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Yuan TangandGitHub
d8998a2d86
* docs: Move Alibi explainer to docs Signed-off-by: Yuan Tang <[email protected]> * Empty-Commit Signed-off-by: Yuan Tang <[email protected]> * fix test Signed-off-by: Yuan Tang <[email protected]> * Empty-Commit Signed-off-by: Yuan Tang <[email protected]> --------- Signed-off-by: Yuan Tang <[email protected]>
33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
# Copyright 2021 The KServe Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import kserve
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from typing import List, Union
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import numpy as np
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class Predictor: # pylint:disable=too-few-public-methods
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def __init__(self, clf: kserve.Model):
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self.clf = clf
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def predict_fn(self, arr: Union[np.ndarray, List]) -> np.ndarray:
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instances = []
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for req_data in arr:
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if isinstance(req_data, np.ndarray):
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instances.append(req_data.tolist())
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else:
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instances.append(req_data)
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resp = self.clf.predict({"instances": instances})
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return np.array(resp["predictions"])
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