Enable RichProgressBar by default if Rich is available

CHANGELOG.md

@@ -211,6 +211,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Changed logging of `LightningModule` and `LightningDataModule` hyperparameters to raise an exception only if there are colliding keys with different values ([#9496](https://github.com/PyTorchLightning/pytorch-lightning/pull/9496))
 
 
+- Enable RichProgressBar by default if Rich is available ([#9647](https://github.com/PyTorchLightning/pytorch-lightning/pull/9647))
+
+
 ### Deprecated
 
 - Deprecated `LightningModule.summarize()` in favor of `pytorch_lightning.utilities.model_summary.summarize()`

pytorch_lightning/trainer/connectors/callback_connector.py

@@ -25,9 +25,9 @@
 )
 from pytorch_lightning.callbacks.rich_model_summary import RichModelSummary
 from pytorch_lightning.callbacks.timer import Timer
-from pytorch_lightning.utilities import ModelSummaryMode, rank_zero_info
+from pytorch_lightning.utilities import _RICH_AVAILABLE, ModelSummaryMode, rank_zero_info
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
-from pytorch_lightning.utilities.warnings import rank_zero_deprecation
+from pytorch_lightning.utilities.warnings import rank_zero_deprecation, rank_zero_warn
 
 
 class CallbackConnector:
@@ -130,8 +130,17 @@ def _configure_swa_callbacks(self):
             self.trainer.callbacks = [StochasticWeightAveraging()] + self.trainer.callbacks
 
     def configure_progress_bar(self, refresh_rate=None, process_position=0):
-        if os.getenv("COLAB_GPU") and refresh_rate is None:
-            # smaller refresh rate on colab causes crashes, choose a higher value
+        use_rich_progress_bar = _RICH_AVAILABLE
+        if use_rich_progress_bar and refresh_rate is not None:
+            rank_zero_warn(
+                "``RichProgressBar`` does not support setting the refresh rate via the Trainer. "
+                "If you'd like to change the refresh rate and continue using the ``RichProgressBar``, "
+                "please pass ``callbacks=RichProgressBar(refresh_rate=4)``. "
+                "Setting to the ``TQDMProgressBar``."
+            )
+            use_rich_progress_bar = False
+        if not use_rich_progress_bar and os.getenv("COLAB_GPU") and refresh_rate is None:
+            # smaller refresh rate on colab causes crashes for TQDM, choose a higher value
             refresh_rate = 20
         refresh_rate = 1 if refresh_rate is None else refresh_rate
 
@@ -144,7 +153,11 @@ def configure_progress_bar(self, refresh_rate=None, process_position=0):
         if len(progress_bars) == 1:
             progress_bar_callback = progress_bars[0]
         elif refresh_rate > 0:
-            progress_bar_callback = ProgressBar(refresh_rate=refresh_rate, process_position=process_position)
+            progress_bar_callback = (
+                RichProgressBar()
+                if use_rich_progress_bar
+                else ProgressBar(refresh_rate=refresh_rate, process_position=process_position)
+            )
             self.trainer.callbacks.append(progress_bar_callback)
         else:
             progress_bar_callback = None

pytorch_lightning/utilities/imports.py

@@ -19,6 +19,7 @@
 import sys
 from importlib.util import find_spec
 
+import pkg_resources
 import torch
 from packaging.version import Version
 from pkg_resources import DistributionNotFound
@@ -53,7 +54,11 @@ def _compare_version(package: str, op, version) -> bool:
     except (ModuleNotFoundError, DistributionNotFound):
         return False
     try:
-        pkg_version = Version(pkg.__version__)
+        if hasattr(pkg, "__version__"):
+            pkg_version = Version(pkg.__version__)
+        else:
+            # try pkg_resources to infer version
+            pkg_version = Version(pkg_resources.get_distribution(pkg).version)
     except TypeError:
         # this is mock by sphinx, so it shall return True ro generate all summaries
         return True
@@ -85,7 +90,7 @@ def _compare_version(package: str, op, version) -> bool:
 _NEPTUNE_GREATER_EQUAL_0_9 = _NEPTUNE_AVAILABLE and _compare_version("neptune", operator.ge, "0.9.0")
 _OMEGACONF_AVAILABLE = _module_available("omegaconf")
 _POPTORCH_AVAILABLE = _module_available("poptorch")
-_RICH_AVAILABLE = _module_available("rich")
+_RICH_AVAILABLE = _module_available("rich") and _compare_version("rich", operator.ge, "10.2.2")
 _TORCH_CPU_AMP_AVAILABLE = _compare_version(
     "torch", operator.ge, "1.10.dev20210902"
 )  # todo: swap to 1.10.0 once released

tests/callbacks/test_rich_progress_bar.py

@@ -17,7 +17,7 @@
 import pytest
 
 from pytorch_lightning import Trainer
-from pytorch_lightning.callbacks import ProgressBarBase, RichProgressBar
+from pytorch_lightning.callbacks import ProgressBar, ProgressBarBase, RichProgressBar
 from pytorch_lightning.callbacks.progress.rich_progress import RichProgressBarTheme
 from pytorch_lightning.utilities.imports import _RICH_AVAILABLE
 from tests.helpers.boring_model import BoringModel
@@ -44,6 +44,25 @@ def test_rich_progress_bar_refresh_rate():
     assert progress_bar.is_disabled
 
 
+@RunIf(rich=True)
+def test_rich_progress_bar_refresh_rate_colab(tmpdir):
+    """Test that the refresh rate is set correctly based on the Trainer, and warn if the user sets the argument."""
+    trainer = Trainer(default_root_dir=tmpdir)
+    assert trainer.progress_bar_callback.refresh_rate_per_second == 10
+    assert isinstance(trainer.progress_bar_callback, RichProgressBar)
+
+    trainer = Trainer(default_root_dir=tmpdir, progress_bar_refresh_rate=None)
+    assert isinstance(trainer.progress_bar_callback, RichProgressBar)
+    assert trainer.progress_bar_callback.refresh_rate_per_second == 10
+
+    with pytest.warns(
+        UserWarning, match="``RichProgressBar`` does not support setting the refresh rate via the Trainer. "
+    ):
+        trainer = Trainer(default_root_dir=tmpdir, progress_bar_refresh_rate=19)
+        assert isinstance(trainer.progress_bar_callback, ProgressBar)
+        assert trainer.progress_bar_callback.refresh_rate == 19
+
+
 @RunIf(rich=True)
 @mock.patch("pytorch_lightning.callbacks.progress.rich_progress.Progress.update")
 def test_rich_progress_bar(progress_update, tmpdir):