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- # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- from __future__ import absolute_import
- from __future__ import division
- from __future__ import print_function
- import math
- import paddle
- import paddle.nn as nn
- import paddle.nn.functional as F
- class PairwiseCosface(nn.Layer):
- def __init__(self, margin, gamma):
- super(PairwiseCosface, self).__init__()
- self.margin = margin
- self.gamma = gamma
- def forward(self, embedding, targets):
- if isinstance(embedding, dict):
- embedding = embedding['features']
- # Normalize embedding features
- embedding = F.normalize(embedding, axis=1)
- dist_mat = paddle.matmul(embedding, embedding, transpose_y=True)
- N = dist_mat.shape[0]
- is_pos = targets.reshape([N, 1]).expand([N, N]).equal(
- paddle.t(targets.reshape([N, 1]).expand([N, N]))).astype('float')
- is_neg = targets.reshape([N, 1]).expand([N, N]).not_equal(
- paddle.t(targets.reshape([N, 1]).expand([N, N]))).astype('float')
- # Mask scores related to itself
- is_pos = is_pos - paddle.eye(N, N)
- s_p = dist_mat * is_pos
- s_n = dist_mat * is_neg
- logit_p = -self.gamma * s_p + (-99999999.) * (1 - is_pos)
- logit_n = self.gamma * (s_n + self.margin) + (-99999999.) * (1 - is_neg
- )
- loss = F.softplus(
- paddle.logsumexp(
- logit_p, axis=1) + paddle.logsumexp(
- logit_n, axis=1)).mean()
- return {"PairwiseCosface": loss}
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