Add missing val/test hooks in LightningModule

CHANGELOG.md

@@ -47,6 +47,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `IoU` class interface ([#4704](https://github.com/PyTorchLightning/pytorch-lightning/pull/4704))
 
 
+- Added missing val/test hooks in `LightningModule` ([#5467](https://github.com/PyTorchLightning/pytorch-lightning/pull/5467))
+
+
 ### Changed
 
 - Changed `stat_scores` metric now calculates stat scores over all classes and gains new parameters, in line with the new `StatScores` metric ([#4839](https://github.com/PyTorchLightning/pytorch-lightning/pull/4839))

pytorch_lightning/core/hooks.py

@@ -17,14 +17,15 @@
 from typing import Any, Dict, List, Optional, Union
 
 import torch
-from pytorch_lightning.utilities import move_data_to_device, rank_zero_warn
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader
 
+from pytorch_lightning.utilities import move_data_to_device, rank_zero_warn
+
 
 class ModelHooks:
     """Hooks to be used in LightningModule."""
-    def setup(self, stage: str):
+    def setup(self, stage: str) -> None:
         """
         Called at the beginning of fit and test.
         This is a good hook when you need to build models dynamically or adjust something about them.
@@ -52,29 +53,29 @@ def setup(stage):
 
         """
 
-    def teardown(self, stage: str):
+    def teardown(self, stage: str) -> None:
         """
         Called at the end of fit and test.
 
         Args:
             stage: either 'fit' or 'test'
         """
 
-    def on_fit_start(self):
+    def on_fit_start(self) -> None:
         """
         Called at the very beginning of fit.
         If on DDP it is called on every process
         """
 
-    def on_fit_end(self):
+    def on_fit_end(self) -> None:
         """
         Called at the very end of fit.
         If on DDP it is called on every process
         """
 
     def on_train_start(self) -> None:
         """
-        Called at the beginning of training before sanity check.
+        Called at the beginning of training after sanity check.
         """
         # do something at the start of training
 
@@ -84,6 +85,18 @@ def on_train_end(self) -> None:
         """
         # do something at the end of training
 
+    def on_validation_start(self) -> None:
+        """
+        Called at the beginning of validation.
+        """
+        # do something at the start of validation
+
+    def on_validation_end(self) -> None:
+        """
+        Called at the end of validation.
+        """
+        # do something at the end of validation
+
     def on_pretrain_routine_start(self) -> None:
         """
         Called at the beginning of the pretrain routine (between fit and train start).
@@ -108,9 +121,7 @@ def on_pretrain_routine_end(self) -> None:
         """
         # do something at the end of the pretrain routine
 
-    def on_train_batch_start(
-        self, batch: Any, batch_idx: int, dataloader_idx: int
-    ) -> None:
+    def on_train_batch_start(self, batch: Any, batch_idx: int, dataloader_idx: int) -> None:
         """
         Called in the training loop before anything happens for that batch.
 
@@ -253,6 +264,18 @@ def on_test_epoch_end(self) -> None:
         """
         # do something when the epoch ends
 
+    def on_test_start(self) -> None:
+        """
+        Called at the beginning of testing.
+        """
+        # do something at the start of testing
+
+    def on_test_end(self) -> None:
+        """
+        Called at the end of testing.
+        """
+        # do something at the end of testing
+
     def on_before_zero_grad(self, optimizer: Optimizer) -> None:
         """
         Called after optimizer.step() and before optimizer.zero_grad().

tests/models/test_hooks.py

@@ -12,15 +12,15 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import inspect
+from unittest.mock import MagicMock
 
 import pytest
 import torch
-from unittest.mock import MagicMock
 
 from pytorch_lightning import Trainer
 from pytorch_lightning.accelerators.gpu_accelerator import GPUAccelerator
 from pytorch_lightning.trainer.states import TrainerState
-from tests.base import EvalModelTemplate, BoringModel
+from tests.base import BoringModel, EvalModelTemplate
 
 
 @pytest.mark.parametrize('max_steps', [1, 2, 3])
@@ -254,10 +254,6 @@ def on_test_start(self):
             self.called.append(inspect.currentframe().f_code.co_name)
             super().on_test_start()
 
-        def on_test_end(self):
-            self.called.append(inspect.currentframe().f_code.co_name)
-            super().on_test_end()
-
         def on_test_batch_start(self, batch, batch_idx, dataloader_idx):
             self.called.append(inspect.currentframe().f_code.co_name)
             super().on_test_batch_start(batch, batch_idx, dataloader_idx)
@@ -290,6 +286,14 @@ def on_test_model_train(self):
             self.called.append(inspect.currentframe().f_code.co_name)
             super().on_test_model_train()
 
+        def on_test_end(self):
+            self.called.append(inspect.currentframe().f_code.co_name)
+            super().on_test_end()
+
+        def teardown(self, stage: str):
+            self.called.append(inspect.currentframe().f_code.co_name)
+            super().teardown(stage)
+
     model = HookedModel()
 
     assert model.called == []
@@ -313,10 +317,12 @@ def on_test_model_train(self):
         'on_pretrain_routine_start',
         'on_pretrain_routine_end',
         'on_validation_model_eval',
+        'on_validation_start',
         'on_validation_epoch_start',
         'on_validation_batch_start',
         'on_validation_batch_end',
         'on_validation_epoch_end',
+        'on_validation_end',
         'on_validation_model_train',
         'on_train_start',
         'on_epoch_start',
@@ -330,16 +336,19 @@ def on_test_model_train(self):
         'on_before_zero_grad',
         'on_train_batch_end',
         'on_validation_model_eval',
+        'on_validation_start',
         'on_validation_epoch_start',
         'on_validation_batch_start',
         'on_validation_batch_end',
         'on_validation_epoch_end',
         'on_save_checkpoint',
+        'on_validation_end',
         'on_validation_model_train',
         'on_epoch_end',
         'on_train_epoch_end',
         'on_train_end',
         'on_fit_end',
+        'teardown',
     ]
 
     assert model.called == expected
@@ -352,12 +361,16 @@ def on_test_model_train(self):
         'on_pretrain_routine_start',
         'on_pretrain_routine_end',
         'on_test_model_eval',
+        'on_test_start',
         'on_test_epoch_start',
         'on_test_batch_start',
         'on_test_batch_end',
         'on_test_epoch_end',
+        'on_test_end',
         'on_test_model_train',
         'on_fit_end',
+        'teardown',  # for 'fit'
+        'teardown',  # for 'test'
     ]
 
     assert model2.called == expected