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add Dlabel script
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python examples/dataset/annotate.py \
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--repo-id lerobot/svla_so101_pickplace \
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--video-key observation.images.side \
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--model HuggingFaceTB/SmolVLM-Instruct \
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# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# env.py - Upload this to your Hub repository
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# Example: huggingface.co/your-username/test-kwargs-env
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import gymnasium as gym
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from gymnasium.vector import SyncVectorEnv
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def make_env(
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n_envs=1,
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use_async_envs=False,
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config_path=None,
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config_overrides=None,
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**kwargs,
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):
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"""
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Create vectorized CartPole environments with configurable options.
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Args:
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n_envs: Number of parallel environments
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use_async_envs: Whether to use AsyncVectorEnv or SyncVectorEnv
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config_path: Optional path to a config file (for demonstration)
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config_overrides: Optional dict of config overrides
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**kwargs: Additional configuration options
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Returns:
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dict mapping suite name to task environments
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"""
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# Merge all config sources for demonstration
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config = {}
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if config_overrides:
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config.update(config_overrides)
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config.update(kwargs)
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# Store config in a way the test can verify
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# In a real env, you'd use these to configure the simulation
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stored_config = {
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"config_path": config_path,
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"config_overrides": config_overrides,
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"extra_kwargs": kwargs,
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}
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def _mk():
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env = gym.make("CartPole-v1")
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# Attach config to env for test verification
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env.hub_config = stored_config
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return env
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Vec = gym.vector.AsyncVectorEnv if use_async_envs else SyncVectorEnv
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vec_env = Vec([_mk for _ in range(n_envs)])
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# Also attach to vector env for easy access in tests
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vec_env.hub_config = stored_config
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return {"cartpole_suite": {0: vec_env}}
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