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223 lines
10 KiB
C++
223 lines
10 KiB
C++
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// =================================================================================================
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// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
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// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
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// width of 100 characters per line.
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//
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// Author(s):
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// Cedric Nugteren <www.cedricnugteren.nl>
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//
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// This file implements a class with static methods to describe the Xim2col routine. Examples of
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// such 'descriptions' are how to calculate the size a of buffer or how to run the routine. These
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// static methods are used by the correctness tester and the performance tester.
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//
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// =================================================================================================
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#ifndef CLBLAST_TEST_ROUTINES_XIM2COL_H_
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#define CLBLAST_TEST_ROUTINES_XIM2COL_H_
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#include "test/routines/common.hpp"
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namespace clblast {
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// =================================================================================================
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// See comment at top of file for a description of the class
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template <typename T>
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class TestXim2col {
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public:
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// The BLAS level: 4 for the extra routines
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static size_t BLASLevel() { return 4; }
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// The list of arguments relevant for this routine
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static std::vector<std::string> GetOptions() {
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return {kArgKernelMode,
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kArgChannels, kArgHeight, kArgWidth, kArgKernelH, kArgKernelW, kArgPadH, kArgPadW,
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kArgStrideH, kArgStrideW, kArgDilationH, kArgDilationW,
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kArgAOffset, kArgBOffset};
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}
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static std::vector<std::string> BuffersIn() { return {kBufMatA, kBufMatB}; }
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static std::vector<std::string> BuffersOut() { return {kBufMatB}; }
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// Describes how to obtain the sizes of the buffers
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static size_t ColHeight(const Arguments<T> &args) {
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const auto size = args.height + 2 * args.pad_h;
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const auto padding = args.dilation_h * (args.kernel_h - 1) + 1;
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if (size >= padding) { return (size - padding) / args.stride_h + 1; }
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return 1;
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}
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static size_t ColWidth(const Arguments<T> &args) {
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const auto size = args.width + 2 * args.pad_w;
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const auto padding = args.dilation_w * (args.kernel_w - 1) + 1;
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if (size >= padding) { return (size - padding) / args.stride_w + 1; }
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return 1;
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}
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static size_t NumPatches(const Arguments<T> &args) {
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return ColHeight(args) * ColWidth(args) * args.channels;
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}
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static size_t GetSizeA(const Arguments<T> &args) {
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return args.height * args.width * args.channels + args.a_offset;
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}
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static size_t GetSizeB(const Arguments<T> &args) {
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return args.kernel_w * args.kernel_h * NumPatches(args) + args.b_offset;
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}
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// Describes how to set the sizes of all the buffers
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static void SetSizes(Arguments<T> &args, Queue&) {
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args.a_size = GetSizeA(args);
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args.b_size = GetSizeB(args);
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}
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// Describes what the default values of the leading dimensions of the matrices are
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static size_t DefaultLDA(const Arguments<T> &) { return 1; } // N/A for this routine
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static size_t DefaultLDB(const Arguments<T> &) { return 1; } // N/A for this routine
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static size_t DefaultLDC(const Arguments<T> &) { return 1; } // N/A for this routine
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// Describes which transpose options are relevant for this routine
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using Transposes = std::vector<Transpose>;
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static Transposes GetATransposes(const Transposes &) { return {}; } // N/A for this routine
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static Transposes GetBTransposes(const Transposes &) { return {}; } // N/A for this routine
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// Describes how to prepare the input data
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static void PrepareData(const Arguments<T>&, Queue&, const int, std::vector<T>&,
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std::vector<T>&, std::vector<T>&, std::vector<T>&, std::vector<T>&,
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std::vector<T>&, std::vector<T>&) {} // N/A for this routine
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// Describes how to run the CLBlast routine
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static StatusCode RunRoutine(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
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#ifdef OPENCL_API
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auto queue_plain = queue();
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auto event = cl_event{};
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auto status = Im2col<T>(args.kernel_mode,
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args.channels, args.height, args.width,
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args.kernel_h, args.kernel_w,
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args.pad_h, args.pad_w,
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args.stride_h, args.stride_w,
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args.dilation_h, args.dilation_w,
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buffers.a_mat(), args.a_offset,
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buffers.b_mat(), args.b_offset,
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&queue_plain, &event);
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if (status == StatusCode::kSuccess) { clWaitForEvents(1, &event); clReleaseEvent(event); }
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#elif CUDA_API
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auto status = Im2col<T>(args.kernel_mode,
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args.channels, args.height, args.width,
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args.kernel_h, args.kernel_w,
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args.pad_h, args.pad_w,
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args.stride_h, args.stride_w,
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args.dilation_h, args.dilation_w,
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buffers.a_mat(), args.a_offset,
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buffers.b_mat(), args.b_offset,
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queue.GetContext()(), queue.GetDevice()());
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cuStreamSynchronize(queue());
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#endif
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return status;
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}
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// Describes how to run a naive version of the routine (for correctness/performance comparison).
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// Note that a proper clBLAS or CPU BLAS comparison is not available for non-BLAS routines.
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static StatusCode RunReference1(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
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auto buffers_host = BuffersHost<T>();
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DeviceToHost(args, buffers, buffers_host, queue, BuffersIn());
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const auto status = RunReference(args, buffers_host);
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HostToDevice(args, buffers, buffers_host, queue, BuffersOut());
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return status;
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}
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static StatusCode RunReference2(const Arguments<T> &args, BuffersHost<T> &buffers_host, Queue&) {
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return RunReference(args, buffers_host);
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}
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static StatusCode RunReference3(const Arguments<T> &, BuffersCUDA<T> &, Queue &) {
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return StatusCode::kUnknownError;
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}
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// Describes how to download the results of the computation (more importantly: which buffer)
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static std::vector<T> DownloadResult(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
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std::vector<T> result(args.b_size, static_cast<T>(0));
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buffers.b_mat.Read(queue, args.b_size, result);
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return result;
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}
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// Describes how to compute the indices of the result buffer
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static size_t ResultID1(const Arguments<T> &args) { return args.kernel_h * args.kernel_w; }
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static size_t ResultID2(const Arguments<T> &args) { return NumPatches(args); }
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static size_t GetResultIndex(const Arguments<T> &args, const size_t id1, const size_t id2) {
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return id1 + args.kernel_h * args.kernel_w * id2 + args.b_offset;
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}
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// Describes how to compute performance metrics
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static size_t GetFlops(const Arguments<T> &) {
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return 1;
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}
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static size_t GetBytes(const Arguments<T> &args) {
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const auto input = args.channels * args.width * args.height; // possibly less with striding
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const auto output = args.kernel_h * args.kernel_w * NumPatches(args);
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return (input + output) * sizeof(T);
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}
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};
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// =================================================================================================
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template <typename T>
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StatusCode RunReference(const Arguments<T> &args, BuffersHost<T> &buffers_host) {
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const auto col_h = TestXim2col<T>::ColHeight(args);
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const auto col_w = TestXim2col<T>::ColWidth(args);
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for (auto c_id = size_t{0}; c_id < args.channels; ++c_id) { // input channels
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for (auto kh_id = size_t{0}; kh_id < args.kernel_h; ++kh_id) { // kernel height
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for (auto kw_id = size_t{0}; kw_id < args.kernel_w; ++kw_id) { // kernel width
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for (auto h_id = size_t{0}; h_id < col_h; ++h_id) { // image height
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for (auto w_id = size_t{0}; w_id < col_w; ++w_id) { // image width
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// Retrieves the input value
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const auto h_index = kh_id * args.dilation_h + args.stride_h * h_id - args.pad_h;
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const auto w_index = kw_id * args.dilation_w + args.stride_w * w_id - args.pad_w;
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auto val = ConstantZero<T>();
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if (h_index >= 0 && h_index < args.height &&
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w_index >= 0 && w_index < args.width) {
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const auto im_index = w_index + args.width * (h_index + args.height * c_id);
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val = buffers_host.a_mat[im_index + args.a_offset];
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}
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// Sets the output value
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const auto kernel_index
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= (args.kernel_mode == KernelMode::kConvolution)
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? args.kernel_h * args.kernel_w - kw_id - args.kernel_w * kh_id - 1
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: kw_id + args.kernel_w * kh_id;
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const auto patch_index = w_id + col_w * h_id;
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const auto col_index = patch_index + kernel_index * col_w * col_h +
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c_id * col_w * col_h * args.kernel_h * args.kernel_w;
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buffers_host.b_mat[col_index + args.b_offset] = val;
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}
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}
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}
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}
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}
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return StatusCode::kSuccess;
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}
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// Half-precision version calling the above reference implementation after conversions
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template <>
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StatusCode RunReference<half>(const Arguments<half> &args, BuffersHost<half> &buffers_host) {
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auto a_buffer2 = HalfToFloatBuffer(buffers_host.a_mat);
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auto b_buffer2 = HalfToFloatBuffer(buffers_host.b_mat);
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auto dummy = std::vector<float>(0);
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auto buffers2 = BuffersHost<float>{dummy, dummy, a_buffer2, b_buffer2, dummy, dummy, dummy};
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auto args2 = Arguments<float>();
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args2.a_size = args.a_size; args2.b_size = args.b_size;
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args2.kernel_mode = args.kernel_mode;
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args2.channels = args.channels; args2.height = args.height; args2.width = args.width;
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args2.kernel_h = args.kernel_h; args2.kernel_w = args.kernel_w;
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args2.pad_h = args.pad_h; args2.pad_w = args.pad_w;
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args2.stride_h = args.stride_h; args2.stride_w = args.stride_w;
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args2.dilation_h = args.dilation_h; args2.dilation_w = args.dilation_w;
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args2.a_offset = args.a_offset; args2.b_offset = args.b_offset;
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auto status = RunReference(args2, buffers2);
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FloatToHalfBuffer(buffers_host.b_mat, buffers2.b_mat);
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return status;
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}
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// =================================================================================================
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} // namespace clblast
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// CLBLAST_TEST_ROUTINES_XIM2COL_H_
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#endif
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