Removed flush_logs_every_n_steps argument from Trainer (#13074)

Co-authored-by: Carlos Mocholí <[email protected]>

Author: shenoynikhil

CHANGELOG.md

@@ -120,6 +120,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Removed
 
+- Removed the deprecated `flush_logs_every_n_steps` argument from the `Trainer` constructor ([#13074](https://github.com/PyTorchLightning/pytorch-lightning/pull/13074))
+
+
 - Removed the deprecated `process_position` argument from the `Trainer` constructor ([13071](https://github.com/PyTorchLightning/pytorch-lightning/pull/13071))
 
 

docs/source/common/trainer.rst

@@ -695,30 +695,6 @@ impact to subsequent runs. These are the changes enabled:
 - Disables the Tuner.
 - If using the CLI, the configuration file is not saved.
 
-flush_logs_every_n_steps
-^^^^^^^^^^^^^^^^^^^^^^^^
-
-.. warning:: ``flush_logs_every_n_steps`` has been deprecated in v1.5 and will be removed in v1.7.
-    Please configure flushing directly in the logger 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/flush_logs%E2%80%A8_every_n_steps.jpg"
-    src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/pl_docs/trainer_flags/flush_logs_every_n_steps.mp4"></video>
-
-|
-
-Writes logs to disk this often.
-
-.. testcode::
-
-    # default used by the Trainer
-    trainer = Trainer(flush_logs_every_n_steps=100)
-
-See Also:
-    - :doc:`logging <../extensions/logging>`
-
 .. _gpus:
 
 gpus

docs/source/visualize/logging_advanced.rst

@@ -49,20 +49,19 @@ To change this behaviour, set the *log_every_n_steps* :class:`~pytorch_lightning
 Modify flushing frequency
 =========================
 
-Metrics are kept in memory for N steps to improve training efficiency. Every N steps, metrics flush to disk. To change the frequency of this flushing, use the *flush_logs_every_n_steps* Trainer argument.
+Some loggers keep logged metrics in memory for N steps and only periodically flush them to disk to improve training efficiency.
+Every logger handles this a bit differently. For example, here is how to fine-tune flushing for the TensorBoard logger:
 
 .. code-block:: python
 
-    # faster training, high memory
-    Trainer(flush_logs_every_n_steps=500)
+    # Default used by TensorBoard: Write to disk after 10 logging events or every two minutes
+    logger = TensorBoardLogger(..., max_queue=10, flush_secs=120)
 
-    # slower training, low memory
-    Trainer(flush_logs_every_n_steps=500)
+    # Faster training, more memory used
+    logger = TensorBoardLogger(..., max_queue=100)
 
-The higher *flush_logs_every_n_steps* is, the faster the model will train but the memory will build up until the next flush.
-The smaller *flush_logs_every_n_steps* is, the slower the model will train but memory will be kept to a minimum.
-
-TODO: chart
+    # Slower training, less memory used
+    logger = TensorBoardLogger(..., max_queue=1)
 
 ----
 

pytorch_lightning/loops/epoch/training_epoch_loop.py

@@ -528,9 +528,7 @@ def _should_check_val_fx(self, batch_idx: int, is_last_batch: bool) -> bool:
 
     def _save_loggers_on_train_batch_end(self) -> None:
         """Flushes loggers to disk."""
-        # this assumes that `batches_that_stepped` was increased before
-        should_flush = self._batches_that_stepped % self.trainer.flush_logs_every_n_steps == 0
-        if should_flush or self.trainer.should_stop:
+        if self.trainer.should_stop:
             for logger in self.trainer.loggers:
                 logger.save()
 

pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py

@@ -43,19 +43,10 @@ def __init__(self, trainer: "pl.Trainer") -> None:
     def on_trainer_init(
         self,
         logger: Union[bool, Logger, Iterable[Logger]],
-        flush_logs_every_n_steps: Optional[int],
         log_every_n_steps: int,
         move_metrics_to_cpu: bool,
     ) -> None:
         self.configure_logger(logger)
-        if flush_logs_every_n_steps is not None:
-            rank_zero_deprecation(
-                f"Setting `Trainer(flush_logs_every_n_steps={flush_logs_every_n_steps})` is deprecated in v1.5 "
-                "and will be removed in v1.7. Please configure flushing in the logger instead."
-            )
-        else:
-            flush_logs_every_n_steps = 100  # original default parameter
-        self.trainer.flush_logs_every_n_steps = flush_logs_every_n_steps
         self.trainer.log_every_n_steps = log_every_n_steps
         self.trainer.move_metrics_to_cpu = move_metrics_to_cpu
         for logger in self.trainer.loggers:

pytorch_lightning/trainer/trainer.py

@@ -159,7 +159,6 @@ def __init__(
         limit_test_batches: Optional[Union[int, float]] = None,
         limit_predict_batches: Optional[Union[int, float]] = None,
         val_check_interval: Optional[Union[int, float]] = None,
-        flush_logs_every_n_steps: Optional[int] = None,
         log_every_n_steps: int = 50,
         accelerator: Optional[Union[str, Accelerator]] = None,
         strategy: Optional[Union[str, Strategy]] = None,
@@ -260,12 +259,6 @@ def __init__(
                 of train, val and test to find any bugs (ie: a sort of unit test).
                 Default: ``False``.
 
-            flush_logs_every_n_steps: How often to flush logs to disk (defaults to every 100 steps).
-
-                .. deprecated:: v1.5
-                    ``flush_logs_every_n_steps`` has been deprecated in v1.5 and will be removed in v1.7.
-                    Please configure flushing directly in the logger instead.
-
             gpus: Number of GPUs to train on (int) or which GPUs to train on (list or str) applied per node
                 Default: ``None``.
 
@@ -555,7 +548,7 @@ def __init__(
 
         # init logger flags
         self._loggers: List[Logger]
-        self._logger_connector.on_trainer_init(logger, flush_logs_every_n_steps, log_every_n_steps, move_metrics_to_cpu)
+        self._logger_connector.on_trainer_init(logger, log_every_n_steps, move_metrics_to_cpu)
 
         # init debugging flags
         self.val_check_interval: Union[int, float]

tests/deprecated_api/test_remove_1-7.py

@@ -61,11 +61,6 @@ def on_keyboard_interrupt(self, trainer, pl_module):
         trainer.fit(model)
 
 
-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)
-
-
 class BoringCallbackDDPSpawnModel(BoringModel):
     def add_to_queue(self, queue):
         ...