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| # Copyright (c) 2020 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.nn as nn | |
| class Activation(nn.Layer): | |
| """ | |
| The wrapper of activations. | |
| Args: | |
| act (str, optional): The activation name in lowercase. It must be one of ['elu', 'gelu', | |
| 'hardshrink', 'tanh', 'hardtanh', 'prelu', 'relu', 'relu6', 'selu', 'leakyrelu', 'sigmoid', | |
| 'softmax', 'softplus', 'softshrink', 'softsign', 'tanhshrink', 'logsigmoid', 'logsoftmax', | |
| 'hsigmoid']. Default: None, means identical transformation. | |
| Returns: | |
| A callable object of Activation. | |
| Raises: | |
| KeyError: When parameter `act` is not in the optional range. | |
| Examples: | |
| from paddleseg.models.common.activation import Activation | |
| relu = Activation("relu") | |
| print(relu) | |
| # <class 'paddle.nn.layer.activation.ReLU'> | |
| sigmoid = Activation("sigmoid") | |
| print(sigmoid) | |
| # <class 'paddle.nn.layer.activation.Sigmoid'> | |
| not_exit_one = Activation("not_exit_one") | |
| # KeyError: "not_exit_one does not exist in the current dict_keys(['elu', 'gelu', 'hardshrink', | |
| # 'tanh', 'hardtanh', 'prelu', 'relu', 'relu6', 'selu', 'leakyrelu', 'sigmoid', 'softmax', | |
| # 'softplus', 'softshrink', 'softsign', 'tanhshrink', 'logsigmoid', 'logsoftmax', 'hsigmoid'])" | |
| """ | |
| def __init__(self, act=None): | |
| super(Activation, self).__init__() | |
| self._act = act | |
| upper_act_names = nn.layer.activation.__dict__.keys() | |
| lower_act_names = [act.lower() for act in upper_act_names] | |
| act_dict = dict(zip(lower_act_names, upper_act_names)) | |
| if act is not None: | |
| if act in act_dict.keys(): | |
| act_name = act_dict[act] | |
| self.act_func = eval("nn.layer.activation.{}()".format( | |
| act_name)) | |
| else: | |
| raise KeyError("{} does not exist in the current {}".format( | |
| act, act_dict.keys())) | |
| def forward(self, x): | |
| if self._act is not None: | |
| return self.act_func(x) | |
| else: | |
| return x | |