concat_kernel.cpp 2.4 KB
Newer Older
Y
yangfei 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
/* Copyright (c) 2018 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. */

#ifdef CONCAT_OP

#include "operators/kernel/concat_kernel.h"

namespace paddle_mobile {
Y
yangfei 已提交
20
namespace operators {
Y
yangfei 已提交
21

Y
yangfei 已提交
22 23
template <>
bool ConcatKernel<GPU_CL, float>::Init(ConcatParam<GPU_CL> *param) {
Y
yangfei 已提交
24 25 26
  if (param->Out()->dims().size() < 4) {
    this->cl_helper_.AddKernel("concatByH", "concat_kernel.cl");
  }
Y
yangfei 已提交
27 28
  return true;
}
Y
yangfei 已提交
29

Y
yangfei 已提交
30
template <>
Y
yangfei 已提交
31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66
void ConcatKernel<GPU_CL, float>::Compute(const ConcatParam<GPU_CL> &param) {
  if (param.Out()->dims().size() < 4) {
    auto kernel = this->cl_helper_.KernelAt(0);
    auto inputs = param.Inputs();
    auto *output_image = param.Out()->GetCLImage();
    int out_W = 0;
    if (param.Out()->dims().size() == 3) {
      out_W = param.Out()->dims()[2];
    } else if (param.Out()->dims().size() == 2) {
      out_W = param.Out()->dims()[1];
    }
    int out_H_Start = 0;
    for (int i = 0; i < inputs.size(); i++) {
      auto input_image = inputs[i]->GetCLImage();
      auto default_work_size = this->cl_helper_.DefaultWorkSize(*inputs[i]);
      cl_int status;
      status = clSetKernelArg(kernel, 0, sizeof(cl_mem), &input_image);
      CL_CHECK_ERRORS(status);
      status = clSetKernelArg(kernel, 1, sizeof(cl_mem), &output_image);
      CL_CHECK_ERRORS(status);
      status = clSetKernelArg(kernel, 2, sizeof(int), &out_W);
      CL_CHECK_ERRORS(status);
      status = clSetKernelArg(kernel, 3, sizeof(int), &out_H_Start);
      CL_CHECK_ERRORS(status);
      status = clEnqueueNDRangeKernel(
          this->cl_helper_.CLCommandQueue(), kernel, default_work_size.size(),
          NULL, default_work_size.data(), NULL, 0, NULL, NULL);
      CL_CHECK_ERRORS(status);
      if (param.Out()->dims().size() == 3) {
        out_H_Start += inputs[i]->dims()[1];
      } else if (param.Out()->dims().size() == 2) {
        out_H_Start += inputs[i]->dims()[0];
      }
    }
  }
}
Y
yangfei 已提交
67

Y
yangfei 已提交
68
}  // namespace operators
Y
yangfei 已提交
69 70 71
}  // namespace paddle_mobile

#endif