gpu_memory(tmpdir):
-    with pytest.deprecated_call(
-        match="Setting `log_gpu_memory` with the trainer flag is deprecated in v1.5 and will be removed"
-    ):
-        _ = Trainer(log_gpu_memory="min_max")
-
-
 def test_v1_7_0_deprecated_slurm_job_id():
     trainer = Trainer()
     with pytest.deprecated_call(match="Method `slurm_job_id` is deprecated in v1.6.0 and will be removed in v1.7.0."):