未验证 提交 6391c90b 编写于 作者: B Bin Lu 提交者: GitHub

Delete ppcls/arch/neck directory

上级 85ca658e
# 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.
__all__ = ['build_neck"]
def build_neck(config):
support_dict = ['FPN', 'FC']
module_name = config.pop('name')
assert module_name in support_dict, Exception('neck only support {}'.format(
support_dict))
module_class = eval(module_name)(**config)
return module_class
# 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 __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import paddle
import paddle.nn as nn
class FC(nn.Layer):
def __init__(self, input_dim,
embedding_size):
super(FC, self).__init__()
self.input_dim = input_dim
self.embedding_size = embedding_size
weight_attr = paddle.ParamAttr(initializer = paddle.nn.initializer.XavierNormal())
self.fc = paddle.nn.Linear(self.input_dim, self.embedding_size, weight_attr=weight_attr)
def forward(self, x):
x = self.fc(x)
return x
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