[HIL-SERL]Remove overstrict pre-commit modifications (#1028)
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@@ -32,10 +32,7 @@ import torch
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from huggingface_hub import HfApi
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import lerobot
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from lerobot.common.datasets.lerobot_dataset import (
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LeRobotDataset,
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LeRobotDatasetMetadata,
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)
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from lerobot.common.datasets.lerobot_dataset import LeRobotDataset, LeRobotDatasetMetadata
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# We ported a number of existing datasets ourselves, use this to see the list:
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print("List of available datasets:")
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@@ -22,10 +22,7 @@ from pathlib import Path
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import torch
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from lerobot.common.datasets.lerobot_dataset import (
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LeRobotDataset,
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LeRobotDatasetMetadata,
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)
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from lerobot.common.datasets.lerobot_dataset import LeRobotDataset, LeRobotDatasetMetadata
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from lerobot.common.datasets.utils import dataset_to_policy_features
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from lerobot.common.policies.diffusion.configuration_diffusion import DiffusionConfig
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from lerobot.common.policies.diffusion.modeling_diffusion import DiffusionPolicy
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@@ -80,24 +77,7 @@ def main():
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# Load the previous action (-0.1), the next action to be executed (0.0),
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# and 14 future actions with a 0.1 seconds spacing. All these actions will be
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# used to supervise the policy.
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"action": [
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-0.1,
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0.0,
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.6,
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0.7,
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0.8,
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0.9,
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1.0,
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1.1,
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1.2,
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1.3,
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1.4,
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],
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"action": [-0.1, 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4],
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}
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# We can then instantiate the dataset with these delta_timestamps configuration.
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@@ -26,10 +26,7 @@ import math
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import torch
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from lerobot.common.datasets.lerobot_dataset import (
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LeRobotDataset,
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LeRobotDatasetMetadata,
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)
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from lerobot.common.datasets.lerobot_dataset import LeRobotDataset, LeRobotDatasetMetadata
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from lerobot.common.policies.diffusion.modeling_diffusion import DiffusionPolicy
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@@ -54,24 +51,7 @@ def main():
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# Load the previous action (-0.1), the next action to be executed (0.0),
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# and 14 future actions with a 0.1 seconds spacing. All these actions will be
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# used to calculate the loss.
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"action": [
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-0.1,
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0.0,
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.6,
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0.7,
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0.8,
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0.9,
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1.0,
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1.1,
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1.2,
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1.3,
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1.4,
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],
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"action": [-0.1, 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4],
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}
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# Load the last 10% of episodes of the dataset as a validation set.
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