wehub-resource-sync
57 lines
2.0 KiB
Python
57 lines
2.0 KiB
Python
import numpy as np
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from transformers import AutoTokenizer
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import shap.benchmark as benchmark
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from shap.maskers import FixedComposite, Image, Impute, Independent, Partition, Text
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def model(x, y):
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return x
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sort_order = "positive"
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perturbation = "keep"
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def test_init(random_seed):
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rs = np.random.RandomState(random_seed)
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X = rs.random((10, 13))
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tabular_masker = Independent(X)
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sequential_perturbation = benchmark.perturbation.SequentialPerturbation(
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model, tabular_masker, sort_order, perturbation
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)
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assert sequential_perturbation.data_type == "tabular"
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tabular_masker = Partition(X)
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sequential_perturbation = benchmark.perturbation.SequentialPerturbation(
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model, tabular_masker, sort_order, perturbation
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)
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assert sequential_perturbation.data_type == "tabular"
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tabular_masker = Impute(X)
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sequential_perturbation = benchmark.perturbation.SequentialPerturbation(
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model, tabular_masker, sort_order, perturbation
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)
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assert sequential_perturbation.data_type == "tabular"
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text_masker = Text(AutoTokenizer.from_pretrained("nateraw/bert-base-uncased-emotion", use_fast=True))
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sequential_perturbation = benchmark.perturbation.SequentialPerturbation(
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model, text_masker, sort_order, perturbation
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)
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assert sequential_perturbation.data_type == "text"
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image_masker = Image("inpaint_telea", shape=(224, 224, 3))
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sequential_perturbation = benchmark.perturbation.SequentialPerturbation(
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model, image_masker, sort_order, perturbation
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)
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assert sequential_perturbation.data_type == "image"
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fc_masker = FixedComposite(text_masker)
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sequential_perturbation = benchmark.perturbation.SequentialPerturbation(model, fc_masker, sort_order, perturbation)
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assert sequential_perturbation.data_type == "text"
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fc_masker = FixedComposite(image_masker)
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sequential_perturbation = benchmark.perturbation.SequentialPerturbation(model, fc_masker, sort_order, perturbation)
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assert sequential_perturbation.data_type == "image"
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