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简介

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改 LeRobot v3.0 数据集的任务文本（整体设一个默认任务，或按 episode 逐个覆盖），并把任务相关的四处元数据一起同步。包 lerobot datasets/dataset_tools.py:1404 modify_tasks（上游是原地改），默认先把数据集整目录拷到 output_path 再改拷贝，源保持不变。

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功能描述

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算子参数

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输入

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输入含义
dataset_path源 v3.0 数据集根目录
output_path接收改动的拷贝目标根目录；为 null 表示原地改源数据集（慎用）
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输出

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输出含义
resultSUCCESS / SKIPPED: output already exists / Failed: dataset_path is required / Failed: [<dataset_path>] <异常类型>: <信息>
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参数

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参数名称类型默认值描述
new_taskstr 或 NoneNone所有 episode 的默认任务文本
episode_tasksdict[int, str] 或 NoneNone按 episode 覆盖，{episode_index: task}，优先级高于 new_task
forceboolFalseTrue 表示输出已是 v3.0 也重新拷贝并改写
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注意事项

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调用示例

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\n Python\n \n
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1from __future__ import annotations\n2\n3import os\n4\n5import daft\n6from daft import col\n7\n8from daft.aihc.common.udf import aihc_udf\n9from daft.aihc.functions.embodied.lerobot.modify_tasks_udf import ModifyTasks\n10\n11if __name__ == \"__main__\":\n12    if os.getenv(\"DAFT_RUNNER\", \"native\") == \"ray\":\n13        import ray\n14        ray.init(dashboard_host=\"0.0.0.0\", ignore_reinit_error=True)\n15        daft.set_runner_ray()\n16    daft.set_execution_config(actor_udf_ready_timeout=6000, min_cpu_per_task=0)\n17\n18# 夹具可用 test/_helpers/lerobot_edit_fixture.py:build_tabular_dataset 生成\n19    samples = {\n20        \"dataset_path\": [\"/path/to/lerobot_dataset\"],\n21        \"output_path\": [\"/tmp/lerobot_tasks_out\"],\n22    }\n23    ds = daft.from_pydict(samples)\n24    ds = ds.with_column(\n25        \"result\",\n26        aihc_udf(\n27            ModifyTasks,\n28            construct_args={\n29                \"new_task\": \"统一任务\",\n30                \"episode_tasks\": {0: \"特例\"},\n31                \"force\": False,\n32            },\n33            num_cpus=1,\n34            concurrency=1,\n35            batch_size=1,\n36        )(col(\"dataset_path\"), col(\"output_path\")),\n37    )\n38    ds.show()
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