google-research

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# coding=utf-8
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# Copyright 2024 The Google Research 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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"""Loss helper functions."""
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import tensorflow.compat.v2 as tf
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def softmax_cross_entropy(pos, neg):
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  """softmax cross entropy loss.
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  Let d_p = pos, d_n = neg.
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  we minimize:
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  log(1+exp(d_p)) + log(1+exp(-d_n))
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  for stability, is it equivalent to
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  d_p + log(1+exp(-d_p)) + log(1+exp(-d_n))
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  Args:
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    pos: Tensor.
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    neg: Tensor of the same shape of pos.
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  Returns:
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    Tensor holding pointwise loss of the same shape as pos.
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  """
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  log_exp_pos = tf.math.log1p(tf.math.exp(-pos))
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  log_exp_neg = tf.math.log1p(tf.math.exp(-neg))
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  return pos + log_exp_pos + log_exp_neg
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