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Summary: Moving SQL dataset to PyTorch3D. It has been extensively tested in pixar_replay. It requires SQLAlchemy 2.0, which is not supported in fbcode. So I exclude the sources and tests that depend on it from buck TARGETS. Reviewed By: bottler Differential Revision: D45086611 fbshipit-source-id: 0285f03e5824c0478c70ad13731525bb5ec7deef
247 lines
11 KiB
Python
247 lines
11 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 logging
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import os
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import unittest
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import torch
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from pytorch3d.implicitron.dataset.data_loader_map_provider import ( # noqa
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SequenceDataLoaderMapProvider,
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SimpleDataLoaderMapProvider,
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)
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from pytorch3d.implicitron.dataset.data_source import ImplicitronDataSource
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from pytorch3d.implicitron.dataset.sql_dataset import SqlIndexDataset # noqa
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from pytorch3d.implicitron.dataset.sql_dataset_provider import ( # noqa
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SqlIndexDatasetMapProvider,
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)
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from pytorch3d.implicitron.dataset.train_eval_data_loader_provider import (
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TrainEvalDataLoaderMapProvider,
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)
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from pytorch3d.implicitron.tools.config import get_default_args
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logger = logging.getLogger("pytorch3d.implicitron.dataset.sql_dataset")
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sh = logging.StreamHandler()
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logger.addHandler(sh)
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logger.setLevel(logging.DEBUG)
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_CO3D_SQL_DATASET_ROOT: str = os.getenv("CO3D_SQL_DATASET_ROOT", "")
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@unittest.skipUnless(_CO3D_SQL_DATASET_ROOT, "Run only if CO3D is available")
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class TestCo3dSqlDataSource(unittest.TestCase):
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def test_no_subsets(self):
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args = get_default_args(ImplicitronDataSource)
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args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
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args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
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provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
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provider_args.ignore_subsets = True
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dataset_args = provider_args.dataset_SqlIndexDataset_args
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dataset_args.pick_categories = ["skateboard"]
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dataset_args.limit_sequences_to = 1
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data_source = ImplicitronDataSource(**args)
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self.assertIsInstance(
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data_source.data_loader_map_provider, TrainEvalDataLoaderMapProvider
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)
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_, data_loaders = data_source.get_datasets_and_dataloaders()
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self.assertEqual(len(data_loaders.train), 202)
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for frame in data_loaders.train:
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self.assertIsNone(frame.frame_type)
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self.assertEqual(frame.image_rgb.shape[-1], 800) # check loading blobs
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break
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def test_subsets(self):
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args = get_default_args(ImplicitronDataSource)
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args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
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provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
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provider_args.subset_lists_path = (
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"skateboard/set_lists/set_lists_manyview_dev_0.json"
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)
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# this will naturally limit to one sequence (no need to limit by cat/sequence)
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dataset_args = provider_args.dataset_SqlIndexDataset_args
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dataset_args.remove_empty_masks = True
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for sampler_type in [
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"SimpleDataLoaderMapProvider",
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"SequenceDataLoaderMapProvider",
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"TrainEvalDataLoaderMapProvider",
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]:
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args.data_loader_map_provider_class_type = sampler_type
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data_source = ImplicitronDataSource(**args)
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_, data_loaders = data_source.get_datasets_and_dataloaders()
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self.assertEqual(len(data_loaders.train), 102)
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self.assertEqual(len(data_loaders.val), 100)
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self.assertEqual(len(data_loaders.test), 100)
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for split in ["train", "val", "test"]:
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for frame in data_loaders[split]:
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self.assertEqual(frame.frame_type, [split])
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# check loading blobs
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self.assertEqual(frame.image_rgb.shape[-1], 800)
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break
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def test_sql_subsets(self):
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args = get_default_args(ImplicitronDataSource)
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args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
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provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
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provider_args.subset_lists_path = "set_lists/set_lists_manyview_dev_0.sqlite"
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dataset_args = provider_args.dataset_SqlIndexDataset_args
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dataset_args.remove_empty_masks = True
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dataset_args.pick_categories = ["skateboard"]
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for sampler_type in [
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"SimpleDataLoaderMapProvider",
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"SequenceDataLoaderMapProvider",
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"TrainEvalDataLoaderMapProvider",
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]:
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args.data_loader_map_provider_class_type = sampler_type
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data_source = ImplicitronDataSource(**args)
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_, data_loaders = data_source.get_datasets_and_dataloaders()
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self.assertEqual(len(data_loaders.train), 102)
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self.assertEqual(len(data_loaders.val), 100)
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self.assertEqual(len(data_loaders.test), 100)
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for split in ["train", "val", "test"]:
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for frame in data_loaders[split]:
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self.assertEqual(frame.frame_type, [split])
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self.assertEqual(
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frame.image_rgb.shape[-1], 800
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) # check loading blobs
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break
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@unittest.skip("It takes 75 seconds; skipping by default")
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def test_huge_subsets(self):
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args = get_default_args(ImplicitronDataSource)
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args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
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args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
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provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
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provider_args.subset_lists_path = "set_lists/set_lists_fewview_dev.sqlite"
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dataset_args = provider_args.dataset_SqlIndexDataset_args
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dataset_args.remove_empty_masks = True
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data_source = ImplicitronDataSource(**args)
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_, data_loaders = data_source.get_datasets_and_dataloaders()
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self.assertEqual(len(data_loaders.train), 3158974)
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self.assertEqual(len(data_loaders.val), 518417)
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self.assertEqual(len(data_loaders.test), 518417)
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for split in ["train", "val", "test"]:
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for frame in data_loaders[split]:
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self.assertEqual(frame.frame_type, [split])
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self.assertEqual(frame.image_rgb.shape[-1], 800) # check loading blobs
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break
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def test_broken_subsets(self):
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args = get_default_args(ImplicitronDataSource)
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args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
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args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
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provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
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provider_args.subset_lists_path = "et_non_est"
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provider_args.dataset_SqlIndexDataset_args.pick_categories = ["skateboard"]
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with self.assertRaises(FileNotFoundError) as err:
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ImplicitronDataSource(**args)
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# check the hint text
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self.assertIn("Subset lists path given but not found", str(err.exception))
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def test_eval_batches(self):
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args = get_default_args(ImplicitronDataSource)
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args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
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args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
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provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
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provider_args.subset_lists_path = "set_lists/set_lists_manyview_dev_0.sqlite"
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provider_args.eval_batches_path = (
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"skateboard/eval_batches/eval_batches_manyview_dev_0.json"
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)
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dataset_args = provider_args.dataset_SqlIndexDataset_args
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dataset_args.remove_empty_masks = True
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dataset_args.pick_categories = ["skateboard"]
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data_source = ImplicitronDataSource(**args)
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_, data_loaders = data_source.get_datasets_and_dataloaders()
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self.assertEqual(len(data_loaders.train), 102)
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self.assertEqual(len(data_loaders.val), 100)
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self.assertEqual(len(data_loaders.test), 50)
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for split in ["train", "val", "test"]:
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for frame in data_loaders[split]:
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self.assertEqual(frame.frame_type, [split])
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self.assertEqual(frame.image_rgb.shape[-1], 800) # check loading blobs
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break
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def test_eval_batches_from_subset_list_name(self):
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args = get_default_args(ImplicitronDataSource)
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args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
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args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
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provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
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provider_args.subset_list_name = "manyview_dev_0"
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provider_args.category = "skateboard"
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dataset_args = provider_args.dataset_SqlIndexDataset_args
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dataset_args.remove_empty_masks = True
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data_source = ImplicitronDataSource(**args)
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dataset, data_loaders = data_source.get_datasets_and_dataloaders()
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self.assertListEqual(list(dataset.train.pick_categories), ["skateboard"])
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self.assertEqual(len(data_loaders.train), 102)
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self.assertEqual(len(data_loaders.val), 100)
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self.assertEqual(len(data_loaders.test), 50)
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for split in ["train", "val", "test"]:
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for frame in data_loaders[split]:
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self.assertEqual(frame.frame_type, [split])
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self.assertEqual(frame.image_rgb.shape[-1], 800) # check loading blobs
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break
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def test_frame_access(self):
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args = get_default_args(ImplicitronDataSource)
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args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
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args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
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provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
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provider_args.subset_lists_path = "set_lists/set_lists_manyview_dev_0.sqlite"
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dataset_args = provider_args.dataset_SqlIndexDataset_args
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dataset_args.remove_empty_masks = True
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dataset_args.pick_categories = ["skateboard"]
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frame_builder_args = dataset_args.frame_data_builder_FrameDataBuilder_args
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frame_builder_args.load_point_clouds = True
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frame_builder_args.box_crop = False # required for .meta
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data_source = ImplicitronDataSource(**args)
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dataset_map, _ = data_source.get_datasets_and_dataloaders()
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dataset = dataset_map["train"]
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for idx in [10, ("245_26182_52130", 22)]:
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example_meta = dataset.meta[idx]
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example = dataset[idx]
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self.assertIsNone(example_meta.image_rgb)
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self.assertIsNone(example_meta.fg_probability)
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self.assertIsNone(example_meta.depth_map)
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self.assertIsNone(example_meta.sequence_point_cloud)
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self.assertIsNotNone(example_meta.camera)
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self.assertIsNotNone(example.image_rgb)
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self.assertIsNotNone(example.fg_probability)
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self.assertIsNotNone(example.depth_map)
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self.assertIsNotNone(example.sequence_point_cloud)
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self.assertIsNotNone(example.camera)
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self.assertEqual(example_meta.sequence_name, example.sequence_name)
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self.assertEqual(example_meta.frame_number, example.frame_number)
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self.assertEqual(example_meta.frame_timestamp, example.frame_timestamp)
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self.assertEqual(example_meta.sequence_category, example.sequence_category)
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torch.testing.assert_close(example_meta.camera.R, example.camera.R)
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torch.testing.assert_close(example_meta.camera.T, example.camera.T)
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torch.testing.assert_close(
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example_meta.camera.focal_length, example.camera.focal_length
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)
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torch.testing.assert_close(
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example_meta.camera.principal_point, example.camera.principal_point
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)
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