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helper.cpp 1.8 kB

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  1. /**
  2. * \file dnn/src/cuda/convolution3d/helper.cpp
  3. * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
  4. *
  5. * Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
  6. *
  7. * Unless required by applicable law or agreed to in writing,
  8. * software distributed under the License is distributed on an
  9. * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  10. */
  11. #include "./helper.h"
  12. using namespace megdnn;
  13. using namespace cuda;
  14. using namespace convolution3d;
  15. bool convolution3d::is_cudnn_supported(const ForwardSizeArgs &args) {
  16. if (args.handle->is_tegra_k1())
  17. return false;
  18. if (args.src_layout->dtype.category() != DTypeCategory::FLOAT)
  19. return false;
  20. if (args.filter_meta.format != param::Convolution3D::Format::NCDHW)
  21. return false;
  22. auto& fm = args.filter_meta;
  23. return
  24. #if CUDNN_MAJOR >= 7
  25. true
  26. #else
  27. fm.group == 1
  28. #endif
  29. && fm.spatial_ndim == 3;
  30. }
  31. void convolution3d::flip_filter(const ForwardSizeArgs &args,
  32. const Workspace &workspace, void *&raw_ptr) {
  33. auto &&fm = args.filter_meta;
  34. megdnn_assert(fm.group == 1 && fm.spatial_ndim == 3);
  35. auto OC = fm.ocpg, IC = fm.icpg, FD = fm.spatial[0], FH = fm.spatial[1], FW = fm.spatial[2];
  36. auto dtype = DType::from_enum(fm.dtype_enum);
  37. megdnn_assert(workspace.size >= dtype.size() * OC * IC * FD * FH * FW);
  38. TensorND src{raw_ptr, {{OC, IC, FD, FH, FW}, dtype}},
  39. dst{workspace.raw_ptr + (FD * FH * FW - 1) * dtype.size(), src.layout};
  40. dst.layout.stride[2] = -dst.layout.stride[2];
  41. dst.layout.stride[3] = -dst.layout.stride[3];
  42. dst.layout.stride[4] = -dst.layout.stride[4];
  43. args.handle->relayout_opr()->exec(src, dst);
  44. raw_ptr = workspace.raw_ptr;
  45. }
  46. // vim: syntax=cpp.doxygen

MegEngine 安装包中集成了使用 GPU 运行代码所需的 CUDA 环境,不用区分 CPU 和 GPU 版。 如果想要运行 GPU 程序,请确保机器本身配有 GPU 硬件设备并安装好驱动。 如果你想体验在云端 GPU 算力平台进行深度学习开发的感觉,欢迎访问 MegStudio 平台