Fix wrong doc-strings in several handlers

monai/handlers/mlflow_handler.py

@@ -116,7 +116,7 @@ def close(self) -> None:
     def epoch_completed(self, engine: Engine) -> None:
         """
         Handler for train or validation/evaluation epoch completed Event.
-        Track epoch level log, default values are from Ignite state.metrics dict.
+        Track epoch level log, default values are from Ignite `engine.state.metrics` dict.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
@@ -143,8 +143,8 @@ def iteration_completed(self, engine: Engine) -> None:
 
     def _default_epoch_log(self, engine: Engine) -> None:
         """
-        Execute epoch level log operation based on Ignite engine.state data.
-        Track the values from Ignite state.metrics dict.
+        Execute epoch level log operation.
+        Default to track the values from Ignite `engine.state.metrics` dict.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
@@ -159,9 +159,10 @@ def _default_epoch_log(self, engine: Engine) -> None:
 
     def _default_iteration_log(self, engine: Engine) -> None:
         """
-        Execute iteration log operation based on Ignite engine.state data.
-        The default behavior is to track loss from output[0] as output is a decollated list
-        and we replicated loss value for every item of the decollated list.
+        Execute iteration log operation based on Ignite `engine.state.output` data.
+        Log the values from `self.output_transform(engine.state.output)`.
+        Since `engine.state.output` is a decollated list and we replicated the loss value for every item
+        of the decollated list, the default behavior is to track the loss from `output[0]`.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.

monai/handlers/stats_handler.py

@@ -108,7 +108,7 @@ def attach(self, engine: Engine) -> None:
     def epoch_completed(self, engine: Engine) -> None:
         """
         Handler for train or validation/evaluation epoch completed Event.
-        Print epoch level log, default values are from Ignite state.metrics dict.
+        Print epoch level log, default values are from Ignite `engine.state.metrics` dict.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
@@ -122,7 +122,7 @@ def epoch_completed(self, engine: Engine) -> None:
     def iteration_completed(self, engine: Engine) -> None:
         """
         Handler for train or validation/evaluation iteration completed Event.
-        Print iteration level log, default values are from Ignite state.logs dict.
+        Print iteration level log, default values are from Ignite `engine.state.output`.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
@@ -149,8 +149,8 @@ def exception_raised(self, engine: Engine, e: Exception) -> None:
 
     def _default_epoch_print(self, engine: Engine) -> None:
         """
-        Execute epoch level log operation based on Ignite engine.state data.
-        print the values from Ignite state.metrics dict.
+        Execute epoch level log operation.
+        Default to print the values from Ignite `engine.state.metrics` dict.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
@@ -179,10 +179,10 @@ def _default_epoch_print(self, engine: Engine) -> None:
 
     def _default_iteration_print(self, engine: Engine) -> None:
         """
-        Execute iteration log operation based on Ignite engine.state data.
-        Print the values from Ignite state.logs dict.
-        The default behavior is to print loss from output[0] as output is a decollated list and we replicated loss
-        value for every item of the decollated list.
+        Execute iteration log operation based on Ignite `engine.state.output` data.
+        Print the values from `self.output_transform(engine.state.output)`.
+        Since `engine.state.output` is a decollated list and we replicated the loss value for every item
+        of the decollated list, the default behavior is to print the loss from `output[0]`.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.

monai/handlers/tensorboard_handlers.py

@@ -136,7 +136,7 @@ def attach(self, engine: Engine) -> None:
     def epoch_completed(self, engine: Engine) -> None:
         """
         Handler for train or validation/evaluation epoch completed Event.
-        Write epoch level events, default values are from Ignite state.metrics dict.
+        Write epoch level events, default values are from Ignite `engine.state.metrics` dict.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
@@ -150,7 +150,7 @@ def epoch_completed(self, engine: Engine) -> None:
     def iteration_completed(self, engine: Engine) -> None:
         """
         Handler for train or validation/evaluation iteration completed Event.
-        Write iteration level events, default values are from Ignite state.logs dict.
+        Write iteration level events, default values are from Ignite `engine.state.output`.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
@@ -163,8 +163,8 @@ def iteration_completed(self, engine: Engine) -> None:
 
     def _default_epoch_writer(self, engine: Engine, writer: SummaryWriter) -> None:
         """
-        Execute epoch level event write operation based on Ignite engine.state data.
-        Default is to write the values from Ignite state.metrics dict.
+        Execute epoch level event write operation.
+        Default to write the values from Ignite `engine.state.metrics` dict.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
@@ -179,9 +179,10 @@ def _default_epoch_writer(self, engine: Engine, writer: SummaryWriter) -> None:
 
     def _default_iteration_writer(self, engine: Engine, writer: SummaryWriter) -> None:
         """
-        Execute iteration level event write operation based on Ignite engine.state data.
-        The default behavior is to print loss from output[0] as output is a decollated list and we replicated loss
-        value for every item of the decollated list.
+        Execute iteration level event write operation based on Ignite `engine.state.output` data.
+        Extract the values from `self.output_transform(engine.state.output)`.
+        Since `engine.state.output` is a decollated list and we replicated the loss value for every item
+        of the decollated list, the default behavior is to track the loss from `output[0]`.
 
         Args:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.