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https://github.com/facebookresearch/pytorch3d.git
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c3f8dad55c
Summary: Stats are logically connected to the training loop, not to the model. Hence, moving to the training loop. Also removing resume_epoch from OptimizerFactory in favor of a single place - ModelFactory. This removes the need for config consistency checks etc. Reviewed By: kjchalup Differential Revision: D38313475 fbshipit-source-id: a1d188a63e28459df381ff98ad8acdcdb14887b7
95 lines
3.6 KiB
Python
95 lines
3.6 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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import unittest
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from omegaconf import OmegaConf
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from pytorch3d.implicitron.models.feature_extractor.resnet_feature_extractor import (
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ResNetFeatureExtractor,
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)
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from pytorch3d.implicitron.models.generic_model import GenericModel
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from pytorch3d.implicitron.models.global_encoder.global_encoder import (
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SequenceAutodecoder,
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)
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from pytorch3d.implicitron.models.implicit_function.idr_feature_field import (
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IdrFeatureField,
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)
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from pytorch3d.implicitron.models.implicit_function.neural_radiance_field import (
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NeuralRadianceFieldImplicitFunction,
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)
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from pytorch3d.implicitron.models.renderer.lstm_renderer import LSTMRenderer
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from pytorch3d.implicitron.models.renderer.multipass_ea import (
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MultiPassEmissionAbsorptionRenderer,
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)
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from pytorch3d.implicitron.models.view_pooler.feature_aggregator import (
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AngleWeightedIdentityFeatureAggregator,
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)
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from pytorch3d.implicitron.tools.config import (
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get_default_args,
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remove_unused_components,
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)
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from tests.common_testing import get_tests_dir
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from .common_resources import provide_resnet34
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DATA_DIR = get_tests_dir() / "implicitron/data"
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DEBUG: bool = False
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# Tests the use of the config system in implicitron
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class TestGenericModel(unittest.TestCase):
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def setUp(self):
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self.maxDiff = None
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def test_create_gm(self):
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args = get_default_args(GenericModel)
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gm = GenericModel(**args)
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self.assertIsInstance(gm.renderer, MultiPassEmissionAbsorptionRenderer)
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self.assertIsInstance(
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gm._implicit_functions[0]._fn, NeuralRadianceFieldImplicitFunction
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)
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self.assertIsNone(gm.global_encoder)
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self.assertFalse(hasattr(gm, "implicit_function"))
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self.assertIsNone(gm.view_pooler)
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self.assertIsNone(gm.image_feature_extractor)
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def test_create_gm_overrides(self):
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provide_resnet34()
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args = get_default_args(GenericModel)
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args.view_pooler_enabled = True
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args.view_pooler_args.feature_aggregator_class_type = (
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"AngleWeightedIdentityFeatureAggregator"
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)
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args.image_feature_extractor_class_type = "ResNetFeatureExtractor"
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args.implicit_function_class_type = "IdrFeatureField"
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args.global_encoder_class_type = "SequenceAutodecoder"
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idr_args = args.implicit_function_IdrFeatureField_args
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idr_args.n_harmonic_functions_xyz = 1729
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args.renderer_class_type = "LSTMRenderer"
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gm = GenericModel(**args)
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self.assertIsInstance(gm.renderer, LSTMRenderer)
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self.assertIsInstance(
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gm.view_pooler.feature_aggregator,
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AngleWeightedIdentityFeatureAggregator,
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)
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self.assertIsInstance(gm._implicit_functions[0]._fn, IdrFeatureField)
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self.assertEqual(gm._implicit_functions[0]._fn.n_harmonic_functions_xyz, 1729)
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self.assertIsInstance(gm.global_encoder, SequenceAutodecoder)
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self.assertIsInstance(gm.image_feature_extractor, ResNetFeatureExtractor)
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self.assertFalse(hasattr(gm, "implicit_function"))
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instance_args = OmegaConf.structured(gm)
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if DEBUG:
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full_yaml = OmegaConf.to_yaml(instance_args, sort_keys=False)
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(DATA_DIR / "overrides_full.yaml").write_text(full_yaml)
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remove_unused_components(instance_args)
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yaml = OmegaConf.to_yaml(instance_args, sort_keys=False)
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if DEBUG:
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(DATA_DIR / "overrides_.yaml").write_text(yaml)
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self.assertEqual(yaml, (DATA_DIR / "overrides.yaml").read_text())
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