| /* |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you 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. |
| */ |
| |
| /*! |
| * \file activation.cc |
| * \brief softmax_activation op |
| * \author Junyuan Xie, Da Zheng |
| */ |
| #include "./softmax_activation-inl.h" |
| #include "../tensor/elemwise_unary_op.h" |
| #include "../mshadow_op.h" |
| |
| namespace mxnet { |
| namespace op { |
| |
| DMLC_REGISTER_PARAMETER(SoftmaxActivationParam); |
| |
| MXNET_OPERATOR_REGISTER_UNARY(SoftmaxActivation) |
| .describe(R"code(Applies softmax activation to input. This is intended for internal layers. |
| |
| .. note:: |
| |
| This operator has been deprecated, please use `softmax`. |
| |
| If `mode` = ``instance``, this operator will compute a softmax for each instance in the batch. |
| This is the default mode. |
| |
| If `mode` = ``channel``, this operator will compute a k-class softmax at each position |
| of each instance, where `k` = ``num_channel``. This mode can only be used when the input array |
| has at least 3 dimensions. |
| This can be used for `fully convolutional network`, `image segmentation`, etc. |
| |
| Example:: |
| |
| >>> input_array = mx.nd.array([[3., 0.5, -0.5, 2., 7.], |
| >>> [2., -.4, 7., 3., 0.2]]) |
| >>> softmax_act = mx.nd.SoftmaxActivation(input_array) |
| >>> print softmax_act.asnumpy() |
| [[ 1.78322066e-02 1.46375655e-03 5.38485940e-04 6.56010211e-03 9.73605454e-01] |
| [ 6.56221947e-03 5.95310994e-04 9.73919690e-01 1.78379621e-02 1.08472735e-03]] |
| |
| )code" ADD_FILELINE) |
| .set_attr_parser(ParamParser<SoftmaxActivationParam>) |
| .set_attr<nnvm::FListOutputNames>("FListOutputNames", |
| [](const NodeAttrs& attrs) { |
| return std::vector<std::string>{"output"}; |
| }) |
| .set_attr<FCompute>("FCompute<cpu>", SoftmaxActivationCompute<cpu>) |
| .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseOut{"_backward_SoftmaxActivation"}) |
| .add_arguments(SoftmaxActivationParam::__FIELDS__()); |
| |
| NNVM_REGISTER_OP(_backward_SoftmaxActivation) |
| .set_num_inputs(2) |
| .set_num_outputs(1) |
| .set_attr<nnvm::TIsBackward>("TIsBackward", true) |
| .set_attr<nnvm::FInplaceOption>("FInplaceOption", |
| [](const NodeAttrs& attrs) { |
| return std::vector<std::pair<int, int> >{{0, 0}}; |
| }) |
| .set_attr<FResourceRequest>("FResourceRequest", |
| [](const NodeAttrs& n) { |
| return std::vector<ResourceRequest>{ResourceRequest::kTempSpace}; |
| }) |
| .set_attr<THasDeterministicOutput>("THasDeterministicOutput", true) |
| .set_attr_parser(ParamParser<SoftmaxActivationParam>) |
| .set_attr<FCompute>("FCompute<cpu>", SoftmaxActivationGradCompute<cpu>); |
| |
| } // namespace op |
| } // namespace mxnet |
