| /*! |
| * Copyright (c) 2015 by Contributors |
| * \file upsampling_nearest.cc |
| * \brief |
| * \author Bing Xu |
| */ |
| |
| #include "./deconvolution-inl.h" |
| #include "./upsampling-inl.h" |
| |
| namespace mxnet { |
| namespace op { |
| template<> |
| Operator *CreateOp<gpu>(UpSamplingParam param, int dtype) { |
| Operator *op = NULL; |
| MSHADOW_REAL_TYPE_SWITCH(dtype, DType, { |
| if (param.sample_type == up_enum::kNearest) { |
| op = new UpSamplingNearestOp<gpu, DType>(param); |
| } else if (param.sample_type == up_enum::kBilinear) { |
| DeconvolutionParam p = DeconvolutionParam(); |
| int kernel = 2 * param.scale - param.scale % 2; |
| int stride = param.scale; |
| int pad = static_cast<int>(ceil((param.scale - 1) / 2.)); |
| p.workspace = param.workspace; |
| p.num_group = param.num_filter; |
| p.num_filter = param.num_filter; |
| p.no_bias = true; |
| int shape[] = {1, 1}; |
| p.dilate = TShape(shape, shape + 2); |
| shape[0] = shape[1] = kernel; |
| p.kernel = TShape(shape, shape + 2); |
| shape[0] = shape[1] = stride; |
| p.stride = TShape(shape, shape + 2); |
| shape[0] = shape[1] = pad; |
| p.pad = TShape(shape, shape + 2); |
| op = new DeconvolutionOp<gpu, DType>(p); |
| } else { |
| LOG(FATAL) << "Unknown sample type"; |
| } |
| }); |
| return op; |
| } |
| |
| } // namespace op |
| } // namespace mxnet |