dlib C++ Library - cublas_dlibapi.h

// Copyright (C) 2015 Davis E. King (davis@dlib.net)
// License: Boost Software License See LICENSE.txt for the full license.
#ifndef DLIB_DNN_CuBLAS_H_
#define DLIB_DNN_CuBLAS_H_
#ifdef DLIB_USE_CUDA
#include "tensor.h"
#include "cuda_errors.h"
namespace dlib
{ 
 namespace cuda 
 { 
 // -----------------------------------------------------------------------------------
 void gemm (
 float beta,
 tensor& dest,
 float alpha,
 const tensor& lhs,
 bool trans_lhs,
 const tensor& rhs,
 bool trans_rhs,
 operation_mode mode = operation_mode::CHANNEL_WISE
 );
 /*!
 requires
 - The dimensions of lhs and rhs must be compatible for matrix multiplication.
 The specific requirements depend on the mode:
 For CHANNEL_WISE mode (default):
 - Let L == trans_lhs ? trans(mat(lhs)) : mat(lhs)
 - Let R == trans_rhs ? trans(mat(rhs)) : mat(rhs)
 - Let D == mat(dest)
 - D.nr() == L.nr() && D.nc() == R.nc()
 (i.e. dest must be preallocated and have the correct output dimensions)
 - L.nc() == R.nr()
 For PLANE_WISE mode:
 - lhs.num_samples() == rhs.num_samples() && lhs.k() == rhs.k()
 - If !trans_lhs && !trans_rhs:
 lhs.nc() == rhs.nr()
 dest.nr() == lhs.nr() && dest.nc() == rhs.nc()
 - If trans_lhs && !trans_rhs:
 lhs.nr() == rhs.nr()
 dest.nr() == lhs.nc() && dest.nc() == rhs.nc()
 - If !trans_lhs && trans_rhs:
 lhs.nc() == rhs.nc()
 dest.nr() == lhs.nr() && dest.nc() == rhs.nr()
 - If trans_lhs && trans_rhs:
 lhs.nr() == rhs.nc()
 dest.nr() == lhs.nc() && dest.nc() == rhs.nr()
 ensures
 - Performs matrix multiplication based on the specified mode:
 For CHANNEL_WISE mode:
 - performs: dest = alpha*L*R + beta*mat(dest)
 where L, R, and D are as defined above.
 For PLANE_WISE mode:
 - Performs matrix multiplication for each corresponding 2D plane (nr x nc)
 in lhs and rhs across all samples and channels.
 - The operation is equivalent to performing the following for each sample
 and channel:
 dest[s][k] = alpha * (lhs[s][k] * rhs[s][k]) + beta * dest[s][k]
 where [s][k] represents the 2D plane for sample s and channel k.
 !*/
 // ------------------------------------------------------------------------------------
 } 
}
#endif // DLIB_USE_CUDA
#endif // DLIB_DNN_CuBLAS_H_