Refactor: drop LoggerStages

CHANGELOG.md

@@ -9,25 +9,25 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Added
 
-- Add support for summarized model total params size in megabytes ([#5590](https://github.com/PyTorchLightning/pytorch-lightning/pull/5590))
+- Added support for summarized model total params size in megabytes ([#5590](https://github.com/PyTorchLightning/pytorch-lightning/pull/5590))
 
 
-- Add Support for multiple train loaders ([#1959](https://github.com/PyTorchLightning/pytorch-lightning/pull/1959))
+- Added support for multiple train loaders ([#1959](https://github.com/PyTorchLightning/pytorch-lightning/pull/1959))
 
 
-- `Accuracy` metric now generalizes to Top-k accuracy for (multi-dimensional) multi-class inputs using the `top_k` parameter ([#4838](https://github.com/PyTorchLightning/pytorch-lightning/pull/4838))
+- Added `Accuracy` metric now generalizes to Top-k accuracy for (multi-dimensional) multi-class inputs using the `top_k` parameter ([#4838](https://github.com/PyTorchLightning/pytorch-lightning/pull/4838))
 
 
-- `Accuracy` metric now enables the computation of subset accuracy for multi-label or multi-dimensional multi-class inputs with the `subset_accuracy` parameter ([#4838](https://github.com/PyTorchLightning/pytorch-lightning/pull/4838))
+- Added `Accuracy` metric now enables the computation of subset accuracy for multi-label or multi-dimensional multi-class inputs with the `subset_accuracy` parameter ([#4838](https://github.com/PyTorchLightning/pytorch-lightning/pull/4838))
 
 
-- `HammingDistance` metric to compute the hamming distance (loss) ([#4838](https://github.com/PyTorchLightning/pytorch-lightning/pull/4838))
+- Added `HammingDistance` metric to compute the hamming distance (loss) ([#4838](https://github.com/PyTorchLightning/pytorch-lightning/pull/4838))
 
 
 - Added `max_fpr` parameter to `auroc` metric for computing partial auroc metric ([#3790](https://github.com/PyTorchLightning/pytorch-lightning/pull/3790))
 
 
-- `StatScores` metric to compute the number of true positives, false positives, true negatives and false negatives ([#4839](https://github.com/PyTorchLightning/pytorch-lightning/pull/4839))
+- Added `StatScores` metric to compute the number of true positives, false positives, true negatives and false negatives ([#4839](https://github.com/PyTorchLightning/pytorch-lightning/pull/4839))
 
 
 - Added `R2Score` metric ([#5241](https://github.com/PyTorchLightning/pytorch-lightning/pull/5241))
@@ -109,7 +109,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Deprecated
 
-- `stat_scores_multiple_classes` is deprecated in favor of `stat_scores` ([#4839](https://github.com/PyTorchLightning/pytorch-lightning/pull/4839))
+- Function `stat_scores_multiple_classes` is deprecated in favor of `stat_scores` ([#4839](https://github.com/PyTorchLightning/pytorch-lightning/pull/4839))
 
 
 - Moved accelerators and plugins to its `legacy` pkg ([#5645](https://github.com/PyTorchLightning/pytorch-lightning/pull/5645))
@@ -129,6 +129,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed deprecated `EvalResult` ([#5633](https://github.com/PyTorchLightning/pytorch-lightning/pull/5633))
 
 
+- Removed `LoggerStages` ([#5673](https://github.com/PyTorchLightning/pytorch-lightning/pull/5673))
+
+
 ### Fixed
 
 - Fixed distributed setting and `ddp_cpu` only with `num_processes>1` ([#5297](https://github.com/PyTorchLightning/pytorch-lightning/pull/5297))
@@ -145,6 +148,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Fixed loading yaml ([#5619](https://github.com/PyTorchLightning/pytorch-lightning/pull/5619))
 
+
+
 ## [1.1.4] - YYYY-MM-DD
 
 ### Added

pytorch_lightning/trainer/connectors/logger_connector/epoch_result_store.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 from collections import defaultdict
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, Dict, List, Optional
 
 import torch
 
@@ -21,26 +21,6 @@
 from pytorch_lightning.utilities import DistributedType, LightningEnum
 
 
-class LoggerStages(LightningEnum):
-    """ Train/validation/test phase in each training step.
-    >>> # you can math the type with string
-    >>> LoggerStages.TRAIN == 'train'
-    True
-    """
-    TRAIN = "train"
-    VAL = "validation"
-    TEST = "test"
-
-    @staticmethod
-    def determine_stage(stage_or_testing: Union[str, bool]) -> 'LoggerStages':
-        if isinstance(stage_or_testing, str) and stage_or_testing in list(LoggerStages):
-            return LoggerStages(stage_or_testing)
-        if isinstance(stage_or_testing, (bool, int)):
-            # stage_or_testing is trainer.testing
-            return LoggerStages.TEST if bool(stage_or_testing) else LoggerStages.VAL
-        raise RuntimeError(f"Invalid stage {stage_or_testing} of type {type(stage_or_testing)} given")
-
-
 class ResultStoreType(LightningEnum):
     INSIDE_BATCH_TRAIN_LOOP = "inside_batch_train_loop"
     OUTSIDE_BATCH_TRAIN_LOOP = "outside_batch_train_loop"