CLBlast/test/routines/levelx/xim2col.hpp

196 lines
8.9 KiB
C++

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