You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
58 lines
2.0 KiB
58 lines
2.0 KiB
# 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}
|
|
|