Remove deprecated mode argument from ModelSummary

CHANGELOG.md

@@ -113,6 +113,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed deprecated `utilities.distributed.rank_zero_{warn/deprecation}` ([#10451](https://github.com/PyTorchLightning/pytorch-lightning/pull/10451))
 
 
+- Removed deprecated `mode` argument from `ModelSummary` class ([#10449](https://github.com/PyTorchLightning/pytorch-lightning/pull/10449))
+
+
 - Removed deprecated `Trainer.train_loop` property in favor of `Trainer.fit_loop` ([#10482](https://github.com/PyTorchLightning/pytorch-lightning/pull/10482))
 
 

pytorch_lightning/core/lightning.py

@@ -1689,19 +1689,14 @@ def tbptt_split_batch(self, batch, split_size):
 
         return splits
 
-    def summarize(self, mode: Optional[str] = "top", max_depth: Optional[int] = None) -> Optional[ModelSummary]:
+    def summarize(self, max_depth: int = 1) -> ModelSummary:
         """Summarize this LightningModule.
 
         .. deprecated:: v1.5
             This method was deprecated in v1.5 in favor of `pytorch_lightning.utilities.model_summary.summarize`
             and will be removed in v1.7.
 
         Args:
-            mode: Can be either ``'top'`` (summarize only direct submodules) or ``'full'`` (summarize all layers).
-
-                .. deprecated:: v1.4
-                    This parameter was deprecated in v1.4 in favor of `max_depth` and will be removed in v1.6.
-
             max_depth: The maximum depth of layer nesting that the summary will include. A value of 0 turns the
                 layer summary off. Default: 1.
 
@@ -1714,7 +1709,7 @@ def summarize(self, mode: Optional[str] = "top", max_depth: Optional[int] = None
             stacklevel=6,
         )
 
-        return summarize(self, mode, max_depth)
+        return summarize(self, max_depth)
 
     def freeze(self) -> None:
         r"""

pytorch_lightning/utilities/model_summary.py

@@ -23,8 +23,7 @@
 from torch.utils.hooks import RemovableHandle
 
 import pytorch_lightning as pl
-from pytorch_lightning.utilities import AMPType, DeviceType, ModelSummaryMode, rank_zero_deprecation
-from pytorch_lightning.utilities.exceptions import MisconfigurationException
+from pytorch_lightning.utilities import AMPType, DeviceType
 from pytorch_lightning.utilities.imports import _TORCH_GREATER_EQUAL_1_8
 from pytorch_lightning.utilities.warnings import WarningCache
 
@@ -130,13 +129,6 @@ class ModelSummary:
 
     Args:
         model: The model to summarize (also referred to as the root module).
-        mode: Can be one of
-
-            - `top` (default): only the top-level modules will be recorded (the children of the root module)
-            - `full`: summarizes all layers and their submodules in the root module
-
-            .. deprecated:: v1.4
-                This parameter was deprecated in v1.4 in favor of `max_depth` and will be removed in v1.6.
 
         max_depth: Maximum depth of modules to show. Use -1 to show all modules or 0 to show no
             summary. Defaults to 1.
@@ -186,22 +178,9 @@ class ModelSummary:
         0.530     Total estimated model params size (MB)
     """
 
-    def __init__(self, model: "pl.LightningModule", mode: Optional[str] = None, max_depth: Optional[int] = 1) -> None:
+    def __init__(self, model: "pl.LightningModule", max_depth: int = 1) -> None:
         self._model = model
 
-        # temporary mapping from mode to max_depth
-        if max_depth is None or mode is not None:
-            if mode in ModelSummaryMode.supported_types():
-                max_depth = ModelSummaryMode.get_max_depth(mode)
-                rank_zero_deprecation(
-                    "Argument `mode` in `ModelSummary` is deprecated in v1.4"
-                    f" and will be removed in v1.6. Use `max_depth={max_depth}` to replicate `mode={mode}` behaviour."
-                )
-            else:
-                raise MisconfigurationException(
-                    f"`mode` can be {', '.join(ModelSummaryMode.supported_types())}, got {mode}."
-                )
-
         if not isinstance(max_depth, int) or max_depth < -1:
             raise ValueError(f"`max_depth` can be -1, 0 or > 0, got {max_depth}.")
 
@@ -436,40 +415,16 @@ def _is_lazy_weight_tensor(p: Tensor) -> bool:
     return False
 
 
-def summarize(
-    lightning_module: "pl.LightningModule", mode: Optional[str] = None, max_depth: Optional[int] = None
-) -> ModelSummary:
+def summarize(lightning_module: "pl.LightningModule", max_depth: int = 1) -> ModelSummary:
     """Summarize the LightningModule specified by `lightning_module`.
 
     Args:
         lightning_module: `LightningModule` to summarize.
-        mode: Can be either ``'top'`` (summarize only direct submodules) or ``'full'`` (summarize all layers).
-
-            .. deprecated:: v1.4
-                This parameter was deprecated in v1.4 in favor of `max_depth` and will be removed in v1.6.
 
         max_depth: The maximum depth of layer nesting that the summary will include. A value of 0 turns the
             layer summary off. Default: 1.
 
     Return:
         The model summary object
     """
-
-    # temporary mapping from mode to max_depth
-    if max_depth is None:
-        if mode is None:
-            model_summary = ModelSummary(lightning_module, max_depth=1)
-        elif mode in ModelSummaryMode.supported_types():
-            max_depth = ModelSummaryMode.get_max_depth(mode)
-            rank_zero_deprecation(
-                "Argument `mode` in `LightningModule.summarize` is deprecated in v1.4"
-                f" and will be removed in v1.6. Use `max_depth={max_depth}` to replicate `mode={mode}` behavior."
-            )
-            model_summary = ModelSummary(lightning_module, max_depth=max_depth)
-        else:
-            raise MisconfigurationException(
-                f"`mode` can be None, {', '.join(ModelSummaryMode.supported_types())}, got {mode}"
-            )
-    else:
-        model_summary = ModelSummary(lightning_module, max_depth=max_depth)
-    return model_summary
+    return ModelSummary(lightning_module, max_depth=max_depth)

tests/deprecated_api/test_remove_1-6.py

@@ -18,7 +18,6 @@
 
 from pytorch_lightning import Trainer
 from pytorch_lightning.utilities.model_helpers import is_overridden
-from pytorch_lightning.utilities.model_summary import ModelSummary
 from tests.helpers import BoringModel
 
 
@@ -69,15 +68,6 @@ def test_v1_6_0_is_overridden_model():
         assert not is_overridden("foo", model=model)
 
 
-def test_v1_6_0_deprecated_model_summary_mode(tmpdir):
-    model = BoringModel()
-    with pytest.deprecated_call(match="Argument `mode` in `ModelSummary` is deprecated in v1.4"):
-        ModelSummary(model, mode="top")
-
-    with pytest.deprecated_call(match="Argument `mode` in `LightningModule.summarize` is deprecated in v1.4"):
-        model.summarize(mode="top")
-
-
 def test_v1_6_0_deprecated_disable_validation():
     trainer = Trainer()
     with pytest.deprecated_call(match="disable_validation` is deprecated in v1.4"):

tests/utilities/test_model_summary.py

@@ -143,17 +143,11 @@ def test_invalid_weights_summmary():
     """Test that invalid value for weights_summary raises an error."""
     model = LightningModule()
 
-    with pytest.raises(MisconfigurationException, match="`mode` can be None, .* got temp"):
-        summarize(model, mode="temp")
-
     with pytest.raises(
         MisconfigurationException, match="`weights_summary` can be None, .* got temp"
     ), pytest.deprecated_call(match="weights_summary=temp)` is deprecated"):
         Trainer(weights_summary="temp")
 
-    with pytest.raises(MisconfigurationException, match="mode` can be .* got temp"):
-        ModelSummary(model, mode="temp")
-
     with pytest.raises(ValueError, match="max_depth` can be .* got temp"):
         ModelSummary(model, max_depth="temp")
 
@@ -334,21 +328,6 @@ def test_lazy_model_summary():
             assert summary.trainable_parameters == 7
 
 
-def test_max_depth_equals_mode_interface():
-    """Test summarize(model, full/top) interface mapping matches max_depth."""
-    model = DeepNestedModel()
-
-    with pytest.deprecated_call(match="mode` in `LightningModule.summarize` is deprecated"):
-        summary_top = summarize(model, mode="top")
-    summary_0 = summarize(model, max_depth=1)
-    assert str(summary_top) == str(summary_0)
-
-    with pytest.deprecated_call(match="mode` in `LightningModule.summarize` is deprecated"):
-        summary_full = summarize(model, mode="full")
-    summary_minus1 = summarize(model, max_depth=-1)
-    assert str(summary_full) == str(summary_minus1)
-
-
 @pytest.mark.parametrize("max_depth", [-1, 0, 1, 3, 999])
 def test_max_depth_param(max_depth):
     """Test that only the modules up to the desired depth are shown."""