| /* |
| * 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. |
| */ |
| |
| /*! |
| * Copyright (c) 2015 by Contributors |
| * \file sequence_op_common.h |
| * \brief common function used for sequence layers |
| * \author Sebastian Bodenstein |
| */ |
| #ifndef MXNET_OPERATOR_SEQUENCE_OP_COMMON_H_ |
| #define MXNET_OPERATOR_SEQUENCE_OP_COMMON_H_ |
| #include <dmlc/logging.h> |
| #include <mxnet/operator.h> |
| #include <vector> |
| #include "./operator_common.h" |
| |
| namespace mxnet { |
| namespace op { |
| |
| template <typename DType, typename RType> |
| typename std::enable_if<std::is_integral<RType>::value>::type |
| inline IndexTensorToVector(mshadow::Tensor<gpu, 1, DType> data, |
| std::vector<RType> *index_vec) { |
| #if MXNET_USE_CUDA |
| size_t const max_seq_len = data.shape_.Size(); |
| DType *temp_index = |
| reinterpret_cast<DType *>(malloc(sizeof(DType) * max_seq_len)); |
| cudaError_t cuda_status = |
| cudaMemcpyAsync(temp_index, data.dptr_, max_seq_len * sizeof(DType), |
| cudaMemcpyDeviceToHost, data.stream_->stream_); |
| CHECK_EQ(cuda_status, cudaSuccess) << "cuda memcpy label error"; |
| for (size_t i = 0; i < max_seq_len; ++i) { |
| (*index_vec)[i] = static_cast<RType>(std::lround(temp_index[i])); |
| } |
| free(temp_index); |
| #endif |
| } |
| template <typename DType, typename RType> |
| typename std::enable_if<std::is_integral<RType>::value>::type |
| inline IndexTensorToVector(mshadow::Tensor<cpu, 1, DType> data, |
| std::vector<RType> *index_vec) { |
| int max_seq_len = data.shape_.Size(); |
| DType *index_array = static_cast<DType *>(data.dptr_); |
| for (int i = 0; i < max_seq_len; ++i) |
| (*index_vec)[i] = static_cast<RType>(std::lround(index_array[i])); |
| } |
| |
| } // namespace op |
| } // namespace mxnet |
| #endif // MXNET_OPERATOR_SEQUENCE_OP_COMMON_H_ |