Error messages for the remaining callback hooks

src/pytorch_lightning/_graveyard/__init__.py

@@ -12,5 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import pytorch_lightning._graveyard.callbacks
 import pytorch_lightning._graveyard.trainer
 import pytorch_lightning._graveyard.training_type  # noqa: F401

src/pytorch_lightning/_graveyard/callbacks.py

@@ -0,0 +1,30 @@
+# 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.
+
+from typing import Any
+
+from pytorch_lightning.callbacks import ModelCheckpoint
+
+
+def _save_checkpoint(_: ModelCheckpoint, __: Any) -> None:
+    # Remove in v2.0.0
+    raise NotImplementedError(
+        f"`{ModelCheckpoint.__name__}.save_checkpoint()` was deprecated in v1.6 and is no longer supported"
+        f" as of 1.8. Please use `trainer.save_checkpoint()` to manually save a checkpoint. This method will be"
+        f" removed completely in v2.0."
+    )
+
+
+# Methods
+ModelCheckpoint.save_checkpoint = _save_checkpoint

src/pytorch_lightning/callbacks/model_checkpoint.py

@@ -351,13 +351,6 @@ def load_state_dict(self, state_dict: Dict[str, Any]) -> None:
 
         self.best_model_path = state_dict["best_model_path"]
 
-    def save_checkpoint(self, trainer: "pl.Trainer") -> None:
-        raise NotImplementedError(
-            f"`{self.__class__.__name__}.save_checkpoint()` was deprecated in v1.6 and is no longer supported"
-            f" as of 1.8. Please use `trainer.save_checkpoint()` to manually save a checkpoint. This method will be"
-            f" removed completely in v2.0."
-        )
-
     def _save_topk_checkpoint(self, trainer: "pl.Trainer", monitor_candidates: Dict[str, Tensor]) -> None:
         if self.save_top_k == 0:
             return

src/pytorch_lightning/trainer/configuration_validator.py

@@ -212,6 +212,14 @@ def _check_on_pretrain_routine(model: "pl.LightningModule") -> None:
 
 def _check_deprecated_callback_hooks(trainer: "pl.Trainer") -> None:
     for callback in trainer.callbacks:
+        if callable(getattr(callback, "on_init_start", None)):
+            raise RuntimeError(
+                "The `on_init_start` callback hook was deprecated in v1.6 and is no longer supported as of v1.8."
+            )
+        if callable(getattr(callback, "on_init_end", None)):
+            raise RuntimeError(
+                "The `on_init_end` callback hook was deprecated in v1.6 and is no longer supported as of v1.8."
+            )
         if callable(getattr(callback, "on_configure_sharded_model", None)):
             raise RuntimeError(
                 "The `on_configure_sharded_model` callback hook was removed in v1.8. Use `setup()` instead."

tests/tests_pytorch/deprecated_api/test_remove_2-0.py

@@ -18,7 +18,6 @@
 
 import pytorch_lightning
 from pytorch_lightning import Callback, Trainer
-from pytorch_lightning.callbacks import ModelCheckpoint
 from pytorch_lightning.demos.boring_classes import BoringModel
 from tests_pytorch.callbacks.test_callbacks import OldStatefulCallback
 from tests_pytorch.helpers.runif import RunIf
@@ -292,11 +291,32 @@ def on_pretrain_routine_end(self, trainer, pl_module):
         trainer.fit(model)
 
 
-def test_v2_0_0_deprecated_mc_save_checkpoint():
-    mc = ModelCheckpoint()
-    trainer = Trainer()
-    with mock.patch.object(trainer, "save_checkpoint"), pytest.raises(
-        NotImplementedError,
-        match=r"ModelCheckpoint.save_checkpoint\(\)` was deprecated in v1.6 and is no longer supported as of 1.8.",
+class OnInitStartCallback(Callback):
+    def on_init_start(self, trainer):
+        print("Starting to init trainer!")
+
+
+class OnInitEndCallback(Callback):
+    def on_init_end(self, trainer):
+        print("Trainer is init now")
+
+
+@pytest.mark.parametrize("callback_class", [OnInitStartCallback, OnInitEndCallback])
+def test_v2_0_0_unsupported_on_init_start_end(callback_class, tmpdir):
+    model = BoringModel()
+    trainer = Trainer(
+        callbacks=[callback_class()],
+        max_epochs=1,
+        fast_dev_run=True,
+        enable_progress_bar=False,
+        logger=False,
+        default_root_dir=tmpdir,
+    )
+    with pytest.raises(
+        RuntimeError, match="callback hook was deprecated in v1.6 and is no longer supported as of v1.8"
+    ):
+        trainer.fit(model)
+    with pytest.raises(
+        RuntimeError, match="callback hook was deprecated in v1.6 and is no longer supported as of v1.8"
     ):
-        mc.save_checkpoint(trainer)
+        trainer.validate(model)

tests/tests_pytorch/graveyard/test_callbacks.py

@@ -0,0 +1,26 @@
+# 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.
+
+import pytest
+
+from pytorch_lightning.callbacks import ModelCheckpoint
+
+
+def test_v2_0_0_deprecated_mc_save_checkpoint():
+    mc = ModelCheckpoint()
+    with pytest.raises(
+        NotImplementedError,
+        match=r"ModelCheckpoint.save_checkpoint\(\)` was deprecated in v1.6 and is no longer supported as of 1.8.",
+    ):
+        mc.save_checkpoint(None)