Fix deadlocks for distributed training for RichProgressBar

CHANGELOG.md

@@ -106,7 +106,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Fixed issue with pickling `CSVLogger` after a call to `CSVLogger.save` ([#10388](https://github.com/PyTorchLightning/pytorch-lightning/pull/10388))
 
--
+- Fixed deadlocks for distributed training with `RichProgressBar` ([#10428](https://github.com/PyTorchLightning/pytorch-lightning/pull/10428))
 
 
 -

pytorch_lightning/callbacks/progress/rich_progress.py

@@ -129,13 +129,19 @@ def render(self, task) -> RenderableType:
     class MetricsTextColumn(ProgressColumn):
         """A column containing text."""
 
-        def __init__(self, trainer, pl_module):
+        def __init__(self, trainer):
             self._trainer = trainer
-            self._pl_module = pl_module
             self._tasks = {}
             self._current_task_id = 0
+            self.metrics = {}
             super().__init__()
 
+        def update(self, metrics):
+            # called when metrics are ready to be rendered.
+            # this is due to preventing render from causing deadlock issues by requesting metrics
+            # in separate thread.
+            self.metrics = metrics
+
         def render(self, task) -> Text:
             from pytorch_lightning.trainer.states import TrainerFn
 
@@ -149,14 +155,8 @@ def render(self, task) -> Text:
             if self._trainer.training and task.id != self._current_task_id:
                 return self._tasks[task.id]
             _text = ""
-            # TODO(@daniellepintz): make this code cleaner
-            progress_bar_callback = getattr(self._trainer, "progress_bar_callback", None)
-            if progress_bar_callback:
-                metrics = self._trainer.progress_bar_callback.get_metrics(self._trainer, self._pl_module)
-            else:
-                metrics = self._trainer.progress_bar_metrics
-
-            for k, v in metrics.items():
+
+            for k, v in self.metrics.items():
                 _text += f"{k}: {round(v, 3) if isinstance(v, float) else v} "
             return Text(_text, justify="left")
 
@@ -225,9 +225,9 @@ def __init__(
         self.progress: Optional[Progress] = None
         self.val_sanity_progress_bar_id: Optional[int] = None
         self._reset_progress_bar_ids()
+        self._metric_component = None
         self._progress_stopped: bool = False
         self.theme = theme
-        self._console: Console = Console()
 
     @property
     def refresh_rate_per_second(self) -> float:
@@ -268,12 +268,15 @@ def test_description(self) -> str:
     def predict_description(self) -> str:
         return "Predicting"
 
-    def _init_progress(self, trainer, pl_module):
-        if self.progress is None or self._progress_stopped:
+    def _init_progress(self, trainer):
+        if self.is_enabled and (self.progress is None or self._progress_stopped):
             self._reset_progress_bar_ids()
+            self._console: Console = Console()
             self._console.clear_live()
+            self._metric_component = MetricsTextColumn(trainer)
             self.progress = CustomProgress(
-                *self.configure_columns(trainer, pl_module),
+                *self.configure_columns(trainer),
+                self._metric_component,
                 refresh_per_second=self.refresh_rate_per_second,
                 disable=self.is_disabled,
                 console=self._console,
@@ -284,19 +287,19 @@ def _init_progress(self, trainer, pl_module):
 
     def on_train_start(self, trainer, pl_module):
         super().on_train_start(trainer, pl_module)
-        self._init_progress(trainer, pl_module)
+        self._init_progress(trainer)
 
     def on_predict_start(self, trainer, pl_module):
         super().on_predict_start(trainer, pl_module)
-        self._init_progress(trainer, pl_module)
+        self._init_progress(trainer)
 
     def on_test_start(self, trainer, pl_module):
         super().on_test_start(trainer, pl_module)
-        self._init_progress(trainer, pl_module)
+        self._init_progress(trainer)
 
     def on_validation_start(self, trainer, pl_module):
         super().on_validation_start(trainer, pl_module)
-        self._init_progress(trainer, pl_module)
+        self._init_progress(trainer)
 
     def __getstate__(self):
         # can't pickle the rich progress objects
@@ -307,12 +310,11 @@ def __getstate__(self):
 
     def __setstate__(self, state):
         self.__dict__ = state
-        # reset console reference after loading progress
-        self._console = Console()
+        state["_console"] = Console()
 
     def on_sanity_check_start(self, trainer, pl_module):
         super().on_sanity_check_start(trainer, pl_module)
-        self._init_progress(trainer, pl_module)
+        self._init_progress(trainer)
         self.val_sanity_progress_bar_id = self._add_task(trainer.num_sanity_val_steps, self.sanity_check_description)
 
     def on_sanity_check_end(self, trainer, pl_module):
@@ -333,10 +335,10 @@ def on_train_epoch_start(self, trainer, pl_module):
         train_description = self._get_train_description(trainer.current_epoch)
         if self.main_progress_bar_id is not None and self._leave:
             self._stop_progress()
-            self._init_progress(trainer, pl_module)
+            self._init_progress(trainer)
         if self.main_progress_bar_id is None:
             self.main_progress_bar_id = self._add_task(total_batches, train_description)
-        else:
+        elif self.progress is not None:
             self.progress.reset(
                 self.main_progress_bar_id, total=total_batches, description=train_description, visible=True
             )
@@ -377,6 +379,7 @@ def on_predict_epoch_start(self, trainer, pl_module):
     def on_train_batch_end(self, trainer, pl_module, outputs, batch, batch_idx):
         super().on_train_batch_end(trainer, pl_module, outputs, batch, batch_idx)
         self._update(self.main_progress_bar_id)
+        self._update_metrics(trainer, pl_module)
 
     def on_validation_batch_end(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx):
         super().on_validation_batch_end(trainer, pl_module, outputs, batch, batch_idx, dataloader_idx)
@@ -419,6 +422,11 @@ def _reset_progress_bar_ids(self):
         self.test_progress_bar_id: Optional[int] = None
         self.predict_progress_bar_id: Optional[int] = None
 
+    def _update_metrics(self, trainer, pl_module) -> None:
+        metrics = self.get_metrics(trainer, pl_module)
+        if self._metric_component:
+            self._metric_component.update(metrics)
+
     def teardown(self, trainer, pl_module, stage: Optional[str] = None) -> None:
         self._stop_progress()
 
@@ -441,7 +449,7 @@ def main_progress_bar(self) -> Task:
     def test_progress_bar(self) -> Task:
         return self.progress.tasks[self.test_progress_bar_id]
 
-    def configure_columns(self, trainer, pl_module) -> list:
+    def configure_columns(self, trainer) -> list:
         return [
             TextColumn("[progress.description]{task.description}"),
             CustomBarColumn(
@@ -452,5 +460,4 @@ def configure_columns(self, trainer, pl_module) -> list:
             BatchesProcessedColumn(style=self.theme.batch_process),
             CustomTimeColumn(style=self.theme.time),
             ProcessingSpeedColumn(style=self.theme.processing_speed),
-            MetricsTextColumn(trainer, pl_module),
         ]

tests/callbacks/test_rich_progress_bar.py

@@ -150,15 +150,15 @@ def test_rich_progress_bar_configure_columns():
     custom_column = TextColumn("[progress.description]Testing Rich!")
 
     class CustomRichProgressBar(RichProgressBar):
-        def configure_columns(self, trainer, pl_module):
+        def configure_columns(self, trainer):
             return [custom_column]
 
     progress_bar = CustomRichProgressBar()
 
-    progress_bar._init_progress(Mock(), Mock())
+    progress_bar._init_progress(Mock())
 
     assert progress_bar.progress.columns[0] == custom_column
-    assert len(progress_bar.progress.columns) == 1
+    assert len(progress_bar.progress.columns) == 2
 
 
 @RunIf(rich=True)