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72 lines
2.6 KiB
72 lines
2.6 KiB
# 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 paddle.nn as nn |
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import math |
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class ArcMargin(nn.Layer): |
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def __init__(self, |
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embedding_size, |
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class_num, |
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margin=0.5, |
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scale=80.0, |
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easy_margin=False): |
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super().__init__() |
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self.embedding_size = embedding_size |
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self.class_num = class_num |
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self.margin = margin |
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self.scale = scale |
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self.easy_margin = easy_margin |
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self.weight = self.create_parameter( |
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shape=[self.embedding_size, self.class_num], |
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is_bias=False, |
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default_initializer=paddle.nn.initializer.XavierNormal()) |
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def forward(self, input, label=None): |
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input_norm = paddle.sqrt( |
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paddle.sum(paddle.square(input), axis=1, keepdim=True)) |
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input = paddle.divide(input, input_norm) |
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weight_norm = paddle.sqrt( |
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paddle.sum(paddle.square(self.weight), axis=0, keepdim=True)) |
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weight = paddle.divide(self.weight, weight_norm) |
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cos = paddle.matmul(input, weight) |
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if not self.training or label is None: |
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return cos |
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sin = paddle.sqrt(1.0 - paddle.square(cos) + 1e-6) |
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cos_m = math.cos(self.margin) |
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sin_m = math.sin(self.margin) |
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phi = cos * cos_m - sin * sin_m |
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th = math.cos(self.margin) * (-1) |
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mm = math.sin(self.margin) * self.margin |
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if self.easy_margin: |
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phi = self._paddle_where_more_than(cos, 0, phi, cos) |
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else: |
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phi = self._paddle_where_more_than(cos, th, phi, cos - mm) |
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one_hot = paddle.nn.functional.one_hot(label, self.class_num) |
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one_hot = paddle.squeeze(one_hot, axis=[1]) |
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output = paddle.multiply(one_hot, phi) + paddle.multiply( |
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(1.0 - one_hot), cos) |
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output = output * self.scale |
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return output |
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def _paddle_where_more_than(self, target, limit, x, y): |
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mask = paddle.cast(x=(target > limit), dtype='float32') |
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output = paddle.multiply(mask, x) + paddle.multiply((1.0 - mask), y) |
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return output
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