[pre-commit.ci] auto fixes from pre-commit.com hooks
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@@ -22,13 +22,17 @@ def synced_hf_dataset_factory(hf_dataset_factory):
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@pytest.fixture(scope="module")
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def unsynced_hf_dataset_factory(synced_hf_dataset_factory):
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def _create_unsynced_hf_dataset(fps: int = 30, tolerance_s: float = 1e-4) -> Dataset:
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def _create_unsynced_hf_dataset(
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fps: int = 30, tolerance_s: float = 1e-4
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) -> Dataset:
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hf_dataset = synced_hf_dataset_factory(fps=fps)
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features = hf_dataset.features
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df = hf_dataset.to_pandas()
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dtype = df["timestamp"].dtype # This is to avoid pandas type warning
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# Modify a single timestamp just outside tolerance
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df.at[30, "timestamp"] = dtype.type(df.at[30, "timestamp"] + (tolerance_s * 1.1))
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df.at[30, "timestamp"] = dtype.type(
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df.at[30, "timestamp"] + (tolerance_s * 1.1)
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)
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unsynced_hf_dataset = Dataset.from_pandas(df, features=features)
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unsynced_hf_dataset.set_transform(hf_transform_to_torch)
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return unsynced_hf_dataset
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@@ -38,13 +42,17 @@ def unsynced_hf_dataset_factory(synced_hf_dataset_factory):
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@pytest.fixture(scope="module")
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def slightly_off_hf_dataset_factory(synced_hf_dataset_factory):
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def _create_slightly_off_hf_dataset(fps: int = 30, tolerance_s: float = 1e-4) -> Dataset:
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def _create_slightly_off_hf_dataset(
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fps: int = 30, tolerance_s: float = 1e-4
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) -> Dataset:
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hf_dataset = synced_hf_dataset_factory(fps=fps)
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features = hf_dataset.features
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df = hf_dataset.to_pandas()
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dtype = df["timestamp"].dtype # This is to avoid pandas type warning
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# Modify a single timestamp just inside tolerance
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df.at[30, "timestamp"] = dtype.type(df.at[30, "timestamp"] + (tolerance_s * 0.9))
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df.at[30, "timestamp"] = dtype.type(
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df.at[30, "timestamp"] + (tolerance_s * 0.9)
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)
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unsynced_hf_dataset = Dataset.from_pandas(df, features=features)
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unsynced_hf_dataset.set_transform(hf_transform_to_torch)
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return unsynced_hf_dataset
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@@ -54,8 +62,12 @@ def slightly_off_hf_dataset_factory(synced_hf_dataset_factory):
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@pytest.fixture(scope="module")
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def valid_delta_timestamps_factory():
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def _create_valid_delta_timestamps(fps: int = 30, keys: list = DUMMY_MOTOR_FEATURES) -> dict:
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delta_timestamps = {key: [i * (1 / fps) for i in range(-10, 10)] for key in keys}
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def _create_valid_delta_timestamps(
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fps: int = 30, keys: list = DUMMY_MOTOR_FEATURES
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) -> dict:
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delta_timestamps = {
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key: [i * (1 / fps) for i in range(-10, 10)] for key in keys
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}
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return delta_timestamps
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return _create_valid_delta_timestamps
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@@ -153,7 +165,9 @@ def test_check_timestamps_sync_slightly_off(slightly_off_hf_dataset_factory):
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def test_check_timestamps_sync_single_timestamp():
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single_timestamp_hf_dataset = Dataset.from_dict({"timestamp": [0.0], "episode_index": [0]})
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single_timestamp_hf_dataset = Dataset.from_dict(
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{"timestamp": [0.0], "episode_index": [0]}
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)
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single_timestamp_hf_dataset.set_transform(hf_transform_to_torch)
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episode_data_index = {"to": torch.tensor([1]), "from": torch.tensor([0])}
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fps = 30
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@@ -202,7 +216,9 @@ def test_check_delta_timestamps_valid(valid_delta_timestamps_factory):
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def test_check_delta_timestamps_slightly_off(slightly_off_delta_timestamps_factory):
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fps = 30
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tolerance_s = 1e-4
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slightly_off_delta_timestamps = slightly_off_delta_timestamps_factory(fps, tolerance_s)
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slightly_off_delta_timestamps = slightly_off_delta_timestamps_factory(
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fps, tolerance_s
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)
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result = check_delta_timestamps(
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delta_timestamps=slightly_off_delta_timestamps,
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fps=fps,
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