adding hint to the logger's error messages

Lightning-AI · Dec 13, 2022 · 84709bb · 84709bb
1 parent 53ceb15
commit 84709bb
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Showing 2 changed files with 29 additions and 29 deletions.
diff --git a/src/pytorch_lightning/trainer/connectors/logger_connector/fx_validator.py b/src/pytorch_lightning/trainer/connectors/logger_connector/fx_validator.py
@@ -174,7 +174,7 @@ def check_logging(cls, fx_name: str) -> None:
             )
 
         if cls.functions[fx_name] is None:
-            raise MisconfigurationException(f"You can't `self.log()` inside `{fx_name}`.")
+            raise MisconfigurationException(f"You can alternatively log with `logger.experiment` inside `{fx_name}`.")
 
     @classmethod
     def get_default_logging_levels(

diff --git a/tests/tests_pytorch/trainer/logging_/test_logger_connector.py b/tests/tests_pytorch/trainer/logging_/test_logger_connector.py
@@ -133,7 +133,7 @@ def test_fx_validator():
                     validator.check_logging_levels(fx_name=func_name, on_step=True, on_epoch=on_epoch)
         else:
             assert func_name in not_supported
-            with pytest.raises(MisconfigurationException, match="You can't"):
+            with pytest.raises(MisconfigurationException, match="You can alternatively log with"):
                 validator.check_logging(fx_name=func_name)
 
     with pytest.raises(RuntimeError, match="Logging inside `foo` is not implemented"):
@@ -188,29 +188,29 @@ def test_fx_validator_integration(tmpdir):
     """Tries to log inside all `LightningModule` and `Callback` hooks to check any expected errors."""
     not_supported = {
         None: "`self.trainer` reference is not registered",
-        "setup": "You can't",
-        "configure_sharded_model": "You can't",
-        "configure_optimizers": "You can't",
-        "on_fit_start": "You can't",
-        "train_dataloader": "You can't",
-        "val_dataloader": "You can't",
-        "on_before_batch_transfer": "You can't",
-        "transfer_batch_to_device": "You can't",
-        "on_after_batch_transfer": "You can't",
-        "on_validation_end": "You can't",
-        "on_train_end": "You can't",
-        "on_fit_end": "You can't",
-        "teardown": "You can't",
-        "on_sanity_check_start": "You can't",
-        "on_sanity_check_end": "You can't",
-        "prepare_data": "You can't",
-        "configure_callbacks": "You can't",
-        "on_validation_model_eval": "You can't",
-        "on_validation_model_train": "You can't",
-        "lr_scheduler_step": "You can't",
-        "on_save_checkpoint": "You can't",
-        "on_load_checkpoint": "You can't",
-        "on_exception": "You can't",
+        "setup": "You can alternatively log with",
+        "configure_sharded_model": "You can alternatively log with",
+        "configure_optimizers": "You can alternatively log with",
+        "on_fit_start": "You can alternatively log with",
+        "train_dataloader": "You can alternatively log with",
+        "val_dataloader": "You can alternatively log with",
+        "on_before_batch_transfer": "You can alternatively log with",
+        "transfer_batch_to_device": "You can alternatively log with",
+        "on_after_batch_transfer": "You can alternatively log with",
+        "on_validation_end": "You can alternatively log with",
+        "on_train_end": "You can alternatively log with",
+        "on_fit_end": "You can alternatively log with",
+        "teardown": "You can alternatively log with",
+        "on_sanity_check_start": "You can alternatively log with",
+        "on_sanity_check_end": "You can alternatively log with",
+        "prepare_data": "You can alternatively log with",
+        "configure_callbacks": "You can alternatively log with",
+        "on_validation_model_eval": "You can alternatively log with",
+        "on_validation_model_train": "You can alternatively log with",
+        "lr_scheduler_step": "You can alternatively log with",
+        "on_save_checkpoint": "You can alternatively log with",
+        "on_load_checkpoint": "You can alternatively log with",
+        "on_exception": "You can alternatively log with",
     }
     model = HookedModel(not_supported)
 
@@ -232,10 +232,10 @@ def test_fx_validator_integration(tmpdir):
     not_supported.update(
         {
             # `lightning_module` ref is now present from the `fit` call
-            "test_dataloader": "You can't",
-            "on_test_model_eval": "You can't",
-            "on_test_model_train": "You can't",
-            "on_test_end": "You can't",
+            "test_dataloader": "You can alternatively log with",
+            "on_test_model_eval": "You can alternatively log with",
+            "on_test_model_train": "You can alternatively log with",
+            "on_test_end": "You can alternatively log with",
         }
     )
     trainer.test(model, verbose=False)