split tests for deprecated api (#5071)

* imports

* imports

* flake8

Co-authored-by: Rohit Gupta <[email protected]>

Author: Borda

tests/deprecated_api/__init__.py

@@ -0,0 +1,21 @@
+# 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.
+"""Test deprecated functionality which will be removed in vX.Y.Z"""
+import sys
+
+
+def _soft_unimport_module(str_module):
+    # once the module is imported  e.g with parsing with pytest it lives in memory
+    if str_module in sys.modules:
+        del sys.modules[str_module]

tests/deprecated_api/test_remove_1-2.py

@@ -0,0 +1,45 @@
+# 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.
+"""Test deprecated functionality which will be removed in vX.Y.Z"""
+
+import pytest
+import torch
+
+from pytorch_lightning.callbacks import ModelCheckpoint
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
+
+
+def test_tbd_remove_in_v1_2_0():
+    with pytest.deprecated_call(match='will be removed in v1.2'):
+        ModelCheckpoint(filepath='..')
+
+    with pytest.deprecated_call(match='will be removed in v1.2'):
+        ModelCheckpoint('..')
+
+    with pytest.raises(MisconfigurationException, match='inputs which are not feasible'):
+        ModelCheckpoint(filepath='..', dirpath='.')
+
+
+def test_tbd_remove_in_v1_2_0_metrics():
+    from pytorch_lightning.metrics.classification import Fbeta
+    from pytorch_lightning.metrics.functional.classification import f1_score, fbeta_score
+
+    with pytest.deprecated_call(match='will be removed in v1.2'):
+        Fbeta(2)
+
+    with pytest.deprecated_call(match='will be removed in v1.2'):
+        fbeta_score(torch.tensor([0, 1, 2, 3]), torch.tensor([0, 1, 2, 1]), 0.2)
+
+    with pytest.deprecated_call(match='will be removed in v1.2'):
+        f1_score(torch.tensor([0, 1, 0, 1]), torch.tensor([0, 1, 0, 0]))

tests/test_deprecated.py renamed to tests/deprecated_api/test_remove_1-3.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Test deprecated functionality which will be removed in vX.Y.Z"""
-import sys
 from argparse import ArgumentParser
 from unittest import mock
 
@@ -21,10 +20,8 @@
 
 from pytorch_lightning import LightningModule, Trainer
 from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
-from pytorch_lightning.metrics.functional.classification import auc
 from pytorch_lightning.profiler.profilers import PassThroughProfiler, SimpleProfiler
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
-from tests.base import EvalModelTemplate
 
 
 def test_tbd_remove_in_v1_3_0(tmpdir):
@@ -52,27 +49,27 @@ def __init__(self, hparams):
 
 
 def test_tbd_remove_in_v1_3_0_metrics():
+    from pytorch_lightning.metrics.functional.classification import to_onehot
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import to_onehot
         to_onehot(torch.tensor([1, 2, 3]))
 
+    from pytorch_lightning.metrics.functional.classification import to_categorical
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import to_categorical
         to_categorical(torch.tensor([[0.2, 0.5], [0.9, 0.1]]))
 
+    from pytorch_lightning.metrics.functional.classification import get_num_classes
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import get_num_classes
         get_num_classes(pred=torch.tensor([0, 1]), target=torch.tensor([1, 1]))
 
     x_binary = torch.tensor([0, 1, 2, 3])
     y_binary = torch.tensor([0, 1, 2, 3])
 
+    from pytorch_lightning.metrics.functional.classification import roc
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import roc
         roc(pred=x_binary, target=y_binary)
 
+    from pytorch_lightning.metrics.functional.classification import _roc
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import _roc
         _roc(pred=x_binary, target=y_binary)
 
     x_multy = torch.tensor([[0.85, 0.05, 0.05, 0.05],
@@ -81,64 +78,40 @@ def test_tbd_remove_in_v1_3_0_metrics():
                             [0.05, 0.05, 0.05, 0.85]])
     y_multy = torch.tensor([0, 1, 3, 2])
 
+    from pytorch_lightning.metrics.functional.classification import multiclass_roc
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import multiclass_roc
         multiclass_roc(pred=x_multy, target=y_multy)
 
+    from pytorch_lightning.metrics.functional.classification import average_precision
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import average_precision
         average_precision(pred=x_binary, target=y_binary)
 
+    from pytorch_lightning.metrics.functional.classification import precision_recall_curve
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import precision_recall_curve
         precision_recall_curve(pred=x_binary, target=y_binary)
 
+    from pytorch_lightning.metrics.functional.classification import multiclass_precision_recall_curve
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.classification import multiclass_precision_recall_curve
         multiclass_precision_recall_curve(pred=x_multy, target=y_multy)
 
+    from pytorch_lightning.metrics.functional.reduction import reduce
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.reduction import reduce
         reduce(torch.tensor([0, 1, 1, 0]), 'sum')
 
+    from pytorch_lightning.metrics.functional.reduction import class_reduce
     with pytest.deprecated_call(match='will be removed in v1.3'):
-        from pytorch_lightning.metrics.functional.reduction import class_reduce
         class_reduce(torch.randint(1, 10, (50,)).float(),
                      torch.randint(10, 20, (50,)).float(),
                      torch.randint(1, 100, (50,)).float())
 
 
-def test_tbd_remove_in_v1_2_0():
-    with pytest.deprecated_call(match='will be removed in v1.2'):
-        checkpoint_cb = ModelCheckpoint(filepath='.')
-
-    with pytest.deprecated_call(match='will be removed in v1.2'):
-        checkpoint_cb = ModelCheckpoint('.')
-
-    with pytest.raises(MisconfigurationException, match='inputs which are not feasible'):
-        checkpoint_cb = ModelCheckpoint(filepath='.', dirpath='.')
-
-
-def test_tbd_remove_in_v1_2_0_metrics():
-    from pytorch_lightning.metrics.classification import Fbeta
-    from pytorch_lightning.metrics.functional.classification import f1_score, fbeta_score
-
-    with pytest.deprecated_call(match='will be removed in v1.2'):
-        Fbeta(2)
-
-    with pytest.deprecated_call(match='will be removed in v1.2'):
-        fbeta_score(torch.tensor([0, 1, 2, 3]), torch.tensor([0, 1, 2, 1]), 0.2)
-
-    with pytest.deprecated_call(match='will be removed in v1.2'):
-        f1_score(torch.tensor([0, 1, 0, 1]), torch.tensor([0, 1, 0, 0]))
-
-
 # TODO: remove bool from Trainer.profiler param in v1.3.0, update profiler_connector.py
 @pytest.mark.parametrize(['profiler', 'expected'], [
     (True, SimpleProfiler),
     (False, PassThroughProfiler),
 ])
 def test_trainer_profiler_remove_in_v1_3_0(profiler, expected):
+    # remove bool from Trainer.profiler param in v1.3.0, update profiler_connector.py
     with pytest.deprecated_call(match='will be removed in v1.3'):
         trainer = Trainer(profiler=profiler)
         assert isinstance(trainer.profiler, expected)
@@ -162,47 +135,3 @@ def test_trainer_cli_profiler_remove_in_v1_3_0(cli_args, expected_parsed_arg, ex
     assert getattr(args, "profiler") == expected_parsed_arg
     trainer = Trainer.from_argparse_args(args)
     assert isinstance(trainer.profiler, expected_profiler)
-
-
-def _soft_unimport_module(str_module):
-    # once the module is imported  e.g with parsing with pytest it lives in memory
-    if str_module in sys.modules:
-        del sys.modules[str_module]
-
-
-class ModelVer0_6(EvalModelTemplate):
-
-    # todo: this shall not be needed while evaluate asks for dataloader explicitly
-    def val_dataloader(self):
-        return self.dataloader(train=False)
-
-    def validation_step(self, batch, batch_idx, *args, **kwargs):
-        return {'val_loss': torch.tensor(0.6)}
-
-    def validation_end(self, outputs):
-        return {'val_loss': torch.tensor(0.6)}
-
-    def test_dataloader(self):
-        return self.dataloader(train=False)
-
-    def test_end(self, outputs):
-        return {'test_loss': torch.tensor(0.6)}
-
-
-class ModelVer0_7(EvalModelTemplate):
-
-    # todo: this shall not be needed while evaluate asks for dataloader explicitly
-    def val_dataloader(self):
-        return self.dataloader(train=False)
-
-    def validation_step(self, batch, batch_idx, *args, **kwargs):
-        return {'val_loss': torch.tensor(0.7)}
-
-    def validation_end(self, outputs):
-        return {'val_loss': torch.tensor(0.7)}
-
-    def test_dataloader(self):
-        return self.dataloader(train=False)
-
-    def test_end(self, outputs):
-        return {'test_loss': torch.tensor(0.7)}