Add docs

docs/source-pytorch/common/trainer.rst

@@ -1077,6 +1077,30 @@ With :func:`torch.inference_mode` disabled, you can enable the grad of your mode
     trainer = Trainer(inference_mode=False)
     trainer.validate(model)
 
+enable_autolog_hparams
+^^^^^^^^^^^^^^^^^^^^^^
+
+Whether to log hyperparameters at the start of a run. Defaults to True.
+
+.. testcode::
+
+    # default used by the Trainer
+    trainer = Trainer(enable_autolog_hparams=True)
+
+    # disable logging hyperparams
+    trainer = Trainer(enable_autolog_hparams=False)
+
+With the parameter set to false, you can add custom code to log hyperparameters.
+
+.. code-block:: python
+
+    model = LitModel()
+    trainer = Trainer(enable_autolog_hparams=False)
+    for logger in trainer.loggers:
+        if isinstance(logger, lightning.pytorch.loggers.CSVLogger):
+            logger.log_hyperparams(hparams_dict_1)
+        else:
+            logger.log_hyperparams(hparams_dict_2)
 
 -----
 

src/lightning/pytorch/trainer/trainer.py

@@ -128,7 +128,7 @@ def __init__(
         sync_batchnorm: bool = False,
         reload_dataloaders_every_n_epochs: int = 0,
         default_root_dir: Optional[_PATH] = None,
-        log_hyperparams_enabled: bool = True,
+        enable_autolog_hparams: bool = True,
     ) -> None:
         r"""Customize every aspect of training via flags.
 
@@ -291,7 +291,7 @@ def __init__(
                 Default: ``os.getcwd()``.
                 Can be remote file paths such as `s3://mybucket/path` or 'hdfs://path/'
 
-            log_hyperparams_enabled: Whether to log hyperparameters at the start of a run.
+            enable_autolog_hparams: Whether to log hyperparameters at the start of a run.
                 Default: ``True``.
 
         Raises:
@@ -500,7 +500,7 @@ def __init__(
             num_sanity_val_steps,
         )
 
-        self.log_hyperparams_enabled = log_hyperparams_enabled
+        self.enable_autolog_hparams = enable_autolog_hparams
 
     def fit(
         self,
@@ -969,7 +969,7 @@ def _run(
             call._call_lightning_module_hook(self, "on_fit_start")
 
         # only log hparams if enabled
-        if self.log_hyperparams_enabled:
+        if self.enable_autolog_hparams:
             _log_hyperparams(self)
 
         if self.strategy.restore_checkpoint_after_setup: