[warning] Add a warning with missing callback with resume_from_checkpoint (#7254)

* add a warning

* add changelog

CHANGELOG.md

@@ -136,6 +136,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `tpu_distributed` check for TPU Spawn barrier ([#7241](https://github.com/PyTorchLightning/pytorch-lightning/pull/7241))
 
 
+- Added warning when missing `Callback` and using `resume_from_checkpoint` ([#7254](https://github.com/PyTorchLightning/pytorch-lightning/pull/7254))
+
+
 ### Changed
 
 - Renamed `pytorch_lightning.callbacks.swa` to `pytorch_lightning.callbacks.stochastic_weight_avg` ([#6259](https://github.com/PyTorchLightning/pytorch-lightning/pull/6259))

pytorch_lightning/trainer/callback_hook.py

@@ -19,7 +19,7 @@ from typing import Any, Callable, Dict, List, Optional, Type
 
 from pytorch_lightning.callbacks import Callback
 from pytorch_lightning.core.lightning import LightningModule
-from pytorch_lightning.utilities import rank_zero_deprecation
+from pytorch_lightning.utilities import rank_zero_deprecation, rank_zero_warn
 from pytorch_lightning.utilities.signature_utils import is_param_in_hook_signature
 from pytorch_lightning.utilities.types import EPOCH_OUTPUT, STEP_OUTPUT
 from pytorch_lightning.utilities.warnings import WarningCache
@@ -293,10 +293,22 @@ class TrainerCallbackHookMixin(ABC):
 
     def on_load_checkpoint(self, checkpoint):
         """Called when loading a model checkpoint."""
-        callback_states = checkpoint.get('callbacks')
+
         # Todo: the `callback_states` are dropped with TPUSpawn as they
         # can't be saved using `xm.save`
         # https://github.com/pytorch/xla/issues/2773
+        callback_states = checkpoint.get('callbacks')
+
+        current_callbacks_type = {type(cb) for cb in self.callbacks}
+        saved_callbacks_type = set(callback_states.keys())
+        difference = saved_callbacks_type.difference(current_callbacks_type)
+        if difference:
+            rank_zero_warn(
+                "Be aware that when using ``resume_from_checkpoint``, "
+                "callbacks used to create the checkpoint need to be provided. "
+                f"Please, add the following callbacks: {list(difference)}. ", UserWarning
+            )
+
         if callback_states is not None:
             for callback in self.callbacks:
                 state = callback_states.get(type(callback))

tests/trainer/test_trainer.py

@@ -2043,6 +2043,28 @@ def test_fit_test_synchronization(tmpdir):
     trainer.test()
 
 
+class CustomCallbackOnLoadCheckpoint(Callback):
+
+    def on_save_checkpoint(self, trainer, pl_module, checkpoint) -> dict:
+        return {"a": None}
+
+
+def test_on_load_checkpoint_missing_callbacks(tmpdir):
+    """ Test a warning appears when callbacks in the checkpoint don't match callbacks provided when resuming. """
+
+    model = BoringModel()
+    chk = ModelCheckpoint(dirpath=tmpdir, save_last=True)
+
+    trainer = Trainer(default_root_dir=tmpdir, max_epochs=3, callbacks=[chk, CustomCallbackOnLoadCheckpoint()])
+    trainer.fit(model)
+
+    trainer = Trainer(
+        default_root_dir=tmpdir, max_epochs=5, resume_from_checkpoint=chk.last_model_path, progress_bar_refresh_rate=1
+    )
+    with pytest.warns(UserWarning, match="CustomCallbackOnLoadCheckpoint"):
+        trainer.fit(model)
+
+
 def test_module_current_fx_attributes_reset(tmpdir):
     """ Ensure that lightning module's attributes related to current hook fx are reset at the end of execution. """
     model = BoringModel()