Files
lerobot/tests/envs/test_robocasa_ordering.py
T
pepijn 9d00293f49 fix(pi052): make fitted FAST checkpoints portable
Package fitted tokenizer artifacts with processor pipelines so pretrained PI052 checkpoints restore their saved recipe and normalization state without refitting.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-24 09:57:10 +00:00

49 lines
1.8 KiB
Python

#!/usr/bin/env python
# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
from lerobot.envs.robocasa import RoboCasaEnv, convert_action
def test_robocasa_action_uses_openpi_checkpoint_order():
action = np.arange(12, dtype=np.float32)
converted = convert_action(action)
np.testing.assert_array_equal(converted["action.end_effector_position"], [0, 1, 2])
np.testing.assert_array_equal(converted["action.end_effector_rotation"], [3, 4, 5])
np.testing.assert_array_equal(converted["action.gripper_close"], [6])
np.testing.assert_array_equal(converted["action.base_motion"], [7, 8, 9, 10])
np.testing.assert_array_equal(converted["action.control_mode"], [11])
def test_robocasa_state_uses_openpi_checkpoint_order():
env = object.__new__(RoboCasaEnv)
env.obs_type = "pixels_agent_pos"
env.camera_name = []
raw_observation = {
"state.end_effector_position_relative": np.arange(0, 3),
"state.end_effector_rotation_relative": np.arange(3, 7),
"state.base_position": np.arange(7, 10),
"state.base_rotation": np.arange(10, 14),
"state.gripper_qpos": np.arange(14, 16),
}
observation = env._format_raw_obs(raw_observation)
np.testing.assert_array_equal(observation["agent_pos"], np.arange(16, dtype=np.float32))