Delete ppcls/arch/head directory

ppcls/arch/head/__init__.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.
-
-from .arcmargin import ArcMargin
-from .cosmargin import CosMargin
-from .circlemargin import CircleMargin
-from .fc import FC
-
-__all__ = ['build_head']
-
-
-def build_head(config):
-    support_dict = ['ArcMargin', 'CosMargin', 'CircleMargin', 'FC']
-    module_name = config.pop('name')
-    assert module_name in support_dict, Exception('head only support {}'.format(
-        support_dict))
-    module_class = eval(module_name)(**config)
-    return module_class

ppcls/arch/head/arcmargin.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 paddle.nn as nn
-import math
-
-class ArcMargin(nn.Layer):
-    def __init__(self, embedding_size, 
-                       class_num,  
-                       margin=0.5, 
-                       scale=80.0, 
-                       easy_margin=False):
-        super(ArcMargin, self).__init__()
-        self.embedding_size   = embedding_size
-        self.class_num   = class_num
-        self.margin      = margin
-        self.scale       = scale
-        self.easy_margin = easy_margin
-
-        weight_attr =  paddle.ParamAttr(initializer = paddle.nn.initializer.XavierNormal())
-        self.fc = nn.Linear(self.embedding_size, self.class_dim, weight_attr=weight_attr, bias_attr=False) 
-
-    def forward(self, input, label):
-        input_norm = paddle.sqrt(paddle.sum(paddle.square(input), axis=1, keepdim=True))
-        input = paddle.divide(input, input_norm)
-
-        weight = self.fc0.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)
-        sin   = paddle.sqrt(1.0 - paddle.square(cos) + 1e-6)
-        cos_m = math.cos(self.margin)
-        sin_m = math.sin(self.margin)
-        phi   = cos * cos_m - sin * sin_m
-
-        th = math.cos(self.margin) * (-1)
-        mm = math.sin(self.margin) * self.margin
-        if self.easy_margin:
-            phi = self._paddle_where_more_than(cos, 0, phi, cos)
-        else:
-            phi = self._paddle_where_more_than(cos, th, phi, cos - mm)
-
-        one_hot = paddle.nn.functional.one_hot(label, self.class_dim)
-        one_hot = paddle.squeeze(one_hot, axis=[1])
-        output  = paddle.multiply(one_hot, phi) + paddle.multiply((1.0 - one_hot), cos)
-        output  = output * self.scale
-        return output
-
-    def _paddle_where_more_than(self, target, limit, x, y):
-        mask   = paddle.cast( x = (target > limit), dtype='float32')
-        output = paddle.multiply(mask, x) + paddle.multiply((1.0 - mask), y)
-        return output

ppcls/arch/head/circlemargin.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 math
-import paddle
-import paddle.nn as nn
-import paddle.nn.functional as F
- 
-class CircleMargin(nn.Layer):
-    def __init__(self, embedding_size, 
-                       class_num, 
-                       margin, 
-                       scale):
-        super(CircleSoftmax, 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.fc0 = paddle.nn.Linear(self.embedding_size, self.class_num, weight_attr=weight_attr)
- 
-    def forward(self, input, label):
-        feat_norm = paddle.sqrt(paddle.sum(paddle.square(input), axis=1, keepdim=True))
-        input = paddle.divide(input, feat_norm)
-
-        weight = self.fc0.weight
-        weight_norm = paddle.sqrt(paddle.sum(paddle.square(weight), axis=0, keepdim=True))
-        weight = paddle.divide(weight, weight_norm)
- 
-        logits   = paddle.matmul(input, weight)
-
-        alpha_p = paddle.clip(-logits.detach() + 1 + self.margin, min=0.)
-        alpha_n = paddle.clip(logits.detach() + self.margin, min=0.)
-        delta_p = 1 - self.margin
-        delta_n = self.margin
-        index = paddle.fluid.layers.where(label != -1).reshape([-1])
-        m_hot = F.one_hot(label.reshape([-1]), num_classes=logits.shape[1])
-        logits_p = alpha_p * (logits - delta_p)
-        logits_n = alpha_n * (logits - delta_n)
-        pre_logits = logits_p * m_hot + logits_n * (1 - m_hot)
-        pre_logits = self.scale * pre_logits
- 
-        return pre_logits

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

ppcls/arch/head/fc.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 paddle.nn as nn
-
-class FC(nn.Layer):
-    def __init__(self, embedding_size, 
-                       class_num):
-        super(FC, self).__init__()
-        self.embedding_size  = embedding_size
-        self.class_num = class_num
-        weight_attr =  paddle.ParamAttr(initializer = paddle.nn.initializer.XavierNormal())
-        self.fc  =  paddle.nn.Linear(self.embedding_size, self.class_num, weight_attr=weight_attr)    
-
-    def forward(self, input, label):
-        out = self.fc(input)
-        return out