mirror of
https://github.com/PaddlePaddle/PaddleClas.git
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51 lines
1.9 KiB
Python
51 lines
1.9 KiB
Python
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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import paddle
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import math
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import paddle.nn as nn
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class CosMargin(paddle.nn.Layer):
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def __init__(self, embedding_size,
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class_num,
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margin=0.35,
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scale=64.0):
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super(CosMargin, self).__init__()
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self.scale = scale
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self.margin = margin
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self.embedding_size = embedding_size
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self.class_num = class_num
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weight_attr = paddle.ParamAttr(initializer = paddle.nn.initializer.XavierNormal())
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self.fc = nn.Linear(self.embedding_size, self.class_num, weight_attr=weight_attr, bias_attr=False)
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def forward(self, input, label):
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label.stop_gradient = True
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input_norm = paddle.sqrt(paddle.sum(paddle.square(input), axis=1, keepdim=True))
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input = paddle.divide(input, x_norm)
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weight = self.fc.weight
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weight_norm = paddle.sqrt(paddle.sum(paddle.square(weight), axis=0, keepdim=True))
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weight = paddle.divide(weight, weight_norm)
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cos = paddle.matmul(input, weight)
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cos_m = cos - self.margin
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one_hot = paddle.nn.functional.one_hot(label, self.out_dim)
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one_hot = paddle.squeeze(one_hot, axis=[1])
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output = paddle.multiply(one_hot, cos_m) + paddle.multiply((1.0 - one_hot), cos)
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output = output * self.scale
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return output
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