| 23 | |
| 24 | template<typename T> |
| 25 | inline void BilateralFilter(nvbench::state &state, nvbench::type_list<T>) |
| 26 | try |
| 27 | { |
| 28 | long3 shape = benchutils::GetShape<3>(state.get_string("shape")); |
| 29 | long varShape = state.get_int64("varShape"); |
| 30 | int diameter = static_cast<int>(state.get_int64("diameter")); |
| 31 | float sigmaSpace = static_cast<float>(state.get_float64("sigmaSpace")); |
| 32 | float sigmaColor = -1.f; |
| 33 | |
| 34 | NVCVBorderType borderType = benchutils::GetBorderType(state.get_string("border")); |
| 35 | |
| 36 | state.add_global_memory_reads(shape.x * shape.y * shape.z * sizeof(T)); |
| 37 | state.add_global_memory_writes(shape.x * shape.y * shape.z * sizeof(T)); |
| 38 | |
| 39 | cvcuda::BilateralFilter op; |
| 40 | |
| 41 | // clang-format off |
| 42 | |
| 43 | if (varShape < 0) // negative var shape means use Tensor |
| 44 | { |
| 45 | nvcv::Tensor src({{shape.x, shape.y, shape.z, 1}, "NHWC"}, benchutils::GetDataType<T>()); |
| 46 | nvcv::Tensor dst({{shape.x, shape.y, shape.z, 1}, "NHWC"}, benchutils::GetDataType<T>()); |
| 47 | |
| 48 | benchutils::FillTensor<T>(src, benchutils::RandomValues<T>()); |
| 49 | |
| 50 | state.exec(nvbench::exec_tag::sync, |
| 51 | [&op, &src, &dst, &diameter, &sigmaColor, &sigmaSpace, &borderType](nvbench::launch &launch) |
| 52 | { |
| 53 | op(launch.get_stream(), src, dst, diameter, sigmaColor, sigmaSpace, borderType); |
| 54 | }); |
| 55 | } |
| 56 | else // zero and positive var shape means use ImageBatchVarShape |
| 57 | { |
| 58 | nvcv::ImageBatchVarShape src(shape.x); |
| 59 | nvcv::ImageBatchVarShape dst(shape.x); |
| 60 | |
| 61 | benchutils::FillImageBatch<T>(src, long2{shape.z, shape.y}, long2{varShape, varShape}, |
| 62 | benchutils::RandomValues<T>()); |
| 63 | dst.pushBack(src.begin(), src.end()); |
| 64 | |
| 65 | nvcv::Tensor diameterTensor({{shape.x}, "N"}, nvcv::TYPE_S32); |
| 66 | nvcv::Tensor sigmaSpaceTensor({{shape.x}, "N"}, nvcv::TYPE_F32); |
| 67 | nvcv::Tensor sigmaColorTensor({{shape.x}, "N"}, nvcv::TYPE_F32); |
| 68 | |
| 69 | benchutils::FillTensor<int>(diameterTensor, [&diameter](auto &){ return diameter; }); |
| 70 | benchutils::FillTensor<float>(sigmaSpaceTensor, [&sigmaSpace](auto &){ return sigmaSpace; }); |
| 71 | benchutils::FillTensor<float>(sigmaColorTensor, [&sigmaColor](auto &){ return sigmaColor; }); |
| 72 | |
| 73 | state.exec(nvbench::exec_tag::sync, |
| 74 | [&op, &src, &dst, &diameterTensor, &sigmaColorTensor, &sigmaSpaceTensor, &borderType] |
| 75 | (nvbench::launch &launch) |
| 76 | { |
| 77 | op(launch.get_stream(), src, dst, diameterTensor, sigmaColorTensor, sigmaSpaceTensor, borderType); |
| 78 | }); |
| 79 | } |
| 80 | } |
| 81 | catch (const std::exception &err) |
| 82 | { |
nothing calls this directly
no test coverage detected