seeker
47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
import runpy
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from pathlib import Path
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import numpy as np
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import pytest
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SCRIPT = runpy.run_path(
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str(Path(__file__).resolve().parents[1] / "scripts" / "build_complete_comparison.py")
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)
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_decode_action = SCRIPT["_decode_action"]
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_extract_component = SCRIPT["_extract_component"]
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_prediction_metrics = SCRIPT["_prediction_metrics"]
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def test_decode_action_uses_statistics_and_nonzero_history_anchor() -> None:
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history_xy = np.array([[8.0, -4.0], [10.0, -3.0]])
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action = np.array([[1.0, -1.0], [0.0, 2.0]])
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decoded = _decode_action(
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action,
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history_xy,
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mean=np.array([0.5, 0.25]),
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scale=np.array([2.0, 0.5]),
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)
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np.testing.assert_allclose(decoded, np.array([[12.5, -3.25], [13.0, -2.0]]))
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def test_extract_component_requires_one_ordered_nonempty_pair() -> None:
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text = "<|cot_start|>keep left<|cot_end|>"
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assert _extract_component(text, "cot") == "keep left"
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with pytest.raises(ValueError):
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_extract_component(text + text, "cot")
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with pytest.raises(ValueError):
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_extract_component("<|cot_start|><|cot_end|>", "cot")
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def test_prediction_metrics_use_normalized_action_and_euclidean_xy() -> None:
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target_action = np.zeros((2, 2))
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predicted_action = np.ones((2, 2))
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target_xy = np.zeros((2, 2))
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predicted_xy = np.array([[3.0, 4.0], [0.0, 0.0]])
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assert _prediction_metrics(predicted_action, predicted_xy, target_action, target_xy) == {
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"action_mse": 1.0,
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"ade_m": 2.5,
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"fde_m": 0.0,
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"max_error_m": 5.0,
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}
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