From a3aad2301737cf31d65a4b4daf9d2e376266086c Mon Sep 17 00:00:00 2001
From: Danielle Pintz <daniellepintz@gmail.com>
Date: Mon, 20 Sep 2021 20:21:38 +0000
Subject: [PATCH 1/7] deprecate progress_bar_refresh_rate

---
 .../trainer/connectors/callback_connector.py              | 8 ++++++++
 pytorch_lightning/trainer/trainer.py                      | 7 ++++++-
 tests/deprecated_api/test_remove_1-7.py                   | 5 +++++
 3 files changed, 19 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/trainer/connectors/callback_connector.py b/pytorch_lightning/trainer/connectors/callback_connector.py
index cafad831cbb30..95e9e930100ba 100644
--- a/pytorch_lightning/trainer/connectors/callback_connector.py
+++ b/pytorch_lightning/trainer/connectors/callback_connector.py
@@ -74,6 +74,14 @@ def on_trainer_init(
                 " in v1.7. Please pass `pytorch_lightning.callbacks.progress.ProgressBar` with"
                 " `process_position` directly to the Trainer's `callbacks` argument instead."
             )
+
+        if progress_bar_refresh_rate is not None:
+            rank_zero_deprecation(
+                f"Setting `Trainer(progress_bar_refresh_rate={progress_bar_refresh_rate})` is deprecated in v1.5 and"
+                " will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.ProgressBar` with"
+                " `refresh_rate` directly to the Trainer's `callbacks` argument instead."
+            )
+
         self.trainer._progress_bar_callback = self.configure_progress_bar(progress_bar_refresh_rate, process_position)
 
         # configure the ModelSummary callback
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 7cabcb292622a..b0dbe77a18e0a 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -137,7 +137,7 @@ def __init__(
         tpu_cores: Optional[Union[List[int], str, int]] = None,
         ipus: Optional[int] = None,
         log_gpu_memory: Optional[str] = None,
-        progress_bar_refresh_rate: Optional[int] = None,
+        progress_bar_refresh_rate: Optional[int] = None,  # TODO: remove in v1.7
         overfit_batches: Union[int, float] = 0.0,
         track_grad_norm: Union[int, float, str] = -1,
         check_val_every_n_epoch: int = 1,
@@ -284,6 +284,11 @@ def __init__(
                 Ignored when a custom progress bar is passed to :paramref:`~Trainer.callbacks`. Default: None, means
                 a suitable value will be chosen based on the environment (terminal, Google COLAB, etc.).
 
+                .. deprecated:: v1.5
+                    ``progress_bar_refresh_rate`` has been deprecated in v1.5 and will be removed in v1.7.
+                    Please pass :class:`~pytorch_lightning.callbacks.progress.ProgressBar` with ``refresh_rate``
+                    directly to the Trainer's ``callbacks`` argument instead.
+
             profiler: To profile individual steps during training and assist in identifying bottlenecks.
 
             overfit_batches: Overfit a fraction of training data (float) or a set number of batches (int).
diff --git a/tests/deprecated_api/test_remove_1-7.py b/tests/deprecated_api/test_remove_1-7.py
index 5d7d7db761233..c949384a0a8db 100644
--- a/tests/deprecated_api/test_remove_1-7.py
+++ b/tests/deprecated_api/test_remove_1-7.py
@@ -224,3 +224,8 @@ def test_v1_7_0_deprecate_add_get_queue(tmpdir):
 
     with pytest.deprecated_call(match=r"`LightningModule.get_from_queue` method was deprecated in v1.5"):
         trainer.fit(model)
+
+
+def test_v1_7_0_progress_bar_refresh_rate_trainer_constructor(tmpdir):
+    with pytest.deprecated_call(match=r"Setting `Trainer\(progress_bar_refresh_rate=1\)` is deprecated in v1.5"):
+        _ = Trainer(progress_bar_refresh_rate=1)

From 746aa74bc1c22b08cb65dffa83ff38304dbf9f3e Mon Sep 17 00:00:00 2001
From: Danielle Pintz <daniellepintz@gmail.com>
Date: Mon, 20 Sep 2021 20:26:38 +0000
Subject: [PATCH 2/7] update changelog

---
 CHANGELOG.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 2462ffbdbb773..0bc0442933e37 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -249,6 +249,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated passing `flush_logs_every_n_steps` as a Trainer argument, instead pass it to the logger init if supported ([#9366](https://github.com/PyTorchLightning/pytorch-lightning/pull/9366))
 
 
+- Deprecated passing `progress_bar_refresh_rate` to the `Trainer` constructor in favor of adding the `ProgressBar` callback with `refresh_rate` directly to the list of callbacks ([#9616] (https://github.com/PyTorchLightning/pytorch-lightning/pull/9616))
 
 ### Removed
 

From 1ef573999dc98a04759e7fec60865b96e34b39f5 Mon Sep 17 00:00:00 2001
From: Danielle Pintz <daniellepintz@gmail.com>
Date: Wed, 22 Sep 2021 18:20:07 +0000
Subject: [PATCH 3/7] fix changelog

---
 CHANGELOG.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 793e157764583..58c6d70679fd5 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -249,10 +249,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated passing `flush_logs_every_n_steps` as a Trainer argument, instead pass it to the logger init if supported ([#9366](https://github.com/PyTorchLightning/pytorch-lightning/pull/9366))
 
 
-- Deprecated passing `progress_bar_refresh_rate` to the `Trainer` constructor in favor of adding the `ProgressBar` callback with `refresh_rate` directly to the list of callbacks ([#9616] (https://github.com/PyTorchLightning/pytorch-lightning/pull/9616))
+- Deprecated `LightningLoggerBase.close`, `LoggerCollection.close` in favor of `LightningLoggerBase.finalize`, `LoggerCollection.finalize` ([#9422](https://github.com/PyTorchLightning/pytorch-lightning/pull/9422))
 
 
-- Deprecated `LightningLoggerBase.close`, `LoggerCollection.close` in favor of `LightningLoggerBase.finalize`, `LoggerCollection.finalize` ([#9422](https://github.com/PyTorchLightning/pytorch-lightning/pull/9422))
+- Deprecated passing `progress_bar_refresh_rate` to the `Trainer` constructor in favor of adding the `ProgressBar` callback with `refresh_rate` directly to the list of callbacks ([#9616](https://github.com/PyTorchLightning/pytorch-lightning/pull/9616))
 
 
 ### Removed

From 62bda1ad6f488c34b0079f6c9b62d08b4dee5dfc Mon Sep 17 00:00:00 2001
From: Danielle Pintz <daniellepintz@gmail.com>
Date: Thu, 23 Sep 2021 05:44:00 +0000
Subject: [PATCH 4/7] add enable_progress_bar

---
 CHANGELOG.md                                  |  2 +
 benchmarks/test_basic_parity.py               |  2 +-
 .../computer_vision_fine_tuning.py            |  1 -
 .../trainer/connectors/callback_connector.py  | 10 +++-
 pytorch_lightning/trainer/trainer.py          |  4 ++
 tests/accelerators/test_ddp_spawn.py          |  4 +-
 tests/accelerators/test_dp.py                 |  2 +-
 tests/callbacks/test_callbacks.py             |  6 +--
 tests/callbacks/test_early_stopping.py        |  6 +--
 tests/callbacks/test_finetuning_callback.py   |  4 +-
 tests/callbacks/test_lr_monitor.py            |  8 ++--
 tests/callbacks/test_progress_bar.py          | 14 ++++--
 tests/callbacks/test_pruning.py               |  8 ++--
 tests/callbacks/test_stochastic_weight_avg.py |  2 +-
 .../test_checkpoint_callback_frequency.py     |  4 +-
 tests/checkpointing/test_model_checkpoint.py  | 28 +++++------
 .../checkpointing/test_trainer_checkpoint.py  |  2 +-
 tests/deprecated_api/test_remove_1-7.py       |  2 +-
 tests/loggers/test_base.py                    |  6 +--
 .../loops/optimization/test_optimizer_loop.py |  2 +-
 tests/loops/test_loops.py                     |  4 +-
 tests/loops/test_training_loop.py             |  2 +-
 .../models/data/horovod/test_train_script.py  |  2 +-
 tests/models/test_cpu.py                      | 16 +++----
 tests/models/test_gpu.py                      |  4 +-
 tests/models/test_hooks.py                    | 12 ++---
 tests/models/test_horovod.py                  | 20 ++++----
 tests/models/test_onnx.py                     |  2 +-
 tests/models/test_restore.py                  |  8 ++--
 tests/models/test_tpu.py                      | 24 +++++-----
 tests/plugins/test_deepspeed_plugin.py        |  4 +-
 tests/profiler/test_profiler.py               |  2 +-
 .../connectors/test_callback_connector.py     |  2 +-
 .../logging_/test_eval_loop_logging.py        |  2 -
 .../trainer/logging_/test_logger_connector.py |  4 +-
 tests/trainer/optimization/test_optimizers.py |  4 +-
 tests/trainer/test_trainer.py                 | 46 +++++++++++--------
 tests/utilities/test_auto_restart.py          |  2 +-
 38 files changed, 150 insertions(+), 127 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 58c6d70679fd5..832f326654cca 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -145,6 +145,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `RichModelSummary` callback ([#9546](https://github.com/PyTorchLightning/pytorch-lightning/pull/9546))
 
 
+- Added `enable_progress_bar` to Trainer constructor ([]())
+
 ### Changed
 
 - `pytorch_lightning.loggers.neptune.NeptuneLogger` is now consistent with new [neptune-client](https://github.com/neptune-ai/neptune-client) API ([#6867](https://github.com/PyTorchLightning/pytorch-lightning/pull/6867)).
diff --git a/benchmarks/test_basic_parity.py b/benchmarks/test_basic_parity.py
index 9c2c3fb72e80e..6612f76280076 100644
--- a/benchmarks/test_basic_parity.py
+++ b/benchmarks/test_basic_parity.py
@@ -157,7 +157,7 @@ def lightning_loop(cls_model, idx, device_type: str = "cuda", num_epochs=10):
     trainer = Trainer(
         # as the first run is skipped, no need to run it long
         max_epochs=num_epochs if idx > 0 else 1,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         gpus=1 if device_type == "cuda" else 0,
         checkpoint_callback=False,
diff --git a/pl_examples/domain_templates/computer_vision_fine_tuning.py b/pl_examples/domain_templates/computer_vision_fine_tuning.py
index 2fba1d8ad1759..2cfeaf655f819 100644
--- a/pl_examples/domain_templates/computer_vision_fine_tuning.py
+++ b/pl_examples/domain_templates/computer_vision_fine_tuning.py
@@ -273,7 +273,6 @@ def add_arguments_to_parser(self, parser):
             {
                 "trainer.max_epochs": 15,
                 "trainer.weights_summary": None,
-                "trainer.progress_bar_refresh_rate": 1,
                 "trainer.num_sanity_val_steps": 0,
             }
         )
diff --git a/pytorch_lightning/trainer/connectors/callback_connector.py b/pytorch_lightning/trainer/connectors/callback_connector.py
index 95e9e930100ba..c5d16885cb134 100644
--- a/pytorch_lightning/trainer/connectors/callback_connector.py
+++ b/pytorch_lightning/trainer/connectors/callback_connector.py
@@ -38,6 +38,7 @@ def on_trainer_init(
         self,
         callbacks: Optional[Union[List[Callback], Callback]],
         checkpoint_callback: bool,
+        enable_progress_bar: bool,
         progress_bar_refresh_rate: Optional[int],
         process_position: int,
         default_root_dir: Optional[str],
@@ -81,8 +82,15 @@ def on_trainer_init(
                 " will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.ProgressBar` with"
                 " `refresh_rate` directly to the Trainer's `callbacks` argument instead."
             )
+        import logging
 
-        self.trainer._progress_bar_callback = self.configure_progress_bar(progress_bar_refresh_rate, process_position)
+        logging.critical(enable_progress_bar)
+        if enable_progress_bar:
+            self.trainer._progress_bar_callback = self.configure_progress_bar(
+                progress_bar_refresh_rate, process_position
+            )
+        else:
+            self.trainer._progress_bar_callback = None
 
         # configure the ModelSummary callback
         self._configure_model_summary_callback(weights_summary)
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index b0dbe77a18e0a..f37253602af88 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -138,6 +138,7 @@ def __init__(
         ipus: Optional[int] = None,
         log_gpu_memory: Optional[str] = None,
         progress_bar_refresh_rate: Optional[int] = None,  # TODO: remove in v1.7
+        enable_progress_bar: bool = True,
         overfit_batches: Union[int, float] = 0.0,
         track_grad_norm: Union[int, float, str] = -1,
         check_val_every_n_epoch: int = 1,
@@ -289,6 +290,8 @@ def __init__(
                     Please pass :class:`~pytorch_lightning.callbacks.progress.ProgressBar` with ``refresh_rate``
                     directly to the Trainer's ``callbacks`` argument instead.
 
+            enable_progress_bar: Whether to enable to progress bar by default.
+
             profiler: To profile individual steps during training and assist in identifying bottlenecks.
 
             overfit_batches: Overfit a fraction of training data (float) or a set number of batches (int).
@@ -452,6 +455,7 @@ def __init__(
         self.callback_connector.on_trainer_init(
             callbacks,
             checkpoint_callback,
+            enable_progress_bar,
             progress_bar_refresh_rate,
             process_position,
             default_root_dir,
diff --git a/tests/accelerators/test_ddp_spawn.py b/tests/accelerators/test_ddp_spawn.py
index a21078cf55542..806c2fd458402 100644
--- a/tests/accelerators/test_ddp_spawn.py
+++ b/tests/accelerators/test_ddp_spawn.py
@@ -52,7 +52,7 @@ def test_multi_gpu_model_ddp_spawn(tmpdir):
         limit_val_batches=10,
         gpus=[0, 1],
         accelerator="ddp_spawn",
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
 
     model = BoringModel()
@@ -73,7 +73,7 @@ def test_ddp_all_dataloaders_passed_to_fit(tmpdir):
 
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.2,
         limit_val_batches=0.2,
diff --git a/tests/accelerators/test_dp.py b/tests/accelerators/test_dp.py
index 8e09460551dec..dafb763170519 100644
--- a/tests/accelerators/test_dp.py
+++ b/tests/accelerators/test_dp.py
@@ -88,7 +88,7 @@ def test_multi_gpu_model_dp(tmpdir):
         limit_val_batches=10,
         gpus=[0, 1],
         accelerator="dp",
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
 
     model = BoringModel()
diff --git a/tests/callbacks/test_callbacks.py b/tests/callbacks/test_callbacks.py
index 5803db051c659..78e21d821b810 100644
--- a/tests/callbacks/test_callbacks.py
+++ b/tests/callbacks/test_callbacks.py
@@ -35,7 +35,7 @@ def configure_callbacks(self):
 
     model = TestModel()
     trainer_options = dict(
-        default_root_dir=tmpdir, checkpoint_callback=False, fast_dev_run=True, progress_bar_refresh_rate=0
+        default_root_dir=tmpdir, checkpoint_callback=False, fast_dev_run=True, enable_progress_bar=False
     )
 
     def assert_expected_calls(_trainer, model_callback, trainer_callback):
@@ -86,9 +86,7 @@ def configure_callbacks(self):
             return [model_callback_mock]
 
     model = TestModel()
-    trainer = Trainer(
-        default_root_dir=tmpdir, fast_dev_run=True, checkpoint_callback=False, progress_bar_refresh_rate=1
-    )
+    trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True, checkpoint_callback=False)
 
     callbacks_before_fit = trainer.callbacks.copy()
     assert callbacks_before_fit
diff --git a/tests/callbacks/test_early_stopping.py b/tests/callbacks/test_early_stopping.py
index 7cab0d8776056..fe6873c8f43bf 100644
--- a/tests/callbacks/test_early_stopping.py
+++ b/tests/callbacks/test_early_stopping.py
@@ -141,7 +141,7 @@ def validation_epoch_end(self, outputs):
         callbacks=[early_stop_callback],
         num_sanity_val_steps=0,
         max_epochs=10,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(model)
     assert trainer.current_epoch == expected_stop_epoch
@@ -177,7 +177,7 @@ def training_epoch_end(self, outputs):
         callbacks=[early_stop_callback],
         num_sanity_val_steps=0,
         max_epochs=10,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(model)
     assert trainer.current_epoch == expected_stop_epoch
@@ -444,7 +444,7 @@ def validation_step(self, batch, batch_idx):
         default_root_dir=tmpdir,
         limit_val_batches=1,
         callbacks=EarlyStopping(monitor="foo"),
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         **kwargs,
     )
 
diff --git a/tests/callbacks/test_finetuning_callback.py b/tests/callbacks/test_finetuning_callback.py
index c014c8e736874..31b8b0e160132 100644
--- a/tests/callbacks/test_finetuning_callback.py
+++ b/tests/callbacks/test_finetuning_callback.py
@@ -425,7 +425,7 @@ def forward(self, x):
         limit_train_batches=1,
         limit_val_batches=1,
         max_epochs=2,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         callbacks=[ckpt, BackboneFinetuning(unfreeze_backbone_at_epoch=1)],
     )
     trainer.fit(BackboneBoringModel())
@@ -436,7 +436,7 @@ def forward(self, x):
         limit_train_batches=1,
         limit_val_batches=1,
         max_epochs=3,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         callbacks=BackboneFinetuning(unfreeze_backbone_at_epoch=1),
         resume_from_checkpoint=ckpt.last_model_path,
     )
diff --git a/tests/callbacks/test_lr_monitor.py b/tests/callbacks/test_lr_monitor.py
index 32b2551245885..df84a1b186231 100644
--- a/tests/callbacks/test_lr_monitor.py
+++ b/tests/callbacks/test_lr_monitor.py
@@ -251,7 +251,7 @@ def configure_optimizers(self):
         limit_val_batches=0.1,
         limit_train_batches=0.5,
         callbacks=[lr_monitor],
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
     )
     trainer.fit(TestModel())
@@ -272,7 +272,7 @@ def configure_optimizers(self):
         limit_val_batches=2,
         limit_train_batches=2,
         callbacks=[lr_monitor],
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
     )
     trainer.fit(TestModel())
@@ -310,7 +310,7 @@ def configure_optimizers(self):
         limit_val_batches=2,
         limit_train_batches=2,
         callbacks=[lr_monitor],
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
     )
 
@@ -388,7 +388,7 @@ def finetune_function(self, pl_module, epoch: int, optimizer, opt_idx: int):
         limit_val_batches=0,
         limit_train_batches=2,
         callbacks=[TestFinetuning(), lr_monitor, Check()],
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         checkpoint_callback=False,
     )
diff --git a/tests/callbacks/test_progress_bar.py b/tests/callbacks/test_progress_bar.py
index 8cf7c0c5fd2b7..fe40150f92680 100644
--- a/tests/callbacks/test_progress_bar.py
+++ b/tests/callbacks/test_progress_bar.py
@@ -59,11 +59,19 @@ def test_progress_bar_on(tmpdir, callbacks: list, refresh_rate: Optional[int]):
     assert progress_bars[0] is trainer.progress_bar_callback
 
 
-@pytest.mark.parametrize("callbacks,refresh_rate", [([], 0), ([], False), ([ModelCheckpoint(dirpath="../trainer")], 0)])
-def test_progress_bar_off(tmpdir, callbacks: list, refresh_rate: Union[bool, int]):
+@pytest.mark.parametrize(
+    "callbacks,refresh_rate,enable_progress_bar",
+    [([], 0, True), ([], False, True), ([ModelCheckpoint(dirpath="../trainer")], 0, True), ([], 1, False)],
+)
+def test_progress_bar_off(tmpdir, callbacks: list, refresh_rate: Union[bool, int], enable_progress_bar: bool):
     """Test different ways the progress bar can be turned off."""
 
-    trainer = Trainer(default_root_dir=tmpdir, callbacks=callbacks, progress_bar_refresh_rate=refresh_rate)
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        callbacks=callbacks,
+        progress_bar_refresh_rate=refresh_rate,
+        enable_progress_bar=enable_progress_bar,
+    )
 
     progress_bars = [c for c in trainer.callbacks if isinstance(c, ProgressBar)]
     assert 0 == len(progress_bars)
diff --git a/tests/callbacks/test_pruning.py b/tests/callbacks/test_pruning.py
index cf02b0a4bce75..5c2f2d4d7b3de 100644
--- a/tests/callbacks/test_pruning.py
+++ b/tests/callbacks/test_pruning.py
@@ -107,7 +107,7 @@ def train_with_pruning_callback(
 
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         checkpoint_callback=False,
         logger=False,
@@ -225,7 +225,7 @@ def apply_lottery_ticket_hypothesis(self):
     )
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         checkpoint_callback=False,
         logger=False,
@@ -252,7 +252,7 @@ def test_multiple_pruning_callbacks(tmpdir, caplog, make_pruning_permanent: bool
 
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         checkpoint_callback=False,
         logger=False,
@@ -321,7 +321,7 @@ def on_save_checkpoint(self, trainer, pl_module, checkpoint):
     ckpt_callback = ModelCheckpoint(
         monitor="test", save_top_k=2, save_last=True, save_on_train_epoch_end=save_on_train_epoch_end
     )
-    trainer = Trainer(callbacks=[pruning_callback, ckpt_callback], max_epochs=3, progress_bar_refresh_rate=0)
+    trainer = Trainer(callbacks=[pruning_callback, ckpt_callback], max_epochs=3, enable_progress_bar=False)
     with caplog.at_level(INFO):
         trainer.fit(model)
 
diff --git a/tests/callbacks/test_stochastic_weight_avg.py b/tests/callbacks/test_stochastic_weight_avg.py
index 6800694eb3fcf..b2693ed5ded48 100644
--- a/tests/callbacks/test_stochastic_weight_avg.py
+++ b/tests/callbacks/test_stochastic_weight_avg.py
@@ -121,7 +121,7 @@ def train_with_swa(
 
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=max_epochs,
         limit_train_batches=5,
         limit_val_batches=0,
diff --git a/tests/checkpointing/test_checkpoint_callback_frequency.py b/tests/checkpointing/test_checkpoint_callback_frequency.py
index 12ec14712fc94..cb38ae8f0573f 100644
--- a/tests/checkpointing/test_checkpoint_callback_frequency.py
+++ b/tests/checkpointing/test_checkpoint_callback_frequency.py
@@ -43,7 +43,7 @@ def test_default_checkpoint_freq(save_mock, tmpdir, epochs: int, val_check_inter
         weights_summary=None,
         val_check_interval=val_check_interval,
         limit_val_batches=1,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(model)
 
@@ -119,7 +119,7 @@ def training_epoch_end(self, outputs) -> None:
     trainer = Trainer(
         callbacks=[callbacks.ModelCheckpoint(dirpath=tmpdir, monitor="my_loss_step", save_top_k=k, mode="max")],
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=epochs,
         weights_summary=None,
         val_check_interval=val_check_interval,
diff --git a/tests/checkpointing/test_model_checkpoint.py b/tests/checkpointing/test_model_checkpoint.py
index 0c1a6fbd51268..8102bbe3d7fb5 100644
--- a/tests/checkpointing/test_model_checkpoint.py
+++ b/tests/checkpointing/test_model_checkpoint.py
@@ -135,7 +135,7 @@ def on_validation_epoch_end(self):
         limit_train_batches=limit_train_batches,
         limit_val_batches=limit_val_batches,
         max_epochs=max_epochs,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(model)
     assert trainer.state.finished, f"Training failed with {trainer.state}"
@@ -236,7 +236,7 @@ def configure_optimizers(self):
         limit_val_batches=limit_val_batches,
         max_epochs=max_epochs,
         val_check_interval=val_check_interval,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         num_sanity_val_steps=0,
     )
     trainer.fit(model)
@@ -639,7 +639,7 @@ def test_ckpt_every_n_train_steps(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=2,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         callbacks=[checkpoint_callback],
         logger=False,
     )
@@ -666,7 +666,7 @@ def test_model_checkpoint_train_time_interval(mock_datetime, tmpdir) -> None:
         default_root_dir=tmpdir,
         min_epochs=num_epochs,
         max_epochs=num_epochs,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         callbacks=[
             ModelCheckpoint(
                 filename="{epoch}-{step}",
@@ -737,7 +737,7 @@ def test_ckpt_metric_names(tmpdir):
         max_epochs=1,
         gradient_clip_val=1.0,
         overfit_batches=0.20,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         limit_train_batches=0.01,
         limit_val_batches=0.01,
         callbacks=[ModelCheckpoint(monitor="early_stop_on", dirpath=tmpdir, filename="{val_loss:.2f}")],
@@ -758,7 +758,7 @@ def test_default_checkpoint_behavior(tmpdir):
 
     model = LogInTwoMethods()
     trainer = Trainer(
-        default_root_dir=tmpdir, max_epochs=3, progress_bar_refresh_rate=0, limit_train_batches=5, limit_val_batches=5
+        default_root_dir=tmpdir, max_epochs=3, enable_progress_bar=False, limit_train_batches=5, limit_val_batches=5
     )
 
     with patch.object(trainer, "save_checkpoint", wraps=trainer.save_checkpoint) as save_mock:
@@ -889,7 +889,7 @@ def validation_step(self, batch, batch_idx):
         limit_test_batches=2,
         callbacks=[checkpoint_callback],
         weights_summary=None,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(model)
     assert os.listdir(tmpdir) == ["epoch=00.ckpt"]
@@ -905,7 +905,7 @@ def validation_step(self, batch, batch_idx):
             limit_test_batches=2,
             resume_from_checkpoint=checkpoint_callback.best_model_path,
             weights_summary=None,
-            progress_bar_refresh_rate=0,
+            enable_progress_bar=False,
         )
         trainer.fit(model)
         trainer.test(model, verbose=False)
@@ -1041,7 +1041,7 @@ def test_val_check_interval_checkpoint_files(tmpdir):
         callbacks=[model_checkpoint],
         logger=False,
         weights_summary=None,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(model)
     files = {p.basename for p in tmpdir.listdir()}
@@ -1065,7 +1065,7 @@ def training_step(self, *args):
         callbacks=[model_checkpoint],
         logger=False,
         weights_summary=None,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(TestModel())
     assert model_checkpoint.current_score == 0.3
@@ -1098,7 +1098,7 @@ def training_step(self, *args):
         callbacks=[model_checkpoint],
         logger=False,
         weights_summary=None,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(TestModel())
     expected = float("inf" if mode == "min" else "-inf")
@@ -1122,7 +1122,7 @@ def __init__(self, hparams):
         callbacks=[model_checkpoint],
         logger=False,
         weights_summary=None,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     hp = {"test_hp_0": 1, "test_hp_1": 2}
     hp = OmegaConf.create(hp) if hparams_type == Container else Namespace(**hp)
@@ -1150,7 +1150,7 @@ def test_ckpt_version_after_rerun_new_trainer(tmpdir):
             callbacks=[mc],
             logger=False,
             weights_summary=None,
-            progress_bar_refresh_rate=0,
+            enable_progress_bar=False,
         )
         trainer.fit(BoringModel())
 
@@ -1176,7 +1176,7 @@ def test_ckpt_version_after_rerun_same_trainer(tmpdir):
         callbacks=[mc],
         logger=False,
         weights_summary=None,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(BoringModel())
     trainer.fit_loop.max_epochs = 4
diff --git a/tests/checkpointing/test_trainer_checkpoint.py b/tests/checkpointing/test_trainer_checkpoint.py
index 739dc98a22834..a617162a4daed 100644
--- a/tests/checkpointing/test_trainer_checkpoint.py
+++ b/tests/checkpointing/test_trainer_checkpoint.py
@@ -64,7 +64,7 @@ def validation_step(self, batch, batch_idx):
             limit_val_batches=12,
             limit_test_batches=12,
             resume_from_checkpoint=best_model_paths[-1],
-            progress_bar_refresh_rate=0,
+            enable_progress_bar=False,
         )
         trainer.fit(model)
         trainer.test()
diff --git a/tests/deprecated_api/test_remove_1-7.py b/tests/deprecated_api/test_remove_1-7.py
index 2fa8f96e77148..de4dba76b9c56 100644
--- a/tests/deprecated_api/test_remove_1-7.py
+++ b/tests/deprecated_api/test_remove_1-7.py
@@ -182,7 +182,7 @@ def on_keyboard_interrupt(self, trainer, pl_module):
         max_epochs=1,
         limit_val_batches=0.1,
         limit_train_batches=0.2,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         logger=False,
         default_root_dir=tmpdir,
     )
diff --git a/tests/loggers/test_base.py b/tests/loggers/test_base.py
index 0ada58ae0b74f..878ea1362b9ed 100644
--- a/tests/loggers/test_base.py
+++ b/tests/loggers/test_base.py
@@ -319,7 +319,7 @@ class _Test:
         limit_val_batches=0.1,
         num_sanity_val_steps=0,
         checkpoint_callback=False,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
     )
     # there should be no exceptions raised for the same key/value pair in the hparams of both
@@ -343,7 +343,7 @@ class _Test:
         limit_val_batches=0.1,
         num_sanity_val_steps=0,
         checkpoint_callback=False,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
     )
     with pytest.raises(MisconfigurationException, match="Error while merging hparams"):
@@ -360,7 +360,7 @@ class _Test:
         limit_val_batches=0.1,
         num_sanity_val_steps=0,
         checkpoint_callback=False,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
     )
     with pytest.raises(MisconfigurationException, match="Error while merging hparams"):
diff --git a/tests/loops/optimization/test_optimizer_loop.py b/tests/loops/optimization/test_optimizer_loop.py
index beaf0d6daaf40..a667072a7cdf2 100644
--- a/tests/loops/optimization/test_optimizer_loop.py
+++ b/tests/loops/optimization/test_optimizer_loop.py
@@ -120,7 +120,7 @@ def configure_optimizers(self):
     trainer = Trainer(
         default_root_dir=tmpdir,
         fast_dev_run=10,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(model)
 
diff --git a/tests/loops/test_loops.py b/tests/loops/test_loops.py
index 47145a2f8f408..c21351d48f54d 100644
--- a/tests/loops/test_loops.py
+++ b/tests/loops/test_loops.py
@@ -362,7 +362,7 @@ def configure_optimizers_multiple(self):
         limit_train_batches=n_batches,
         limit_val_batches=0,
         accumulate_grad_batches=accumulate_grad_batches,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         logger=False,
         checkpoint_callback=False,
     )
@@ -557,7 +557,7 @@ def configure_optimizers_multiple(self):
         limit_train_batches=n_batches,
         limit_val_batches=0,
         accumulate_grad_batches=accumulate_grad_batches,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         logger=False,
         checkpoint_callback=True,
     )
diff --git a/tests/loops/test_training_loop.py b/tests/loops/test_training_loop.py
index ae36e56495f93..7c0e99f69cabf 100644
--- a/tests/loops/test_training_loop.py
+++ b/tests/loops/test_training_loop.py
@@ -53,7 +53,7 @@ def training_epoch_end(self, outputs):
         limit_val_batches=1,
         limit_train_batches=2,
         limit_test_batches=1,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
     )
     trainer.fit(model)
diff --git a/tests/models/data/horovod/test_train_script.py b/tests/models/data/horovod/test_train_script.py
index ee77efeeb8675..ea59a82f96a1c 100644
--- a/tests/models/data/horovod/test_train_script.py
+++ b/tests/models/data/horovod/test_train_script.py
@@ -21,7 +21,7 @@ def test_horovod_model_script(tmpdir):
         default_root_dir=str(tmpdir),
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
diff --git a/tests/models/test_cpu.py b/tests/models/test_cpu.py
index c9d05ae5f3f42..18663562df626 100644
--- a/tests/models/test_cpu.py
+++ b/tests/models/test_cpu.py
@@ -108,7 +108,7 @@ def validation_step(self, *args, **kwargs):
         gradient_clip_val=1.0,
         overfit_batches=0.20,
         track_grad_norm=2,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         accumulate_grad_batches=2,
         limit_train_batches=0.1,
         limit_val_batches=0.1,
@@ -129,7 +129,7 @@ def test_multi_cpu_model_ddp(tmpdir):
 
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -159,7 +159,7 @@ def __init__(self, optimizer_name, learning_rate):
     trainer_options = dict(
         default_root_dir=tmpdir,
         max_epochs=1,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary="top",
         limit_train_batches=0.2,
         limit_val_batches=0.2,
@@ -176,7 +176,7 @@ def test_default_logger_callbacks_cpu_model(tmpdir):
         max_epochs=1,
         gradient_clip_val=1.0,
         overfit_batches=0.20,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         limit_train_batches=0.01,
         limit_val_batches=0.01,
     )
@@ -214,7 +214,7 @@ def test_step(self, *args, **kwargs):
     # fit model
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -258,7 +258,7 @@ def test_step(self, *args, **kwargs):
     # fit model
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -291,7 +291,7 @@ def test_simple_cpu(tmpdir):
 def test_cpu_model(tmpdir):
     """Make sure model trains on CPU."""
     trainer_options = dict(
-        default_root_dir=tmpdir, progress_bar_refresh_rate=0, max_epochs=1, limit_train_batches=4, limit_val_batches=4
+        default_root_dir=tmpdir, enable_progress_bar=False, max_epochs=1, limit_train_batches=4, limit_val_batches=4
     )
 
     model = BoringModel()
@@ -305,7 +305,7 @@ def test_all_features_cpu_model(tmpdir):
         gradient_clip_val=1.0,
         overfit_batches=0.20,
         track_grad_norm=2,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         accumulate_grad_batches=2,
         max_epochs=1,
         limit_train_batches=0.4,
diff --git a/tests/models/test_gpu.py b/tests/models/test_gpu.py
index 1faf4b820eae5..be70dd033b8a9 100644
--- a/tests/models/test_gpu.py
+++ b/tests/models/test_gpu.py
@@ -43,7 +43,7 @@ def test_multi_gpu_none_backend(tmpdir):
     tutils.set_random_master_port()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.2,
         limit_val_batches=0.2,
@@ -61,7 +61,7 @@ def test_single_gpu_model(tmpdir, gpus):
     """Make sure single GPU works (DP mode)."""
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.1,
         limit_val_batches=0.1,
diff --git a/tests/models/test_hooks.py b/tests/models/test_hooks.py
index 6ea8b76d253fa..470d3eb2b42f5 100644
--- a/tests/models/test_hooks.py
+++ b/tests/models/test_hooks.py
@@ -454,7 +454,7 @@ def training_step(self, batch, batch_idx):
         max_epochs=1,
         limit_train_batches=train_batches,
         limit_val_batches=val_batches,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         callbacks=[callback],
         **kwargs,
@@ -565,7 +565,7 @@ def test_trainer_model_hook_system_fit_no_val_and_resume(tmpdir):
         default_root_dir=tmpdir,
         max_steps=1,
         limit_val_batches=0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         callbacks=[HookedCallback([])],
     )
@@ -582,7 +582,7 @@ def test_trainer_model_hook_system_fit_no_val_and_resume(tmpdir):
         # already performed 1 step, now resuming to do an additional 2
         max_steps=(1 + train_batches),
         limit_val_batches=0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         resume_from_checkpoint=best_model_path,
         callbacks=[callback],
@@ -677,7 +677,7 @@ def test_trainer_model_hook_system_eval(tmpdir, batches, verb, noun, dataloader,
         max_epochs=1,
         limit_val_batches=batches,
         limit_test_batches=batches,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         callbacks=[callback],
     )
@@ -724,7 +724,7 @@ def test_trainer_model_hook_system_predict(tmpdir):
     callback = HookedCallback(called)
     batches = 2
     trainer = Trainer(
-        default_root_dir=tmpdir, limit_predict_batches=batches, progress_bar_refresh_rate=0, callbacks=[callback]
+        default_root_dir=tmpdir, limit_predict_batches=batches, enable_progress_bar=False, callbacks=[callback]
     )
     assert called == [
         dict(name="Callback.on_init_start", args=(trainer,)),
@@ -844,7 +844,7 @@ def call(hook, fn, *args, **kwargs):
         limit_val_batches=batches,
         limit_test_batches=batches,
         limit_predict_batches=batches,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         weights_summary=None,
         reload_dataloaders_every_epoch=True,
     )
diff --git a/tests/models/test_horovod.py b/tests/models/test_horovod.py
index c3f3cdcf7ffc2..ac4c0979c1b67 100644
--- a/tests/models/test_horovod.py
+++ b/tests/models/test_horovod.py
@@ -73,7 +73,7 @@ def test_horovod_cpu(tmpdir):
         default_root_dir=str(tmpdir),
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -91,7 +91,7 @@ def test_horovod_cpu_clip_grad_by_value(tmpdir):
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
         gradient_clip_algorithm="value",
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -108,7 +108,7 @@ def test_horovod_cpu_implicit(tmpdir):
         default_root_dir=str(tmpdir),
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -124,7 +124,7 @@ def test_horovod_multi_gpu(tmpdir):
         default_root_dir=str(tmpdir),
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -143,7 +143,7 @@ def test_horovod_multi_gpu_grad_by_value(tmpdir):
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
         gradient_clip_algorithm="value",
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -165,7 +165,7 @@ def test_horovod_apex(tmpdir):
         default_root_dir=str(tmpdir),
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -185,7 +185,7 @@ def test_horovod_amp(tmpdir):
         default_root_dir=str(tmpdir),
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -205,7 +205,7 @@ def test_horovod_gather(tmpdir):
         default_root_dir=str(tmpdir),
         weights_save_path=str(tmpdir),
         gradient_clip_val=1.0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -231,7 +231,7 @@ def validation_step(self, batch, *args, **kwargs):
 
     trainer_options = dict(
         default_root_dir=str(tmpdir),
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
@@ -249,7 +249,7 @@ def test_horovod_multi_optimizer(tmpdir):
     # fit model
     trainer = Trainer(
         default_root_dir=str(tmpdir),
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=0.4,
         limit_val_batches=0.2,
diff --git a/tests/models/test_onnx.py b/tests/models/test_onnx.py
index 59af0ffa831d7..fcce3d4bc86b7 100644
--- a/tests/models/test_onnx.py
+++ b/tests/models/test_onnx.py
@@ -97,7 +97,7 @@ def test_model_saves_on_multi_gpu(tmpdir):
         limit_val_batches=10,
         gpus=[0, 1],
         accelerator="ddp_spawn",
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
 
     model = BoringModel()
diff --git a/tests/models/test_restore.py b/tests/models/test_restore.py
index c9a784ed0a0f5..5a68f757e8744 100644
--- a/tests/models/test_restore.py
+++ b/tests/models/test_restore.py
@@ -220,7 +220,7 @@ def test_running_test_pretrained_model_distrib_dp(tmpdir):
     checkpoint = tutils.init_checkpoint_callback(logger)
 
     trainer_options = dict(
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         limit_train_batches=5,
         limit_val_batches=5,
@@ -266,7 +266,7 @@ def test_running_test_pretrained_model_distrib_ddp_spawn(tmpdir):
     checkpoint = tutils.init_checkpoint_callback(logger)
 
     trainer_options = dict(
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         limit_train_batches=2,
         limit_val_batches=2,
@@ -313,7 +313,7 @@ def test_running_test_pretrained_model_cpu(tmpdir):
     checkpoint = tutils.init_checkpoint_callback(logger)
 
     trainer_options = dict(
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         limit_train_batches=2,
         limit_val_batches=2,
@@ -345,7 +345,7 @@ def test_load_model_from_checkpoint(tmpdir, model_template):
     model = model_template()
 
     trainer_options = dict(
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         limit_train_batches=2,
         limit_val_batches=2,
diff --git a/tests/models/test_tpu.py b/tests/models/test_tpu.py
index 950c3577b89b9..dd4707fb324d3 100644
--- a/tests/models/test_tpu.py
+++ b/tests/models/test_tpu.py
@@ -62,7 +62,7 @@ def test_model_tpu_cores_1(tmpdir):
     tutils.reset_seed()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         tpu_cores=1,
         limit_train_batches=4,
@@ -81,7 +81,7 @@ def test_model_tpu_index(tmpdir, tpu_core):
     tutils.reset_seed()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         tpu_cores=[tpu_core],
         limit_train_batches=4,
@@ -100,7 +100,7 @@ def test_model_tpu_cores_8(tmpdir):
     tutils.reset_seed()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         tpu_cores=8,
         limit_train_batches=4,
@@ -120,7 +120,7 @@ def test_model_16bit_tpu_cores_1(tmpdir):
     trainer_options = dict(
         default_root_dir=tmpdir,
         precision=16,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         tpu_cores=1,
         limit_train_batches=8,
@@ -141,7 +141,7 @@ def test_model_16bit_tpu_index(tmpdir, tpu_core):
     trainer_options = dict(
         default_root_dir=tmpdir,
         precision=16,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         tpu_cores=[tpu_core],
         limit_train_batches=4,
@@ -162,7 +162,7 @@ def test_model_16bit_tpu_cores_8(tmpdir):
     trainer_options = dict(
         default_root_dir=tmpdir,
         precision=16,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         tpu_cores=8,
         limit_train_batches=4,
@@ -190,7 +190,7 @@ def validation_step(self, *args, **kwargs):
     trainer = Trainer(
         callbacks=[EarlyStopping(monitor="val_loss")],
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         limit_train_batches=2,
         limit_val_batches=2,
@@ -207,7 +207,7 @@ def test_tpu_grad_norm(tmpdir):
     tutils.reset_seed()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=4,
         tpu_cores=1,
         limit_train_batches=0.4,
@@ -226,7 +226,7 @@ def test_tpu_clip_grad_by_value(tmpdir):
     tutils.reset_seed()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=4,
         tpu_cores=1,
         limit_train_batches=10,
@@ -379,7 +379,7 @@ def test_tpu_precision_16_clip_gradients(mock_clip_grad_norm, clip_val, tmpdir):
     tutils.reset_seed()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         tpu_cores=1,
         precision=16,
@@ -437,7 +437,7 @@ def teardown(self, stage):
     tutils.reset_seed()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=4,
         tpu_cores=8,
         limit_train_batches=0.4,
@@ -464,7 +464,7 @@ def teardown(self, stage):
     tutils.reset_seed()
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=4,
         tpu_cores=8,
         limit_train_batches=0.4,
diff --git a/tests/plugins/test_deepspeed_plugin.py b/tests/plugins/test_deepspeed_plugin.py
index c7ccaab3e72f4..8354667e9f120 100644
--- a/tests/plugins/test_deepspeed_plugin.py
+++ b/tests/plugins/test_deepspeed_plugin.py
@@ -371,7 +371,7 @@ def on_before_accelerator_backend_setup(self, trainer, pl_module) -> None:
     model = BoringModel()
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         plugins=[DeepSpeedPlugin(config=deepspeed_zero_config)],
         precision=16,
@@ -723,7 +723,7 @@ def on_train_batch_start(
     verification_callback = VerificationCallback()
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         # TODO: this test fails with max_epochs >1 as there are leftover batches per epoch.
         # there's divergence in how Lightning handles the last batch of the epoch with how DeepSpeed does it.
         # we step the optimizers on the last batch but DeepSpeed keeps the accumulation for the next epoch
diff --git a/tests/profiler/test_profiler.py b/tests/profiler/test_profiler.py
index 8210804a46ddc..25726f64b049a 100644
--- a/tests/profiler/test_profiler.py
+++ b/tests/profiler/test_profiler.py
@@ -265,7 +265,7 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     model = BoringModel()
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=1,
         limit_train_batches=5,
         limit_val_batches=5,
diff --git a/tests/trainer/connectors/test_callback_connector.py b/tests/trainer/connectors/test_callback_connector.py
index 713344ae2b0e1..1703df4f859e9 100644
--- a/tests/trainer/connectors/test_callback_connector.py
+++ b/tests/trainer/connectors/test_callback_connector.py
@@ -122,7 +122,7 @@ def assert_composition(trainer_callbacks, model_callbacks, expected):
         model = LightningModule()
         model.configure_callbacks = lambda: model_callbacks
         trainer = Trainer(
-            checkpoint_callback=False, progress_bar_refresh_rate=0, weights_summary=None, callbacks=trainer_callbacks
+            checkpoint_callback=False, enable_progress_bar=False, weights_summary=None, callbacks=trainer_callbacks
         )
         trainer.model = model
         cb_connector = CallbackConnector(trainer)
diff --git a/tests/trainer/logging_/test_eval_loop_logging.py b/tests/trainer/logging_/test_eval_loop_logging.py
index e8b398bee8872..885027224a0e0 100644
--- a/tests/trainer/logging_/test_eval_loop_logging.py
+++ b/tests/trainer/logging_/test_eval_loop_logging.py
@@ -527,7 +527,6 @@ def test_step(self, batch, batch_idx):
         limit_val_batches=2,
         limit_test_batches=2,
         max_epochs=2,
-        progress_bar_refresh_rate=1,
     )
 
     # Train the model ⚡
@@ -598,7 +597,6 @@ def validation_step(self, batch, batch_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        progress_bar_refresh_rate=1,
     )
 
     trainer.fit(model)
diff --git a/tests/trainer/logging_/test_logger_connector.py b/tests/trainer/logging_/test_logger_connector.py
index d26471a715c2b..b20cc4812e0d3 100644
--- a/tests/trainer/logging_/test_logger_connector.py
+++ b/tests/trainer/logging_/test_logger_connector.py
@@ -361,7 +361,7 @@ def test_epoch_end(self, outputs):
             assert all(torch.equal(d["test"], torch.tensor([0, 1])) for d in outputs)  # check values
 
     model = TestModel()
-    trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=2, progress_bar_refresh_rate=0)
+    trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=2, enable_progress_bar=False)
     trainer.fit(model)
     trainer.validate(model)
     trainer.test(model)
@@ -510,7 +510,7 @@ def _assert_called(model, fn, stage):
         limit_val_batches=2,
         limit_test_batches=2,
         max_epochs=1,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         num_sanity_val_steps=2,
         checkpoint_callback=False,
     )
diff --git a/tests/trainer/optimization/test_optimizers.py b/tests/trainer/optimization/test_optimizers.py
index 2cd7e8f706a61..25a9c438319c3 100644
--- a/tests/trainer/optimization/test_optimizers.py
+++ b/tests/trainer/optimization/test_optimizers.py
@@ -542,7 +542,7 @@ def test_lr_scheduler_state_updated_before_saving(tmpdir, every_n_train_steps, e
     lr, gamma = 1, 10
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         logger=False,
         max_epochs=max_epochs,
         limit_train_batches=batches,
@@ -578,7 +578,7 @@ def test_plateau_scheduler_lr_step_interval_updated_after_saving(tmpdir, save_on
     batches = 4
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         logger=False,
         max_epochs=1,
         limit_train_batches=batches,
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index 5f1bdd1f34541..e159e2d899dc6 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -258,7 +258,7 @@ def on_train_batch_end(self, outputs, batch, batch_idx, *_):
         limit_train_batches=limit_train_batches,
         limit_val_batches=0,
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
 
     trainer.fit(model)
@@ -432,7 +432,7 @@ def on_load_checkpoint(self, _):
         callbacks=[ModelCheckpoint(dirpath=tmpdir, monitor="early_stop_on", save_top_k=-1)],
         default_root_dir=tmpdir,
         val_check_interval=1.0,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         logger=False,
         weights_summary=None,
     )
@@ -474,7 +474,7 @@ def test_trainer_max_steps_and_epochs(tmpdir):
         "max_steps": num_train_samples + 10,
         "logger": False,
         "weights_summary": None,
-        "progress_bar_refresh_rate": 0,
+        "enable_progress_bar": False,
     }
     trainer = Trainer(**trainer_kwargs)
     trainer.fit(model)
@@ -561,7 +561,7 @@ def test_trainer_min_steps_and_epochs(tmpdir):
         "min_steps": num_train_samples // 2,
         "logger": False,
         "weights_summary": None,
-        "progress_bar_refresh_rate": 0,
+        "enable_progress_bar": False,
     }
     trainer = Trainer(**trainer_kwargs)
     trainer.fit(model)
@@ -599,7 +599,7 @@ def training_step(self, batch, batch_idx):
     min_epochs = 5
     trainer = Trainer(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         min_epochs=min_epochs,
         limit_val_batches=0,
         limit_train_batches=2,
@@ -627,7 +627,7 @@ def test_trainer_max_steps_accumulate_batches(tmpdir):
         accumulate_grad_batches=10,
         logger=False,
         weights_summary=None,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
     trainer.fit(model)
 
@@ -677,7 +677,7 @@ def predict_step(self, batch, *_):
         limit_val_batches=1,
         limit_test_batches=1,
         limit_predict_batches=1,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         default_root_dir=tmpdir,
         callbacks=[ModelCheckpoint(monitor="foo", save_top_k=save_top_k)],
     )
@@ -748,7 +748,7 @@ def training_epoch_end(self, *args, **kwargs):
 
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         limit_train_batches=0.0,
         limit_val_batches=0.2,
@@ -811,7 +811,7 @@ def validation_epoch_end(self, *args, **kwargs):
 
     trainer_options = dict(
         default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         max_epochs=2,
         limit_train_batches=0.4,
         limit_val_batches=0.0,
@@ -925,7 +925,7 @@ def on_keyboard_interrupt(self, trainer, pl_module):
         max_epochs=1,
         limit_val_batches=0.1,
         limit_train_batches=0.2,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         logger=False,
         default_root_dir=tmpdir,
     )
@@ -1308,7 +1308,15 @@ def on_predict_epoch_end(self, trainer, pl_module, outputs):
 
 
 def predict(
-    tmpdir, accelerator, gpus, num_processes, model=None, plugins=None, datamodule=True, pbrr=None, use_callbacks=True
+    tmpdir,
+    accelerator,
+    gpus,
+    num_processes,
+    model=None,
+    plugins=None,
+    datamodule=True,
+    enable_progress_bar=True,
+    use_callbacks=True,
 ):
     dataloaders = [torch.utils.data.DataLoader(RandomDataset(32, 2)), torch.utils.data.DataLoader(RandomDataset(32, 2))]
 
@@ -1327,7 +1335,7 @@ def predict(
         gpus=gpus,
         num_processes=num_processes,
         plugins=plugins,
-        progress_bar_refresh_rate=pbrr,
+        enable_progress_bar=enable_progress_bar,
         callbacks=[cb, cb_1] if use_callbacks else [],
     )
     if accelerator == "ddp_spawn":
@@ -1379,10 +1387,10 @@ def predict_step(self, batch, batch_idx, dataloader_idx=None):
     assert x.expand_as(x).grad_fn is not None
 
 
-@pytest.mark.parametrize("progress_bar_refresh_rate", [0, 5, None])
+@pytest.mark.parametrize("enable_progress_bar", [False, True])
 @pytest.mark.parametrize("datamodule", [False, True])
-def test_trainer_predict_cpu(tmpdir, datamodule, progress_bar_refresh_rate):
-    predict(tmpdir, None, None, 1, datamodule=datamodule, pbrr=progress_bar_refresh_rate)
+def test_trainer_predict_cpu(tmpdir, datamodule, enable_progress_bar):
+    predict(tmpdir, None, None, 1, datamodule=datamodule, enable_progress_bar=enable_progress_bar)
 
 
 @RunIf(min_gpus=2, special=True)
@@ -1592,7 +1600,7 @@ def test_train_loop_system(tmpdir):
         limit_train_batches=5,
         limit_val_batches=1,
         limit_test_batches=1,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
     )
 
     class TestOptimizer(SGD):
@@ -1791,9 +1799,7 @@ def test_on_load_checkpoint_missing_callbacks(tmpdir):
     trainer = Trainer(default_root_dir=tmpdir, max_epochs=3, callbacks=[chk, CustomCallbackOnLoadCheckpoint()])
     trainer.fit(model)
 
-    trainer = Trainer(
-        default_root_dir=tmpdir, max_epochs=5, resume_from_checkpoint=chk.last_model_path, progress_bar_refresh_rate=1
-    )
+    trainer = Trainer(default_root_dir=tmpdir, max_epochs=5, resume_from_checkpoint=chk.last_model_path)
     with pytest.warns(UserWarning, match="CustomCallbackOnLoadCheckpoint"):
         trainer.fit(model)
 
@@ -1880,7 +1886,7 @@ def current_memory():
         fast_dev_run=True,
         gpus=1,
         accelerator="ddp",
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         callbacks=Check(),
     )
     trainer = Trainer(**trainer_kwargs)
diff --git a/tests/utilities/test_auto_restart.py b/tests/utilities/test_auto_restart.py
index 5500fe5393f27..e78403fba054a 100644
--- a/tests/utilities/test_auto_restart.py
+++ b/tests/utilities/test_auto_restart.py
@@ -941,7 +941,7 @@ def test_dataset_rng_states_restart_with_lightning(tmpdir, dataset_classes, mult
         default_root_dir=tmpdir,
         max_epochs=3,
         weights_summary=None,
-        progress_bar_refresh_rate=0,
+        enable_progress_bar=False,
         multiple_trainloader_mode=multiple_trainloader_mode,
     )
 

From 73afc01f30050cf2f39ab85f28d64ffb6556334f Mon Sep 17 00:00:00 2001
From: Danielle Pintz <daniellepintz@gmail.com>
Date: Thu, 23 Sep 2021 06:13:06 +0000
Subject: [PATCH 5/7] changelog

---
 CHANGELOG.md                                               | 2 +-
 pytorch_lightning/trainer/connectors/callback_connector.py | 2 --
 2 files changed, 1 insertion(+), 3 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 832f326654cca..fc0bcee5ac55d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -145,7 +145,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `RichModelSummary` callback ([#9546](https://github.com/PyTorchLightning/pytorch-lightning/pull/9546))
 
 
-- Added `enable_progress_bar` to Trainer constructor ([]())
+- Added `enable_progress_bar` to Trainer constructor ([#9664](https://github.com/PyTorchLightning/pytorch-lightning/pull/9664))
 
 ### Changed
 
diff --git a/pytorch_lightning/trainer/connectors/callback_connector.py b/pytorch_lightning/trainer/connectors/callback_connector.py
index c5d16885cb134..a4192c58bc77e 100644
--- a/pytorch_lightning/trainer/connectors/callback_connector.py
+++ b/pytorch_lightning/trainer/connectors/callback_connector.py
@@ -82,9 +82,7 @@ def on_trainer_init(
                 " will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.ProgressBar` with"
                 " `refresh_rate` directly to the Trainer's `callbacks` argument instead."
             )
-        import logging
 
-        logging.critical(enable_progress_bar)
         if enable_progress_bar:
             self.trainer._progress_bar_callback = self.configure_progress_bar(
                 progress_bar_refresh_rate, process_position

From ba016cfb9e683cdd73db062c8525966bcbb91274 Mon Sep 17 00:00:00 2001
From: Danielle Pintz <daniellepintz@gmail.com>
Date: Fri, 24 Sep 2021 00:41:08 +0000
Subject: [PATCH 6/7] update docs

---
 docs/source/common/trainer.rst                  | 17 +++++++++++++++++
 .../trainer/connectors/callback_connector.py    |  3 ++-
 pytorch_lightning/trainer/trainer.py            |  3 ++-
 3 files changed, 21 insertions(+), 2 deletions(-)

diff --git a/docs/source/common/trainer.rst b/docs/source/common/trainer.rst
index de37f5839e82b..9e7de8f928730 100644
--- a/docs/source/common/trainer.rst
+++ b/docs/source/common/trainer.rst
@@ -1281,6 +1281,10 @@ See the :doc:`profiler documentation <../advanced/profiler>`. for more details.
 
 progress_bar_refresh_rate
 ^^^^^^^^^^^^^^^^^^^^^^^^^
+``progress_bar_refresh_rate`` has been deprecated in v1.5 and will be removed in v1.7.
+Please pass :class:`~pytorch_lightning.callbacks.progress.ProgressBar` with ``refresh_rate``
+directly to the Trainer's ``callbacks`` argument instead. To disable the progress bar,
+pass ``enable_progress_bar = False`` to the Trainer.
 
 .. raw:: html
 
@@ -1305,6 +1309,19 @@ Note:
       Lightning will set it to 20 in these environments if the user does not provide a value.
     - This argument is ignored if a custom callback is passed to :paramref:`~Trainer.callbacks`.
 
+enable_progress_bar
+^^^^^^^^^^^^^^^^^^^
+
+Whether to enable or disable the progress bar. Defaults to True.
+
+.. testcode::
+
+    # default used by the Trainer
+    trainer = Trainer(enable_progress_bar=True)
+
+    # disable progress bar
+    trainer = Trainer(enable_progress_bar=False)
+
 reload_dataloaders_every_n_epochs
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
diff --git a/pytorch_lightning/trainer/connectors/callback_connector.py b/pytorch_lightning/trainer/connectors/callback_connector.py
index a4192c58bc77e..71ea37b2df947 100644
--- a/pytorch_lightning/trainer/connectors/callback_connector.py
+++ b/pytorch_lightning/trainer/connectors/callback_connector.py
@@ -80,7 +80,8 @@ def on_trainer_init(
             rank_zero_deprecation(
                 f"Setting `Trainer(progress_bar_refresh_rate={progress_bar_refresh_rate})` is deprecated in v1.5 and"
                 " will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.ProgressBar` with"
-                " `refresh_rate` directly to the Trainer's `callbacks` argument instead."
+                " `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress"
+                " bar pass `enable_progress_bar = False` to the Trainer."
             )
 
         if enable_progress_bar:
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index d47fe8f897aff..521ddbb0a623d 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -286,7 +286,8 @@ def __init__(
                 .. deprecated:: v1.5
                     ``progress_bar_refresh_rate`` has been deprecated in v1.5 and will be removed in v1.7.
                     Please pass :class:`~pytorch_lightning.callbacks.progress.ProgressBar` with ``refresh_rate``
-                    directly to the Trainer's ``callbacks`` argument instead.
+                    directly to the Trainer's ``callbacks`` argument instead. To disable the progress bar,
+                    pass ``enable_progress_bar = False`` to the Trainer.
 
             enable_progress_bar: Whether to enable to progress bar by default.
 

From 71027b14740465fab7da064b47facc08a12bc578 Mon Sep 17 00:00:00 2001
From: Danielle Pintz <daniellepintz@gmail.com>
Date: Fri, 24 Sep 2021 04:37:37 +0000
Subject: [PATCH 7/7] update changelog

---
 CHANGELOG.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 1090d418e33d5..bf4e121c68a2a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -265,7 +265,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `LightningLoggerBase.close`, `LoggerCollection.close` in favor of `LightningLoggerBase.finalize`, `LoggerCollection.finalize` ([#9422](https://github.com/PyTorchLightning/pytorch-lightning/pull/9422))
 
 
-- Deprecated passing `progress_bar_refresh_rate` to the `Trainer` constructor in favor of adding the `ProgressBar` callback with `refresh_rate` directly to the list of callbacks ([#9616](https://github.com/PyTorchLightning/pytorch-lightning/pull/9616))
+- Deprecated passing `progress_bar_refresh_rate` to the `Trainer` constructor in favor of adding the `ProgressBar` callback with `refresh_rate` directly to the list of callbacks, or passing `enable_progress_bar=False` to disable the progress bar ([#9616](https://github.com/PyTorchLightning/pytorch-lightning/pull/9616))
 
 
 ### Removed