| /************************************************************ |
| * |
| * 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. |
| * |
| *************************************************************/ |
| |
| #include "singa/neuralnet/input_layer.h" |
| namespace singa { |
| void RNNLabelLayer::Setup(const LayerProto& proto, |
| const vector<Layer*>& srclayers) { |
| InputLayer::Setup(proto, srclayers); |
| aux_data_.resize(srclayers[0]->data(unroll_index() + 1).shape(0)); |
| } |
| void RNNLabelLayer::ComputeFeature(int flag, const vector<Layer*>& srclayers) { |
| const float* input = srclayers[0]->data(unroll_index() + 1).cpu_data(); |
| for (unsigned i = 0; i < aux_data_.size(); i++) { |
| aux_data_[i] = static_cast<int>(input[i]); |
| } |
| } |
| } // namespace singa |
