wehub-resource-sync
59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. 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,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# pylint: disable=invalid-name, trailing-whitespace
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"""Softmax and log_softmax operation in python"""
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import numpy as np
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def softmax_python(a_np, axis=1):
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"""Softmax operator.
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Parameters
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----------
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a_np : numpy.ndarray
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N-D input data
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Returns
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-------
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output_np : numpy.ndarray
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N-D output with same shape
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"""
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max_elem = np.amax(a_np, axis=axis, keepdims=True)
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e = np.exp(a_np - max_elem)
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expsum = np.sum(e, axis=axis, keepdims=True)
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out_np = e / expsum
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return out_np
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def log_softmax_python(a_np, axis=1):
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"""Log_softmax operator.
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Parameters
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----------
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a_np : numpy.ndarray
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N-D input data
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Returns
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-------
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output_np : numpy.ndarray
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N-D output with same shape
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"""
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max_elem = np.amax(a_np, axis=axis, keepdims=True)
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e = np.exp(a_np - max_elem)
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expsum = np.sum(e, axis=axis, keepdims=True)
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out_np = a_np - max_elem - np.log(expsum)
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return out_np
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