Download task01_picking_up_trash/code/tests/test_contract.py from davidwdw/b1k: direct link, hf CLI and curl.
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4.59 kB
| import json | |
| import io | |
| from pathlib import Path | |
| import sys | |
| import msgpack | |
| import numpy as np | |
| sys.path.insert(0, str(Path(__file__).resolve().parents[1])) | |
| from gpt6_b1k.recording import sensor_only | |
| from gpt6_b1k.server import pack, unpack | |
| from gpt6_b1k.policy import TrashPolicy | |
| from gpt6_b1k.perception import held_can_evidence, refine_can | |
| from gpt6_b1k.motion import SkillFailure | |
| from run import summarize | |
| def test_privileged_fields_do_not_enter_policy_observations(): | |
| raw = {'robot::proprio': np.zeros(61), 'robot::head::rgb': np.zeros((4, 4, 3)), | |
| 'robot::head::depth_linear': np.ones((4, 4)), | |
| 'robot::head::seg_instance': np.ones((4, 4)), 'object_poses': {'can': [1, 2, 3]}, | |
| 'robot_global_pose': [0, 0, 0], 'q_score': 1.0} | |
| assert set(sensor_only(raw)) == {'robot::proprio', 'robot::head::rgb', 'robot::head::depth_linear'} | |
| def test_official_wire_arrays_roundtrip(): | |
| arrays = {'action': np.arange(23, dtype=np.float32), 'rgb': np.ones((3, 4, 3), dtype=np.uint8)} | |
| result = msgpack.unpackb(msgpack.packb(arrays, default=pack), object_hook=unpack, strict_map_key=False) | |
| for name, value in arrays.items(): | |
| np.testing.assert_array_equal(result[name], value) | |
| assert result[name].dtype == value.dtype | |
| def test_reset_clears_episode_memory(): | |
| policy = TrashPolicy(io.StringIO()) | |
| policy.objects = [dict(done=True)] | |
| policy.odom.pose[:] = 3 | |
| policy.gripper = -1 | |
| policy.reset() | |
| assert policy.objects == [] and policy.gripper == 1 | |
| np.testing.assert_array_equal(policy.odom.pose, np.zeros(3)) | |
| def test_open_gripper_is_not_mistaken_for_carried_can(): | |
| from types import SimpleNamespace | |
| p = np.zeros(61) | |
| p[49:51] = .05 | |
| assert held_can_evidence(SimpleNamespace(p=p)) == (False, 0) | |
| def test_physical_skill_failure_keeps_evaluation_actions_valid(): | |
| p = np.zeros(61) | |
| p[23] = p[48] = 1 # Valid end-effector quaternions. | |
| raw = {'robot::proprio': p} | |
| for camera in ('zed', 'left_realsense', 'right_realsense'): | |
| prefix = f'robot:{camera}_link:Camera:0::' | |
| raw[prefix+'rgb'] = np.zeros((16, 16, 3), dtype=np.uint8) | |
| raw[prefix+'depth_linear'] = np.ones((16, 16), dtype=np.float32) | |
| policy = TrashPolicy(io.StringIO()) | |
| policy.gripper = -1 | |
| def blocked_motion(): | |
| raise SkillFailure('Physical execution blocked') | |
| yield | |
| policy.generator = blocked_motion() | |
| for _ in range(2): | |
| action = policy.predict(raw) | |
| assert action.shape == (23,) and np.isfinite(action).all() | |
| assert action[22] == -1 | |
| assert policy.phase == 'unresolved_motion' | |
| def test_wrist_refinement_accepts_a_silver_can_lid(): | |
| from types import SimpleNamespace | |
| x, y = np.meshgrid(np.linspace(.70, .77, 20), np.linspace(-.34, -.27, 20)) | |
| cloud = np.stack((x, y, np.full_like(x, .12)), -1) | |
| # No RGB supplied: semantic identity was established in the preceding head | |
| # view, and the silver lid is refined from the local observed depth surface. | |
| d = refine_can(SimpleNamespace(cloud=lambda camera: cloud), [.735, -.305, .07]) | |
| assert d is not None | |
| np.testing.assert_allclose(d.center[:2], [.735, -.305], atol=.001) | |
| def test_short_or_partial_runs_cannot_claim_goal(tmp_path): | |
| (tmp_path/'manifest.json').write_text(json.dumps(dict(indices=list(range(20)), instance_ids=list(range(301,321)), diagnostic=True))) | |
| out = tmp_path/'instance_301/evaluation/json' | |
| out.mkdir(parents=True) | |
| (out/'picking_up_trash_301_0.json').write_text(json.dumps(dict(instance_id=301, q_score={'final':1.}, success=True, steps=1))) | |
| summarize(tmp_path) | |
| result = json.loads((tmp_path/'summary.json').read_text()) | |
| assert result['completed'] == 1 | |
| assert not result['complete'] and not result['target_achieved'] | |
| def test_complete_score_must_be_strictly_above_threshold(tmp_path): | |
| (tmp_path/'manifest.json').write_text(json.dumps(dict(indices=list(range(20)), instance_ids=list(range(301,321)), diagnostic=False))) | |
| out = tmp_path/'batch_000/evaluation/json' | |
| out.mkdir(parents=True) | |
| for i in range(301,321): | |
| (out/f'{i}.json').write_text(json.dumps(dict(instance_id=i, q_score={'final': .7}, success=False, steps=1))) | |
| summarize(tmp_path) | |
| result = json.loads((tmp_path/'summary.json').read_text()) | |
| assert result['complete'] and not result['target_achieved'] | |
| (out/'301.json').write_text(json.dumps(dict(instance_id=301, q_score={'final':1.}, success=True, steps=1))) | |
| summarize(tmp_path) | |
| assert json.loads((tmp_path/'summary.json').read_text())['target_achieved'] | |