fix progress bar restart with fault-tolerant training enabled (#9310)

* reset progress updates
* update docs
* add test

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

CHANGELOG.md

@@ -297,6 +297,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed `move_metrics_to_cpu` moving the loss on cpu while training on device ([#9308](https://github.com/PyTorchLightning/pytorch-lightning/pull/9308))
 
 
+- Fixed incorrect main progress bar indicator when resuming training mid-epoch ([#9310](https://github.com/PyTorchLightning/pytorch-lightning/pull/9310))
+
+
 ## [1.4.5] - 2021-08-31
 
 - Fixed reduction using `self.log(sync_dict=True, reduce_fx={mean,max})` ([#9142](https://github.com/PyTorchLightning/pytorch-lightning/pull/9142))

pytorch_lightning/callbacks/progress/base.py

@@ -154,10 +154,10 @@ class ProgressBarBase(Callback):
         self._trainer = trainer
 
     def on_train_start(self, trainer, pl_module):
-        self._train_batch_idx = trainer.fit_loop.batch_idx
+        self._train_batch_idx = 0
 
     def on_train_epoch_start(self, trainer, pl_module):
-        self._train_batch_idx = 0
+        self._train_batch_idx = trainer.fit_loop.epoch_loop.batch_progress.current.completed
 
     def on_train_batch_end(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx):
         self._train_batch_idx += 1

pytorch_lightning/callbacks/progress/progress.py

@@ -229,7 +229,7 @@ class ProgressBar(ProgressBarBase):
             val_checks_per_epoch = total_train_batches // trainer.val_check_batch
             total_val_batches = total_val_batches * val_checks_per_epoch
         total_batches = total_train_batches + total_val_batches
-        reset(self.main_progress_bar, total_batches)
+        reset(self.main_progress_bar, total=total_batches, current=self.train_batch_idx)
         self.main_progress_bar.set_description(f"Epoch {trainer.current_epoch}")
 
     def on_train_batch_end(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx):
@@ -243,11 +243,11 @@ class ProgressBar(ProgressBarBase):
     def on_validation_start(self, trainer, pl_module):
         super().on_validation_start(trainer, pl_module)
         if trainer.sanity_checking:
-            reset(self.val_progress_bar, sum(trainer.num_sanity_val_batches))
+            reset(self.val_progress_bar, total=sum(trainer.num_sanity_val_batches), current=self.val_batch_idx)
         else:
             self._update_bar(self.main_progress_bar)  # fill up remaining
             self.val_progress_bar = self.init_validation_tqdm()
-            reset(self.val_progress_bar, self.total_val_batches)
+            reset(self.val_progress_bar, total=self.total_val_batches, current=self.val_batch_idx)
 
     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)
@@ -333,7 +333,8 @@ def convert_inf(x: Optional[Union[int, float]]) -> Optional[Union[int, float]]:
     return x
 
 
-def reset(bar: tqdm, total: Optional[int] = None) -> None:
-    """Resets the tqdm bar to 0 progress with a new total, unless it is disabled."""
+def reset(bar: tqdm, total: Optional[int] = None, current: int = 0) -> None:
+    """Resets the tqdm bar to the desired position and sets a new total, unless it is disabled."""
     if not bar.disable:
         bar.reset(total=convert_inf(total))
+        bar.n = current

tests/callbacks/test_progress_bar.py

@@ -558,3 +558,33 @@ def _test_progress_bar_max_val_check_interval(
     total_val_batches = total_val_batches * val_checks_per_epoch
     if trainer.is_global_zero:
         assert trainer.progress_bar_callback.main_progress_bar.total == total_train_batches + total_val_batches
+
+
+def test_progress_bar_main_bar_resume():
+    """Test that the progress bar can resume its counters based on the Trainer state."""
+    bar = ProgressBar()
+    trainer = Mock()
+    model = Mock()
+
+    trainer.sanity_checking = False
+    trainer.check_val_every_n_epoch = 1
+    trainer.current_epoch = 1
+    trainer.num_training_batches = 5
+    trainer.val_check_batch = 5
+    trainer.num_val_batches = [3]
+    trainer.fit_loop.epoch_loop.batch_progress.current.completed = 3
+
+    bar.on_init_end(trainer)
+    bar.on_train_start(trainer, model)
+    bar.on_train_epoch_start(trainer, model)
+
+    assert bar.main_progress_bar.n == 3
+    assert bar.main_progress_bar.total == 8
+
+    # bar.on_train_epoch_end(trainer, model)
+    bar.on_validation_start(trainer, model)
+    bar.on_validation_epoch_start(trainer, model)
+
+    # restarting mid validation epoch is not currently supported
+    assert bar.val_progress_bar.n == 0
+    assert bar.val_progress_bar.total == 3