return early if no loggers

Author: akashkw

pytorch_lightning/trainer/trainer.py

@@ -1245,36 +1245,38 @@ def _run(
         return results
 
     def _log_hyperparams(self) -> None:
+        if not self.loggers:
+            return
+
         # log hyper-parameters
         hparams_initial = None
 
         # save exp to get started (this is where the first experiment logs are written)
         datamodule_log_hyperparams = self.datamodule._log_hyperparams if self.datamodule is not None else False
 
-        if self.loggers:
-            if self.lightning_module._log_hyperparams and datamodule_log_hyperparams:
-                datamodule_hparams = self.datamodule.hparams_initial
-                lightning_hparams = self.lightning_module.hparams_initial
-                inconsistent_keys = []
-                for key in lightning_hparams.keys() & datamodule_hparams.keys():
-                    lm_val, dm_val = lightning_hparams[key], datamodule_hparams[key]
-                    if type(lm_val) != type(dm_val):
-                        inconsistent_keys.append(key)
-                    elif isinstance(lm_val, torch.Tensor) and id(lm_val) != id(dm_val):
-                        inconsistent_keys.append(key)
-                    elif lm_val != dm_val:
-                        inconsistent_keys.append(key)
-                if inconsistent_keys:
-                    raise MisconfigurationException(
-                        f"Error while merging hparams: the keys {inconsistent_keys} are present "
-                        "in both the LightningModule's and LightningDataModule's hparams "
-                        "but have different values."
-                    )
-                hparams_initial = {**lightning_hparams, **datamodule_hparams}
-            elif self.lightning_module._log_hyperparams:
-                hparams_initial = self.lightning_module.hparams_initial
-            elif datamodule_log_hyperparams:
-                hparams_initial = self.datamodule.hparams_initial
+        if self.lightning_module._log_hyperparams and datamodule_log_hyperparams:
+            datamodule_hparams = self.datamodule.hparams_initial
+            lightning_hparams = self.lightning_module.hparams_initial
+            inconsistent_keys = []
+            for key in lightning_hparams.keys() & datamodule_hparams.keys():
+                lm_val, dm_val = lightning_hparams[key], datamodule_hparams[key]
+                if type(lm_val) != type(dm_val):
+                    inconsistent_keys.append(key)
+                elif isinstance(lm_val, torch.Tensor) and id(lm_val) != id(dm_val):
+                    inconsistent_keys.append(key)
+                elif lm_val != dm_val:
+                    inconsistent_keys.append(key)
+            if inconsistent_keys:
+                raise MisconfigurationException(
+                    f"Error while merging hparams: the keys {inconsistent_keys} are present "
+                    "in both the LightningModule's and LightningDataModule's hparams "
+                    "but have different values."
+                )
+            hparams_initial = {**lightning_hparams, **datamodule_hparams}
+        elif self.lightning_module._log_hyperparams:
+            hparams_initial = self.lightning_module.hparams_initial
+        elif datamodule_log_hyperparams:
+            hparams_initial = self.datamodule.hparams_initial
 
         for logger in self.loggers:
             if hparams_initial is not None: