0b3d2db9f3
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com> Co-authored-by: Aryan Kumar <156166681+aryan5v@users.noreply.github.com>
42 lines
1.7 KiB
Python
42 lines
1.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""VideoCaptionMergedDataset must not keep decoded pixels on its stored metadata."""
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import argparse
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import json
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import torch
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from fastvideo.dataset import getdataset
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def _dataset(tmp_path, clips: int):
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videos = tmp_path / "videos"
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videos.mkdir()
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annotations = []
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for i in range(clips):
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(videos / f"clip{i}.mp4").write_bytes(b"")
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annotations.append({"path": f"clip{i}.mp4", "cap": ["a caption"], "resolution": {"width": 32, "height": 32},
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"fps": 8, "duration": 1.0, "num_frames": 8})
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(tmp_path / "annotation.json").write_text(json.dumps(annotations))
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(tmp_path / "merge.txt").write_text(f"{videos},{tmp_path / 'annotation.json'}\n")
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args = argparse.Namespace(model_path=str(tmp_path / "no-model"), cache_dir=str(tmp_path), num_frames=8,
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train_fps=8, speed_factor=1.0, video_length_tolerance_range=5, drop_short_ratio=1.0,
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text_max_length=32, training_cfg_rate=0.0, max_height=32, max_width=32,
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do_temporal_sample=False, data_merge_path=str(tmp_path / "merge.txt"), seed=0)
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return getdataset(args)
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def test_iterating_does_not_retain_pixels_on_processed_batches(tmp_path, monkeypatch) -> None:
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dataset = _dataset(tmp_path, clips=3)
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def fake_decode(batch):
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batch.pixel_values = torch.zeros(3, 8, 32, 32)
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return batch
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monkeypatch.setattr(dataset.video_transform_stage, "process", fake_decode)
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items = list(dataset)
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assert len(items) == 3 and all(item["pixel_values"] is not None for item in items)
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assert all(batch.pixel_values is None for batch in dataset.processed_batches)
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