Rename ProgressBarBase to ProgressBar

docs/source-pytorch/api_references.rst

@@ -42,7 +42,7 @@ callbacks
     ModelPruning
     ModelSummary
     OnExceptionCheckpoint
-    ProgressBarBase
+    ProgressBar
     RichModelSummary
     RichProgressBar
     StochasticWeightAveraging

docs/source-pytorch/common/progress_bar.rst

@@ -11,7 +11,7 @@ Customize the progress bar
 Lightning supports two different types of progress bars (`tqdm <https://github.com/tqdm/tqdm>`_ and `rich <https://github.com/Textualize/rich>`_). :class:`~lightning.pytorch.callbacks.TQDMProgressBar` is used by default,
 but you can override it by passing a custom :class:`~lightning.pytorch.callbacks.TQDMProgressBar` or :class:`~lightning.pytorch.callbacks.RichProgressBar` to the ``callbacks`` argument of the :class:`~lightning.pytorch.trainer.trainer.Trainer`.
 
-You could also use the :class:`~lightning.pytorch.callbacks.ProgressBarBase` class to implement your own progress bar.
+You could also use the :class:`~lightning.pytorch.callbacks.ProgressBar` class to implement your own progress bar.
 
 -------------
 

docs/source-pytorch/extensions/callbacks.rst

@@ -98,7 +98,7 @@ Lightning has a few built-in callbacks.
     ModelCheckpoint
     ModelPruning
     ModelSummary
-    ProgressBarBase
+    ProgressBar
     RichModelSummary
     RichProgressBar
     StochasticWeightAveraging

docs/source-pytorch/extensions/logging.rst

@@ -318,7 +318,7 @@ Modifying the Progress Bar
 
 The progress bar by default already includes the training loss and version number of the experiment
 if you are using a logger. These defaults can be customized by overriding the
-:meth:`~lightning.pytorch.callbacks.progress.base.ProgressBarBase.get_metrics` hook in your logger.
+:meth:`~lightning.pytorch.callbacks.progress.progress_bar.ProgressBar.get_metrics` hook in your logger.
 
 .. code-block:: python
 

docs/source-pytorch/visualize/logging_advanced.rst

@@ -12,7 +12,7 @@ Track and Visualize Experiments (advanced)
 ****************************
 Change progress bar defaults
 ****************************
-To change the default values (ie: version number) shown in the progress bar, override the :meth:`~lightning.pytorch.callbacks.progress.base.ProgressBarBase.get_metrics` method in your logger.
+To change the default values (ie: version number) shown in the progress bar, override the :meth:`~lightning.pytorch.callbacks.progress.progress_bar.ProgressBar.get_metrics` method in your logger.
 
 .. code-block:: python
 

docs/source-pytorch/visualize/logging_expert.rst

@@ -82,14 +82,14 @@ To customize either the  :class:`~lightning.pytorch.callbacks.TQDMProgressBar` o
 ***************************
 Build your own progress bar
 ***************************
-To build your own progress bar, subclass :class:`~lightning.pytorch.callbacks.ProgressBarBase`
+To build your own progress bar, subclass :class:`~lightning.pytorch.callbacks.ProgressBar`
 
 .. code-block:: python
 
-    from lightning.pytorch.callbacks import ProgressBarBase
+    from lightning.pytorch.callbacks import ProgressBar
 
 
-    class LitProgressBar(ProgressBarBase):
+    class LitProgressBar(ProgressBar):
         def __init__(self):
             super().__init__()  # don't forget this :)
             self.enable = True

src/lightning/app/cli/pl-app-template/core/callbacks.py

@@ -7,7 +7,7 @@
 from lightning.app.storage import Path
 from lightning.app.utilities.app_helpers import Logger
 from lightning.pytorch import Callback
-from lightning.pytorch.callbacks.progress.base import get_standard_metrics
+from lightning.pytorch.callbacks.progress.progress_bar import get_standard_metrics
 from lightning.pytorch.loggers import TensorBoardLogger, WandbLogger
 from lightning.pytorch.utilities.parsing import collect_init_args
 

src/lightning/pytorch/CHANGELOG.md

@@ -70,6 +70,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Renamed `ProgressBarBase` to `ProgressBar` ([#17058](https://github.com/Lightning-AI/lightning/pull/17058))
+
 
 - The `Trainer` now chooses `accelerator="auto", strategy="auto", devices="auto"` as defaults ([#16847](https://github.com/Lightning-AI/lightning/pull/16847))
 

src/lightning/pytorch/callbacks/__init__.py

@@ -25,7 +25,7 @@
 from lightning.pytorch.callbacks.model_summary import ModelSummary
 from lightning.pytorch.callbacks.on_exception_checkpoint import OnExceptionCheckpoint
 from lightning.pytorch.callbacks.prediction_writer import BasePredictionWriter
-from lightning.pytorch.callbacks.progress import ProgressBarBase, RichProgressBar, TQDMProgressBar
+from lightning.pytorch.callbacks.progress import ProgressBar, RichProgressBar, TQDMProgressBar
 from lightning.pytorch.callbacks.pruning import ModelPruning
 from lightning.pytorch.callbacks.rich_model_summary import RichModelSummary
 from lightning.pytorch.callbacks.stochastic_weight_avg import StochasticWeightAveraging
@@ -48,7 +48,7 @@
     "ModelPruning",
     "ModelSummary",
     "OnExceptionCheckpoint",
-    "ProgressBarBase",
+    "ProgressBar",
     "RichModelSummary",
     "RichProgressBar",
     "StochasticWeightAveraging",

src/lightning/pytorch/callbacks/progress/__init__.py

@@ -18,6 +18,6 @@
 Use or override one of the progress bar callbacks.
 
 """
-from lightning.pytorch.callbacks.progress.base import ProgressBarBase  # noqa: F401
+from lightning.pytorch.callbacks.progress.progress_bar import ProgressBar  # noqa: F401
 from lightning.pytorch.callbacks.progress.rich_progress import RichProgressBar  # noqa: F401
 from lightning.pytorch.callbacks.progress.tqdm_progress import TQDMProgressBar  # noqa: F401

src/lightning/pytorch/callbacks/progress/base.py → src/lightning/pytorch/callbacks/progress/progress_bar.py

@@ -18,15 +18,15 @@
 from lightning.pytorch.utilities.rank_zero import rank_zero_warn
 
 
-class ProgressBarBase(Callback):
+class ProgressBar(Callback):
     r"""
     The base class for progress bars in Lightning. It is a :class:`~lightning.pytorch.callbacks.Callback`
     that keeps track of the batch progress in the :class:`~lightning.pytorch.trainer.trainer.Trainer`.
     You should implement your highly custom progress bars with this as the base class.
 
     Example::
 
-        class LitProgressBar(ProgressBarBase):
+        class LitProgressBar(ProgressBar):
 
             def __init__(self):
                 super().__init__()  # don't forget this :)

src/lightning/pytorch/callbacks/progress/rich_progress.py

@@ -19,7 +19,7 @@
 from lightning_utilities.core.imports import RequirementCache
 
 import lightning.pytorch as pl
-from lightning.pytorch.callbacks.progress.base import ProgressBarBase
+from lightning.pytorch.callbacks.progress.progress_bar import ProgressBar
 from lightning.pytorch.utilities.types import STEP_OUTPUT
 
 _RICH_AVAILABLE = RequirementCache("rich>=10.2.2")
@@ -28,19 +28,19 @@
     from rich import get_console, reconfigure
     from rich.console import Console, RenderableType
     from rich.progress import BarColumn, Progress, ProgressColumn, Task, TaskID, TextColumn
-    from rich.progress_bar import ProgressBar
+    from rich.progress_bar import ProgressBar as _RichProgressBar
     from rich.style import Style
     from rich.text import Text
 
     class CustomBarColumn(BarColumn):
         """Overrides ``BarColumn`` to provide support for dataloaders that do not define a size (infinite size)
         such as ``IterableDataset``."""
 
-        def render(self, task: "Task") -> ProgressBar:
+        def render(self, task: "Task") -> _RichProgressBar:
             """Gets a progress bar widget for a task."""
             assert task.total is not None
             assert task.remaining is not None
-            return ProgressBar(
+            return _RichProgressBar(
                 total=max(0, task.total),
                 completed=max(0, task.completed),
                 width=None if self.bar_width is None else max(1, self.bar_width),
@@ -204,7 +204,7 @@ class RichProgressBarTheme:
     metrics: Union[str, Style] = "white"
 
 
-class RichProgressBar(ProgressBarBase):
+class RichProgressBar(ProgressBar):
     """Create a progress bar with `rich text formatting <https://github.com/Textualize/rich>`_.
 
     Install it with pip:

src/lightning/pytorch/callbacks/progress/tqdm_progress.py

@@ -28,7 +28,7 @@
     from tqdm import tqdm as _tqdm
 
 import lightning.pytorch as pl
-from lightning.pytorch.callbacks.progress.base import ProgressBarBase
+from lightning.pytorch.callbacks.progress.progress_bar import ProgressBar
 from lightning.pytorch.utilities.rank_zero import rank_zero_debug
 
 _PAD_SIZE = 5
@@ -59,7 +59,7 @@ def format_num(n: Union[int, float, str]) -> str:
         return n
 
 
-class TQDMProgressBar(ProgressBarBase):
+class TQDMProgressBar(ProgressBar):
     r"""
     This is the default progress bar used by Lightning. It prints to ``stdout`` using the
     :mod:`tqdm` package and shows up to four different bars:

src/lightning/pytorch/trainer/connectors/callback_connector.py

@@ -23,7 +23,7 @@
     Checkpoint,
     ModelCheckpoint,
     ModelSummary,
-    ProgressBarBase,
+    ProgressBar,
     RichProgressBar,
     TQDMProgressBar,
 )
@@ -115,7 +115,7 @@ def _configure_model_summary_callback(self, enable_model_summary: bool) -> None:
         self.trainer.callbacks.append(model_summary)
 
     def _configure_progress_bar(self, enable_progress_bar: bool = True) -> None:
-        progress_bars = [c for c in self.trainer.callbacks if isinstance(c, ProgressBarBase)]
+        progress_bars = [c for c in self.trainer.callbacks if isinstance(c, ProgressBar)]
         if len(progress_bars) > 1:
             raise MisconfigurationException(
                 "You added multiple progress bar callbacks to the Trainer, but currently only one"

src/lightning/pytorch/trainer/trainer.py

@@ -36,7 +36,7 @@
 from lightning.fabric.utilities.cloud_io import get_filesystem
 from lightning.fabric.utilities.types import _PATH
 from lightning.pytorch.accelerators import Accelerator
-from lightning.pytorch.callbacks import Callback, Checkpoint, EarlyStopping, ProgressBarBase
+from lightning.pytorch.callbacks import Callback, Checkpoint, EarlyStopping, ProgressBar
 from lightning.pytorch.core.datamodule import LightningDataModule
 from lightning.pytorch.loggers import Logger
 from lightning.pytorch.loggers.tensorboard import TensorBoardLogger
@@ -1193,11 +1193,11 @@ def checkpoint_callbacks(self) -> List[Checkpoint]:
         return [c for c in self.callbacks if isinstance(c, Checkpoint)]
 
     @property
-    def progress_bar_callback(self) -> Optional[ProgressBarBase]:
-        """An instance of :class:`~lightning.pytorch.callbacks.progress.base.ProgressBarBase` found in the
+    def progress_bar_callback(self) -> Optional[ProgressBar]:
+        """An instance of :class:`~lightning.pytorch.callbacks.progress.progress_bar.ProgressBar` found in the
         Trainer.callbacks list, or ``None`` if one doesn't exist."""
         for c in self.callbacks:
-            if isinstance(c, ProgressBarBase):
+            if isinstance(c, ProgressBar):
                 return c
         return None
 

tests/tests_pytorch/callbacks/progress/test_rich_progress_bar.py

@@ -20,7 +20,7 @@
 from torch.utils.data import DataLoader
 
 from lightning.pytorch import Trainer
-from lightning.pytorch.callbacks import ProgressBarBase, RichProgressBar
+from lightning.pytorch.callbacks import ProgressBar, RichProgressBar
 from lightning.pytorch.callbacks.progress.rich_progress import RichProgressBarTheme
 from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset, RandomIterableDataset
 from lightning.pytorch.loggers import CSVLogger
@@ -31,7 +31,7 @@
 def test_rich_progress_bar_callback():
     trainer = Trainer(callbacks=RichProgressBar())
 
-    progress_bars = [c for c in trainer.callbacks if isinstance(c, ProgressBarBase)]
+    progress_bars = [c for c in trainer.callbacks if isinstance(c, ProgressBar)]
 
     assert len(progress_bars) == 1
     assert isinstance(trainer.progress_bar_callback, RichProgressBar)

tests/tests_pytorch/callbacks/progress/test_tqdm_progress_bar.py

@@ -25,7 +25,7 @@
 from torch.utils.data.dataloader import DataLoader
 
 from lightning.pytorch import Trainer
-from lightning.pytorch.callbacks import ModelCheckpoint, ProgressBarBase, TQDMProgressBar
+from lightning.pytorch.callbacks import ModelCheckpoint, ProgressBar, TQDMProgressBar
 from lightning.pytorch.callbacks.progress.tqdm_progress import Tqdm
 from lightning.pytorch.core.module import LightningModule
 from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
@@ -85,15 +85,15 @@ def test_tqdm_progress_bar_on(tmpdir, pbar):
     """Test different ways the progress bar can be turned on."""
     trainer = Trainer(default_root_dir=tmpdir, callbacks=pbar)
 
-    progress_bars = [c for c in trainer.callbacks if isinstance(c, ProgressBarBase)]
+    progress_bars = [c for c in trainer.callbacks if isinstance(c, ProgressBar)]
     assert len(progress_bars) == 1
     assert progress_bars[0] is trainer.progress_bar_callback
 
 
 def test_tqdm_progress_bar_off(tmpdir):
     """Test turning the progress bar off."""
     trainer = Trainer(default_root_dir=tmpdir, enable_progress_bar=False)
-    progress_bars = [c for c in trainer.callbacks if isinstance(c, ProgressBarBase)]
+    progress_bars = [c for c in trainer.callbacks if isinstance(c, ProgressBar)]
     assert not len(progress_bars)
 
 

tests/tests_pytorch/trainer/connectors/test_callback_connector.py

@@ -26,7 +26,7 @@
     LearningRateMonitor,
     ModelCheckpoint,
     ModelSummary,
-    ProgressBarBase,
+    ProgressBar,
     TQDMProgressBar,
 )
 from lightning.pytorch.callbacks.batch_size_finder import BatchSizeFinder
@@ -164,7 +164,7 @@ def test_attach_model_callbacks():
     def _attach_callbacks(trainer_callbacks, model_callbacks):
         model = LightningModule()
         model.configure_callbacks = lambda: model_callbacks
-        has_progress_bar = any(isinstance(cb, ProgressBarBase) for cb in trainer_callbacks + model_callbacks)
+        has_progress_bar = any(isinstance(cb, ProgressBar) for cb in trainer_callbacks + model_callbacks)
         trainer = Trainer(
             enable_checkpointing=False,
             enable_progress_bar=has_progress_bar,