Remove the unused utilities.parsing.flatten_dict

src/lightning/pytorch/CHANGELOG.md

@@ -226,6 +226,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed the unused `lightning.pytorch.utilities.finite_checks.print_nan_gradients` function ([#16682](https://github.com/Lightning-AI/lightning/pull/16682))
 - Removed the unused `lightning.pytorch.utilities.finite_checks.detect_nan_parameters` function ([#16682](https://github.com/Lightning-AI/lightning/pull/16682))
+- Removed the unused `lightning.pytorch.utilities.parsing.flatten_dict` function ([#16744](https://github.com/Lightning-AI/lightning/pull/16744))
+- Removed the unused `lightning.pytorch.utilities.metrics.metrics_to_scalars` function ([#16681](https://github.com/Lightning-AI/lightning/pull/16681))
+- Removed the unused `lightning.pytorch.utilities.supporters.{SharedCycleIteratorState,CombinedLoaderIterator}` classes ([#16714](https://github.com/Lightning-AI/lightning/pull/16714))
 
 
 - Tuner removal
@@ -241,8 +244,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed the `using_lbfgs` argument from `LightningModule.optimizer_step` hook ([#16538](https://github.com/Lightning-AI/lightning/pull/16538))
 
+
 - Removed the `Trainer.data_parallel` property. Use `isinstance(trainer.strategy, ParallelStrategy)` instead ([#16703](https://github.com/Lightning-AI/lightning/pull/16703))
 
+
 - Removed support for multiple optimizers in automatic optimization mode ([#16539](https://github.com/Lightning-AI/lightning/pull/16539))
   * Removed `opt_idx` argument from `BaseFinetuning.finetune_function` callback method
   * Removed `opt_idx` argument from `Callback.on_before_optimizer_step` callback method
@@ -265,13 +270,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed `PrecisionPlugin.dispatch` ([#16618](https://github.com/Lightning-AI/lightning/pull/16618))
 
-- Removed the unused `lightning.pytorch.utilities.metrics.metrics_to_scalars` function ([#16681](https://github.com/Lightning-AI/lightning/pull/16681))
-
-- Removed the unused `lightning.pytorch.utilities.supporters.{SharedCycleIteratorState,CombinedLoaderIterator}` classes ([#16714](https://github.com/Lightning-AI/lightning/pull/16714))
-
 ### Fixed
 
--
+- Fixed an attribute error and improved input validation for invalid strategy types being passed to Trainer ([#16693](https://github.com/Lightning-AI/lightning/pull/16693))
 
 
 - Fixed early stopping triggering extra validation runs after reaching `min_epochs` or `min_steps` ([#16719](https://github.com/Lightning-AI/lightning/pull/16719))
@@ -289,8 +290,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed the batch_sampler reference for DataLoaders wrapped with XLA's MpDeviceLoader ([#16571](https://github.com/Lightning-AI/lightning/pull/16571))
 - Fixed an import error when `torch.distributed` is not available ([#16658](https://github.com/Lightning-AI/lightning/pull/16658))
 
-- Fixed an attribute error and improved input validation for invalid strategy types being passed to Trainer ([#16693](https://github.com/Lightning-AI/lightning/pull/16693))
-
 
 ## [1.9.0] - 2023-01-17
 

src/lightning/pytorch/utilities/__init__.py

@@ -26,7 +26,7 @@
     _TORCHVISION_AVAILABLE,
 )
 from lightning.pytorch.utilities.parameter_tying import find_shared_parameters, set_shared_parameters  # noqa: F401
-from lightning.pytorch.utilities.parsing import AttributeDict, flatten_dict, is_picklable  # noqa: F401
+from lightning.pytorch.utilities.parsing import AttributeDict, is_picklable  # noqa: F401
 from lightning.pytorch.utilities.rank_zero import (  # noqa: F401
     rank_zero_deprecation,
     rank_zero_info,

src/lightning/pytorch/utilities/parsing.py

@@ -189,19 +189,6 @@ def collect_init_args(
     return path_args
 
 
-def flatten_dict(source: Dict[str, Any], result: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
-    if result is None:
-        result = {}
-
-    for k, v in source.items():
-        if isinstance(v, dict):
-            _ = flatten_dict(v, result)
-        else:
-            result[k] = v
-
-    return result
-
-
 def save_hyperparameters(
     obj: Any, *args: Any, ignore: Optional[Union[Sequence[str], str]] = None, frame: Optional[types.FrameType] = None
 ) -> None:

tests/tests_pytorch/utilities/test_parsing.py

@@ -21,7 +21,6 @@
     AttributeDict,
     clean_namespace,
     collect_init_args,
-    flatten_dict,
     get_init_args,
     is_picklable,
     lightning_getattr,
@@ -296,11 +295,3 @@ def test_attribute_dict(tmpdir):
     ad = AttributeDict({"key1": 1})
     ad.key1 = 123
     assert ad.key1 == 123
-
-
-def test_flatten_dict(tmpdir):
-    d = {"1": 1, "_": {"2": 2, "_": {"3": 3, "4": 4}}}
-
-    expected = {"1": 1, "2": 2, "3": 3, "4": 4}
-
-    assert flatten_dict(d) == expected