Create cosmargin.py

ppcls/arch/head/cosmargin.py

+# 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