wehub-resource-sync
92 lines
4.2 KiB
Python
92 lines
4.2 KiB
Python
from io import BytesIO
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from typing import Any
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import numpy as np
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from shap.explainers.other._ubjson import _decode_simple_key_value_pair
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def test_decode_simple_key_value_pair():
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# todo: this is not correct, fix this
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num_class = b"L\x00\x00\x00\x00\x00\x00\x00\tnum_classL\x00\x00\x00\x00\x00\x00\x00\x0b"
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fp = BytesIO(num_class)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type=key_type)
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assert key == "num_class" and value == 11
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boost_from_average = b"L\x00\x00\x00\x00\x00\x00\x00\x12boost_from_averageSL\x00\x00\x00\x00\x00\x00\x00\x011"
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fp = BytesIO(boost_from_average)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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assert key == "boost_from_average" and value == "1"
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num_feature = b"L\x00\x00\x00\x00\x00\x00\x00\x0bnum_featureSL\x00\x00\x00\x00\x00\x00\x00\x013"
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fp = BytesIO(num_feature)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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assert key == "num_feature" and value == "3"
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num_class = b"L\x00\x00\x00\x00\x00\x00\x00\tnum_classSL\x00\x00\x00\x00\x00\x00\x00\x010"
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fp = BytesIO(num_class)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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assert key == "num_class" and value == "0"
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def test_decode_object():
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expected_value: dict[str, Any]
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regression_loss = b"L\x00\x00\x00\x00\x00\x00\x00\x0ereg_loss_param{L\x00\x00\x00\x00\x00\x00\x00\x10scale_pos_weightSL\x00\x00\x00\x00\x00\x00\x00\x011}"
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fp = BytesIO(regression_loss)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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expected_key = "reg_loss_param"
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expected_value = {"scale_pos_weight": "1"}
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assert expected_key == key and value == expected_value
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objective_dict = b"L\x00\x00\x00\x00\x00\x00\x00\tobjective{L\x00\x00\x00\x00\x00\x00\x00\x04nameSL\x00\x00\x00\x00\x00\x00\x00\x0fbinary:logisticL\x00\x00\x00\x00\x00\x00\x00\x0ereg_loss_param{L\x00\x00\x00\x00\x00\x00\x00\x10scale_pos_weightSL\x00\x00\x00\x00\x00\x00\x00\x011}}"
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fp = BytesIO(objective_dict)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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expected_key = "objective"
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expected_value = {"name": "binary:logistic", "reg_loss_param": {"scale_pos_weight": "1"}}
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assert expected_key == key and value == expected_value
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objective_reversed_dict = b"L\x00\x00\x00\x00\x00\x00\x00\tobjective{L\x00\x00\x00\x00\x00\x00\x00\x0ereg_loss_param{L\x00\x00\x00\x00\x00\x00\x00\x10scale_pos_weightSL\x00\x00\x00\x00\x00\x00\x00\x011}L\x00\x00\x00\x00\x00\x00\x00\x04nameSL\x00\x00\x00\x00\x00\x00\x00\x0fbinary:logisticL\x00\x00\x00\x00\x00\x00\x00\x0e}"
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fp = BytesIO(objective_reversed_dict)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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expected_key = "objective"
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expected_value = {
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"reg_loss_param": {"scale_pos_weight": "1"},
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"name": "binary:logistic",
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}
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assert expected_key == key and value == expected_value
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empty_object_dict = b"L\x00\x00\x00\x00\x00\x00\x00\nattributes{}"
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fp = BytesIO(empty_object_dict)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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assert key == "attributes" and value == {}
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def test_decode_array():
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left_children = b"L\x00\x00\x00\x00\x00\x00\x00\rleft_children[$l#L\x00\x00\x00\x00\x00\x00\x00\x01\xff\xff\xff\xffL\x00\x00\x00\x00\x00\x00\x00\x0c"
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fp = BytesIO(left_children)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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assert key == "left_children" and value == np.array([-1], dtype=np.int32)
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# string array
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feature_names = b"L\x00\x00\x00\x00\x00\x00\x00\rfeature_names[#L\x00\x00\x00\x00\x00\x00\x00\x00L\x00\x00\x00\x00\x00\x00\x00\r"
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fp = BytesIO(feature_names)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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assert key == "feature_names" and value == []
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base_weights = b"L\x00\x00\x00\x00\x00\x00\x00\x0cbase_weights[$d#L\x00\x00\x00\x00\x00\x00\x00\x01\xba\xa2\xe1&"
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fp = BytesIO(base_weights)
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key_type = fp.read(1)
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key, value = _decode_simple_key_value_pair(fp, key_type)
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assert key == "base_weights" and value == [-0.0012426718603819609]
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