Removed `process_position` argument from Trainer Class (#13071)

CHANGELOG.md

@@ -112,6 +112,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Removed
 
+- Removed the deprecated `process_position` argument from the `Trainer` constructor ([13071](https://github.com/PyTorchLightning/pytorch-lightning/pull/13071))
+
+
 - Removed the deprecated `checkpoint_callback` argument from the `Trainer` constructor ([#13027](https://github.com/PyTorchLightning/pytorch-lightning/pull/13027))
 
 

docs/source/common/trainer.rst

@@ -1214,31 +1214,6 @@ Half precision, or mixed precision, is the combined use of 32 and 16 bit floatin
         # turn on 16-bit
         trainer = Trainer(amp_backend="apex", amp_level="O2", precision=16, accelerator="gpu", devices=1)
 
-
-process_position
-^^^^^^^^^^^^^^^^
-
-.. warning:: ``process_position`` has been deprecated in v1.5 and will be removed in v1.7.
-    Please pass :class:`~pytorch_lightning.callbacks.progress.TQDMProgressBar` with ``process_position``
-    directly to the Trainer's ``callbacks`` argument instead.
-
-.. raw:: html
-
-    <video width="50%" max-width="400px" controls
-    poster="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/pl_docs/trainer_flags/thumb/process_position.jpg"
-    src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/pl_docs/trainer_flags/process_position.mp4"></video>
-
-|
-
-Orders the progress bar. Useful when running multiple trainers on the same node.
-
-.. testcode::
-
-    # default used by the Trainer
-    trainer = Trainer(process_position=0)
-
-.. note:: This argument is ignored if a custom callback is passed to :paramref:`~Trainer.callbacks`.
-
 profiler
 ^^^^^^^^
 

pytorch_lightning/trainer/connectors/callback_connector.py

@@ -45,7 +45,6 @@ class CallbackConnector:
         callbacks: Optional[Union[List[Callback], Callback]],
         enable_checkpointing: bool,
         enable_progress_bar: bool,
-        process_position: int,
         default_root_dir: Optional[str],
         weights_save_path: Optional[str],
         enable_model_summary: bool,
@@ -77,14 +76,7 @@ class CallbackConnector:
         self._configure_timer_callback(max_time)
 
         # init progress bar
-        if process_position != 0:
+        self._configure_progress_bar(enable_progress_bar)
-            rank_zero_deprecation(
-                f"Setting `Trainer(process_position={process_position})` is deprecated in v1.5 and will be removed"
-                " in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with"
-                " `process_position` directly to the Trainer's `callbacks` argument instead."
-            )
-
-        self._configure_progress_bar(process_position, enable_progress_bar)
 
         # configure the ModelSummary callback
         self._configure_model_summary_callback(enable_model_summary, weights_summary)
@@ -188,7 +180,7 @@ class CallbackConnector:
         self.trainer.callbacks.append(model_summary)
         self.trainer._weights_summary = weights_summary
 
-    def _configure_progress_bar(self, process_position: int = 0, enable_progress_bar: bool = True) -> None:
+    def _configure_progress_bar(self, enable_progress_bar: bool = True) -> None:
         progress_bars = [c for c in self.trainer.callbacks if isinstance(c, ProgressBarBase)]
         if len(progress_bars) > 1:
             raise MisconfigurationException(
@@ -210,7 +202,7 @@ class CallbackConnector:
             )
 
         if enable_progress_bar:
-            progress_bar_callback = TQDMProgressBar(process_position=process_position)
+            progress_bar_callback = TQDMProgressBar()
             self.trainer.callbacks.append(progress_bar_callback)
 
     def _configure_timer_callback(self, max_time: Optional[Union[str, timedelta, Dict[str, int]]] = None) -> None:

pytorch_lightning/trainer/trainer.py

@@ -137,7 +137,6 @@ class Trainer(
         default_root_dir: Optional[str] = None,
         gradient_clip_val: Optional[Union[int, float]] = None,
         gradient_clip_algorithm: Optional[str] = None,
-        process_position: int = 0,
         num_nodes: int = 1,
         num_processes: Optional[int] = None,  # TODO: Remove in 2.0
         devices: Optional[Union[List[int], str, int]] = None,
@@ -305,13 +304,6 @@ class Trainer(
             log_every_n_steps: How often to log within steps.
                 Default: ``50``.
 
-            process_position: Orders the progress bar when running multiple models on same machine.
-
-                .. deprecated:: v1.5
-                    ``process_position`` has been deprecated in v1.5 and will be removed in v1.7.
-                    Please pass :class:`~pytorch_lightning.callbacks.progress.TQDMProgressBar` with ``process_position``
-                    directly to the Trainer's ``callbacks`` argument instead.
-
             enable_progress_bar: Whether to enable to progress bar by default.
                 Default: ``False``.
 
@@ -508,7 +500,6 @@ class Trainer(
             callbacks,
             enable_checkpointing,
             enable_progress_bar,
-            process_position,
             default_root_dir,
             weights_save_path,
             enable_model_summary,

tests/deprecated_api/test_remove_1-7.py

@@ -61,11 +61,6 @@ def test_v1_7_0_on_interrupt(tmpdir):
         trainer.fit(model)
 
 
-def test_v1_7_0_process_position_trainer_constructor(tmpdir):
-    with pytest.deprecated_call(match=r"Setting `Trainer\(process_position=5\)` is deprecated in v1.5"):
-        _ = Trainer(process_position=5)
-
-
 def test_v1_7_0_flush_logs_every_n_steps_trainer_constructor(tmpdir):
     with pytest.deprecated_call(match=r"Setting `Trainer\(flush_logs_every_n_steps=10\)` is deprecated in v1.5"):
         _ = Trainer(flush_logs_every_n_steps=10)