79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
# TODO(aliberts): Mute logging for these tests
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import subprocess
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from pathlib import Path
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def _find_and_replace(text: str, finds_and_replaces: list[tuple[str, str]]) -> str:
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for f, r in finds_and_replaces:
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assert f in text
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text = text.replace(f, r)
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return text
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def _run_script(path):
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subprocess.run(["python", path], check=True)
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def test_example_1():
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path = "examples/1_load_hugging_face_dataset.py"
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_run_script(path)
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assert Path("outputs/examples/1_load_hugging_face_dataset/episode_5.mp4").exists()
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def test_example_2():
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path = "examples/2_load_lerobot_dataset.py"
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_run_script(path)
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assert Path("outputs/examples/2_load_lerobot_dataset/episode_5.mp4").exists()
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def test_examples_4_and_3():
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"""
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Train a model with example 3, check the outputs.
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Evaluate the trained model with example 2, check the outputs.
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"""
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path = "examples/4_train_policy.py"
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with open(path) as file:
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file_contents = file.read()
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# Do less steps, use smaller batch, use CPU, and don't complicate things with dataloader workers.
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file_contents = _find_and_replace(
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file_contents,
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[
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("training_steps = 5000", "training_steps = 1"),
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("num_workers=4", "num_workers=0"),
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('device = torch.device("cuda")', 'device = torch.device("cpu")'),
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("batch_size=cfg.batch_size", "batch_size=1"),
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],
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)
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# Pass empty globals to allow dictionary comprehension https://stackoverflow.com/a/32897127/4391249.
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exec(file_contents, {})
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for file_name in ["model.pt", "stats.pth", "config.yaml"]:
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assert Path(f"outputs/train/example_pusht_diffusion/{file_name}").exists()
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path = "examples/3_evaluate_pretrained_policy.py"
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with open(path) as file:
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file_contents = file.read()
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# Do less evals, use CPU, and use the local model.
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file_contents = _find_and_replace(
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file_contents,
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[
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('"eval_episodes=10"', '"eval_episodes=1"'),
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('"rollout_batch_size=10"', '"rollout_batch_size=1"'),
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('"device=cuda"', '"device=cpu"'),
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(
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'# folder = Path("outputs/train/example_pusht_diffusion")',
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'folder = Path("outputs/train/example_pusht_diffusion")',
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),
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('hub_id = "lerobot/diffusion_policy_pusht_image"', ""),
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("folder = Path(snapshot_download(hub_id)", ""),
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],
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)
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assert Path("outputs/train/example_pusht_diffusion").exists()
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