mirror of
https://github.com/huggingface/lerobot.git
synced 2026-07-16 14:32:03 +00:00
Pepijn
76 lines
2.6 KiB
Python
76 lines
2.6 KiB
Python
# Copyright 2026 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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from types import SimpleNamespace
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from unittest.mock import MagicMock
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import pytest
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import torch
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from lerobot.runtime.cli import _build_rollout_runtime_io, _parse_args
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def test_parse_args_preserves_rollout_robot_overrides():
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args = _parse_args(
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[
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"--policy.path=checkpoint",
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"--robot.type=so101_follower",
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"--robot.calibration_dir=/tmp/calibration",
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]
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)
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assert args.robot_type == "so101_follower"
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assert "--robot.calibration_dir=/tmp/calibration" in args.raw_argv
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def test_parse_args_rejects_removed_dataset_replay_flags():
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with pytest.raises(SystemExit):
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_parse_args(["--policy.path=checkpoint", "--dataset.repo_id=dataset"])
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def test_rollout_runtime_io_uses_context_processors():
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robot = MagicMock()
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robot.robot_type = "mock_robot"
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robot.cameras = {}
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robot.get_observation.return_value = {"joint.pos": 1.5}
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ctx = SimpleNamespace(
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hardware=SimpleNamespace(robot_wrapper=robot),
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runtime=SimpleNamespace(cfg=SimpleNamespace(device="cpu")),
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processors=SimpleNamespace(
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robot_observation_processor=lambda observation: observation,
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robot_action_processor=lambda pair: pair[0],
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),
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policy=SimpleNamespace(
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preprocessor=lambda observation: observation,
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postprocessor=lambda action: action,
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),
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data=SimpleNamespace(
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dataset_features={
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"observation.state": {
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"dtype": "float32",
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"shape": (1,),
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"names": ["joint.pos"],
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},
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"action": {"dtype": "float32", "shape": (1,), "names": ["joint.pos"]},
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}
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),
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)
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provider, executor = _build_rollout_runtime_io(ctx, rerun_log=False, get_task=lambda: "move")
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observation = provider()
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executor(torch.tensor([[2.0]]))
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assert observation["observation.state"].shape == (1, 1)
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robot.send_action.assert_called_once_with({"joint.pos": 2.0})
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