Move metrics_to_scalars to a dedicated utilities file (#7180)

* rm-trainer-logging

* Update CHANGELOG.md

* Update metrics.py

* Update logging.py

* Update metrics.py

CHANGELOG.md

@@ -12,6 +12,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added a `teardown` hook to `ClusterEnvironment` ([#6942](https://github.com/PyTorchLightning/pytorch-lightning/pull/6942))
 
 
+- Added utils for metrics to scalar conversions ([#7180](https://github.com/PyTorchLightning/pytorch-lightning/pull/7180))
+
+
 - Added utils for NaN/Inf detection for gradients and parameters ([#6834](https://github.com/PyTorchLightning/pytorch-lightning/pull/6834/))
 
 
@@ -146,6 +149,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Deprecated
 
+- Deprecated `TrainerLoggingMixin` in favor of a separate utilities module for metric handling ([#7180](https://github.com/PyTorchLightning/pytorch-lightning/pull/7180))
+
+
 - Deprecated `TrainerTrainingTricksMixin` in favor of a separate utilities module for NaN/Inf detection for gradients and parameters ([#6834](https://github.com/PyTorchLightning/pytorch-lightning/pull/6834/))
 
 

pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py

@@ -26,6 +26,7 @@ from pytorch_lightning.trainer.connectors.logger_connector.epoch_result_store im
 from pytorch_lightning.trainer.connectors.logger_connector.metrics_holder import MetricsHolder
 from pytorch_lightning.trainer.states import RunningStage, TrainerState
 from pytorch_lightning.utilities import DeviceType
+from pytorch_lightning.utilities.metrics import metrics_to_scalars
 
 
 class LoggerConnector:
@@ -210,7 +211,7 @@ class LoggerConnector:
         metrics.update(grad_norm_dic)
 
         # turn all tensors to scalars
-        scalar_metrics = self.trainer.metrics_to_scalars(metrics)
+        scalar_metrics = metrics_to_scalars(metrics)
 
         if "step" in scalar_metrics and step is None:
             step = scalar_metrics.pop("step")

pytorch_lightning/trainer/logging.py

@@ -14,28 +14,21 @@
 
 from abc import ABC
 
-import torch
+from pytorch_lightning.utilities.distributed import rank_zero_deprecation
-
+from pytorch_lightning.utilities.metrics import metrics_to_scalars as new_metrics_to_scalars
-from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
 
 class TrainerLoggingMixin(ABC):
+    """
+    TODO: Remove this class in v1.5.
 
-    def metrics_to_scalars(self, metrics):
+    Use the utilities from ``pytorch_lightning.utilities.metrics`` instead.
-        new_metrics = {}
+    """
-        # TODO: this is duplicated in MetricsHolder. should be unified
-        for k, v in metrics.items():
-            if isinstance(v, torch.Tensor):
-                if v.numel() != 1:
-                    raise MisconfigurationException(
-                        f"The metric `{k}` does not contain a single element"
-                        f" thus it cannot be converted to float. Found `{v}`"
-                    )
-                v = v.item()
 
-            if isinstance(v, dict):
+    def metrics_to_scalars(self, metrics: dict) -> dict:
-                v = self.metrics_to_scalars(v)
+        rank_zero_deprecation(
-
+            "Internal: TrainerLoggingMixin.metrics_to_scalars is deprecated in v1.3"
-            new_metrics[k] = v
+            " and will be removed in v1.5."
-
+            " Use `pytorch_lightning.utilities.metrics.metrics_to_scalars` instead."
-        return new_metrics
+        )
+        return new_metrics_to_scalars(metrics)

pytorch_lightning/utilities/metrics.py

@@ -0,0 +1,40 @@
+# 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.
+"""Helper functions to operate on metric values. """
+
+import torch
+
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
+
+
+def metrics_to_scalars(metrics: dict) -> dict:
+    """ Recursively walk through a dictionary of metrics and convert single-item tensors to scalar values. """
+
+    # TODO: this is duplicated in MetricsHolder. should be unified
+    new_metrics = {}
+    for k, v in metrics.items():
+        if isinstance(v, torch.Tensor):
+            if v.numel() != 1:
+                raise MisconfigurationException(
+                    f"The metric `{k}` does not contain a single element"
+                    f" thus it cannot be converted to float. Found `{v}`"
+                )
+            v = v.item()
+
+        if isinstance(v, dict):
+            v = metrics_to_scalars(v)
+
+        new_metrics[k] = v
+
+    return new_metrics

tests/deprecated_api/test_remove_1-5.py

@@ -242,3 +242,9 @@ def test_v1_5_0_auto_move_data():
             @auto_move_data
             def bar(self):
                 pass
+
+
+def test_v1_5_0_trainer_logging_mixin(tmpdir):
+    trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, checkpoint_callback=False, logger=False)
+    with pytest.deprecated_call(match="is deprecated in v1.3 and will be removed in v1.5"):
+        trainer.metrics_to_scalars({})