Create cosmargin.py

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Bin Lu 2021-05-28 19:22:31 +08:00 committed by GitHub
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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.
import paddle
import math
import paddle.nn as nn
class CosMargin(paddle.nn.Layer):
def __init__(self, embedding_size,
class_num,
margin=0.35,
scale=64.0):
super(CosMargin, self).__init__()
self.scale = scale
self.margin = margin
self.embedding_size = embedding_size
self.class_num = class_num
weight_attr = paddle.ParamAttr(initializer = paddle.nn.initializer.XavierNormal())
self.fc = nn.Linear(self.embedding_size, self.class_num, weight_attr=weight_attr, bias_attr=False)
def forward(self, input, label):
label.stop_gradient = True
input_norm = paddle.sqrt(paddle.sum(paddle.square(input), axis=1, keepdim=True))
input = paddle.divide(input, x_norm)
weight = self.fc.weight
weight_norm = paddle.sqrt(paddle.sum(paddle.square(weight), axis=0, keepdim=True))
weight = paddle.divide(weight, weight_norm)
cos = paddle.matmul(input, weight)
cos_m = cos - self.margin
one_hot = paddle.nn.functional.one_hot(label, self.out_dim)
one_hot = paddle.squeeze(one_hot, axis=[1])
output = paddle.multiply(one_hot, cos_m) + paddle.multiply((1.0 - one_hot), cos)
output = output * self.scale
return output