Hard population of registry system with pre_expand

Summary: Provide an extension point pre_expand to let a configurable class A make sure another class B is registered before A is expanded. This reduces top level imports.

Reviewed By: bottler

Differential Revision: D44504122

fbshipit-source-id: c418bebbe6d33862d239be592d9751378eee3a62

pytorch3d/implicitron/dataset/data_source.py

@@ -13,13 +13,8 @@
 )
 from pytorch3d.renderer.cameras import CamerasBase
 
-from .blender_dataset_map_provider import BlenderDatasetMapProvider  # noqa
 from .data_loader_map_provider import DataLoaderMap, DataLoaderMapProviderBase
 from .dataset_map_provider import DatasetMap, DatasetMapProviderBase
-from .json_index_dataset_map_provider import JsonIndexDatasetMapProvider  # noqa
-from .json_index_dataset_map_provider_v2 import JsonIndexDatasetMapProviderV2  # noqa
-from .llff_dataset_map_provider import LlffDatasetMapProvider  # noqa
-from .rendered_mesh_dataset_map_provider import RenderedMeshDatasetMapProvider  # noqa
 
 
 class DataSourceBase(ReplaceableBase):
@@ -60,6 +55,26 @@ class ImplicitronDataSource(DataSourceBase):  # pyre-ignore[13]
     data_loader_map_provider: DataLoaderMapProviderBase
     data_loader_map_provider_class_type: str = "SequenceDataLoaderMapProvider"
 
+    @classmethod
+    def pre_expand(cls) -> None:
+        # use try/finally to bypass cinder's lazy imports
+        try:
+            from .blender_dataset_map_provider import (  # noqa: F401
+                BlenderDatasetMapProvider,
+            )
+            from .json_index_dataset_map_provider import (  # noqa: F401
+                JsonIndexDatasetMapProvider,
+            )
+            from .json_index_dataset_map_provider_v2 import (  # noqa: F401
+                JsonIndexDatasetMapProviderV2,
+            )
+            from .llff_dataset_map_provider import LlffDatasetMapProvider  # noqa: F401
+            from .rendered_mesh_dataset_map_provider import (  # noqa: F401
+                RenderedMeshDatasetMapProvider,
+            )
+        finally:
+            pass
+
     def __post_init__(self):
         run_auto_creation(self)
         self._all_train_cameras_cache: Optional[Tuple[Optional[CamerasBase]]] = None

pytorch3d/implicitron/models/generic_model.py

@@ -20,23 +20,8 @@
     ImplicitronRender,
 )
 from pytorch3d.implicitron.models.feature_extractor import FeatureExtractorBase
-from pytorch3d.implicitron.models.feature_extractor.resnet_feature_extractor import (  # noqa
-    ResNetFeatureExtractor,
-)
 from pytorch3d.implicitron.models.global_encoder.global_encoder import GlobalEncoderBase
 from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase
-from pytorch3d.implicitron.models.implicit_function.idr_feature_field import (  # noqa
-    IdrFeatureField,
-)
-from pytorch3d.implicitron.models.implicit_function.neural_radiance_field import (  # noqa
-    NeRFormerImplicitFunction,
-)
-from pytorch3d.implicitron.models.implicit_function.scene_representation_networks import (  # noqa
-    SRNHyperNetImplicitFunction,
-)
-from pytorch3d.implicitron.models.implicit_function.voxel_grid_implicit_function import (  # noqa
-    VoxelGridImplicitFunction,
-)
 from pytorch3d.implicitron.models.metrics import (
     RegularizationMetricsBase,
     ViewMetricsBase,
@@ -50,14 +35,7 @@
     RendererOutput,
     RenderSamplingMode,
 )
-from pytorch3d.implicitron.models.renderer.lstm_renderer import LSTMRenderer  # noqa
-from pytorch3d.implicitron.models.renderer.multipass_ea import (  # noqa
-    MultiPassEmissionAbsorptionRenderer,
-)
 from pytorch3d.implicitron.models.renderer.ray_sampler import RaySamplerBase
-from pytorch3d.implicitron.models.renderer.sdf_renderer import (  # noqa
-    SignedDistanceFunctionRenderer,
-)
 
 from pytorch3d.implicitron.models.utils import (
     apply_chunked,
@@ -315,6 +293,37 @@ class GenericModel(ImplicitronModelBase):  # pyre-ignore: 13
         ]
     )
 
+    @classmethod
+    def pre_expand(cls) -> None:
+        # use try/finally to bypass cinder's lazy imports
+        try:
+            from pytorch3d.implicitron.models.feature_extractor.resnet_feature_extractor import (  # noqa: F401, B950
+                ResNetFeatureExtractor,
+            )
+            from pytorch3d.implicitron.models.implicit_function.idr_feature_field import (  # noqa: F401, B950
+                IdrFeatureField,
+            )
+            from pytorch3d.implicitron.models.implicit_function.neural_radiance_field import (  # noqa: F401, B950
+                NeRFormerImplicitFunction,
+            )
+            from pytorch3d.implicitron.models.implicit_function.scene_representation_networks import (  # noqa: F401, B950
+                SRNHyperNetImplicitFunction,
+            )
+            from pytorch3d.implicitron.models.implicit_function.voxel_grid_implicit_function import (  # noqa: F401, B950
+                VoxelGridImplicitFunction,
+            )
+            from pytorch3d.implicitron.models.renderer.lstm_renderer import (  # noqa: F401
+                LSTMRenderer,
+            )
+            from pytorch3d.implicitron.models.renderer.multipass_ea import (  # noqa
+                MultiPassEmissionAbsorptionRenderer,
+            )
+            from pytorch3d.implicitron.models.renderer.sdf_renderer import (  # noqa: F401
+                SignedDistanceFunctionRenderer,
+            )
+        finally:
+            pass
+
     def __post_init__(self):
         if self.view_pooler_enabled:
             if self.image_feature_extractor_class_type is None:

pytorch3d/implicitron/models/overfit_model.py

@@ -258,6 +258,31 @@ class OverfitModel(ImplicitronModelBase):  # pyre-ignore: 13
         ]
     )
 
+    @classmethod
+    def pre_expand(cls) -> None:
+        # use try/finally to bypass cinder's lazy imports
+        try:
+            from pytorch3d.implicitron.models.implicit_function.idr_feature_field import (  # noqa: F401, B950
+                IdrFeatureField,
+            )
+            from pytorch3d.implicitron.models.implicit_function.neural_radiance_field import (  # noqa: F401, B950
+                NeuralRadianceFieldImplicitFunction,
+            )
+            from pytorch3d.implicitron.models.implicit_function.scene_representation_networks import (  # noqa: F401, B950
+                SRNImplicitFunction,
+            )
+            from pytorch3d.implicitron.models.renderer.lstm_renderer import (  # noqa: F401
+                LSTMRenderer,
+            )
+            from pytorch3d.implicitron.models.renderer.multipass_ea import (  # noqa: F401
+                MultiPassEmissionAbsorptionRenderer,
+            )
+            from pytorch3d.implicitron.models.renderer.sdf_renderer import (  # noqa: F401
+                SignedDistanceFunctionRenderer,
+            )
+        finally:
+            pass
+
     def __post_init__(self):
         # The attribute will be filled by run_auto_creation
         run_auto_creation(self)

pytorch3d/implicitron/tools/config.py

@@ -185,6 +185,7 @@ def __post_init__(self):
 IMPL_SUFFIX: str = "_impl"
 TWEAK_SUFFIX: str = "_tweak_args"
 _DATACLASS_INIT: str = "__dataclass_own_init__"
+PRE_EXPAND_NAME: str = "pre_expand"
 
 
 class ReplaceableBase:
@@ -838,6 +839,9 @@ def x_tweak_args(cls, member_type: Type, args: DictConfig) -> None
     In addition, if the class inherits torch.nn.Module, the generated __init__ will
     call torch.nn.Module's __init__ before doing anything else.
 
+    Before any transformation of the class, if the class has a classmethod called
+    `pre_expand`, it will be called with no arguments.
+
     Note that although the *_args members are intended to have type DictConfig, they
     are actually internally annotated as dicts. OmegaConf is happy to see a DictConfig
     in place of a dict, but not vice-versa. Allowing dict lets a class user specify
@@ -858,6 +862,9 @@ def x_tweak_args(cls, member_type: Type, args: DictConfig) -> None
     if _is_actually_dataclass(some_class):
         return some_class
 
+    if hasattr(some_class, PRE_EXPAND_NAME):
+        getattr(some_class, PRE_EXPAND_NAME)()
+
     # The functions this class's run_auto_creation will run.
     creation_functions: List[str] = []
     # The classes which this type knows about from the registry

tests/implicitron/test_config.py

@@ -10,6 +10,7 @@
 from dataclasses import dataclass, field, is_dataclass
 from enum import Enum
 from typing import Any, Dict, List, Optional, Tuple
+from unittest.mock import Mock
 
 from omegaconf import DictConfig, ListConfig, OmegaConf, ValidationError
 from pytorch3d.implicitron.tools.config import (
@@ -805,6 +806,39 @@ def __post_init__(self):
 
         self.assertEqual(control_args, ["Orange", "Orange", True, True])
 
+    def test_pre_expand(self):
+        # Check that the precreate method of a class is called once before
+        # when expand_args_fields is called on the class.
+
+        class A(Configurable):
+            n: int = 9
+
+            @classmethod
+            def pre_expand(cls):
+                pass
+
+        A.pre_expand = Mock()
+        expand_args_fields(A)
+        A.pre_expand.assert_called()
+
+    def test_pre_expand_replaceable(self):
+        # Check that the precreate method of a class is called once before
+        # when expand_args_fields is called on the class.
+
+        class A(ReplaceableBase):
+            pass
+
+            @classmethod
+            def pre_expand(cls):
+                pass
+
+        class A1(A):
+            n: 9
+
+        A.pre_expand = Mock()
+        expand_args_fields(A1)
+        A.pre_expand.assert_called()
+
 
 @dataclass(eq=False)
 class MockDataclass: