wehub-resource-sync
56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
import numpy as np
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import shap
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def model(x):
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return np.array([np.linalg.norm(x)])
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X = np.array([[3, 4], [5, 12], [7, 24]])
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y = np.array([5, 13, 25])
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explainer = np.array([[-1, 2], [-4, 2], [1, 2]])
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masker = X
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def test_update():
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"""This is to test the update function within benchmark/framework"""
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sort_order = "positive"
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def score_function(true, pred):
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return np.mean(pred)
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perturbation = "keep"
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scores = {"name": "test", "metrics": list(), "values": dict()}
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shap.benchmark.update(model, X, y, explainer, masker, sort_order, score_function, perturbation, scores)
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metric = perturbation + " " + sort_order
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assert scores["metrics"][0] == metric
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assert len(scores["values"][metric]) == 3
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def test_get_benchmark():
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"""This is to test the get benchmark function within benchmark/framework"""
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metrics = {"sort_order": ["positive", "negative"], "perturbation": ["keep"]}
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scores = shap.benchmark.get_benchmark(model, X, y, explainer, masker, metrics)
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expected_metrics = ["keep positive", "keep negative"]
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assert set(expected_metrics) == set(scores["metrics"])
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assert len(scores["values"]) == 2
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def test_get_metrics():
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"""This is to test the get metrics function with respect to different selection method"""
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scores1 = {"name": "test1", "metrics": ["keep positive", "keep absolute"], "values": dict()}
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scores2 = {"name": "test2", "metrics": ["keep positive", "keep negative"], "values": dict()}
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benchmarks = {"test1": scores1, "test2": scores2}
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expected_metrics1 = set(["keep positive"])
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expected_metrics2 = set(["keep positive", "keep negative", "keep absolute"])
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assert set(shap.benchmark.get_metrics(benchmarks, lambda x, y: x.intersection(y))) == expected_metrics1
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assert set(shap.benchmark.get_metrics(benchmarks, lambda x, y: x.union(y))) == expected_metrics2
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