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/*
* Copyright (c) 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "src/gpu/cl/kernels/helpers/MatMulKernelHelpers.h"
#include "arm_compute/core/Coordinates.h"
#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
#include "arm_compute/core/utils/math/Math.h"
#include "src/core/helpers/WindowHelpers.h"
namespace arm_compute
{
namespace opencl
{
namespace kernels
{
Status validate_matmul_input_shapes(const TensorShape &lhs_shape,
const TensorShape &rhs_shape,
const MatMulKernelInfo &matmul_kernel_info)
{
const size_t lhs_k = matmul_kernel_info.adj_lhs ? lhs_shape.y() : lhs_shape.x();
const size_t rhs_k = matmul_kernel_info.adj_rhs ? rhs_shape.x() : rhs_shape.y();
ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_k != rhs_k, "K dimension in Lhs and Rhs matrices must match.");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_shape.total_size() == 0, "Lhs tensor can't be empty");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(rhs_shape.total_size() == 0, "Rhs tensor can't be empty");
constexpr size_t batch_dim_start = 2;
for (size_t i = batch_dim_start; i < Coordinates::num_max_dimensions; ++i)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_shape[i] != rhs_shape[i], "Batch dimension broadcasting is not supported");
}
return Status{};
}
std::pair<Status, Window> validate_and_configure_window_for_mmul_kernels(const ITensorInfo *lhs,
const ITensorInfo *rhs,
const ITensorInfo *dst,
const MatMulKernelInfo &matmul_kernel_info,
int mmul_m0,
int mmul_n0)
{
ARM_COMPUTE_UNUSED(lhs, rhs);
const Window win = calculate_max_window(*dst, Steps(1, 1));
// Collapse along the Z direction
// This collapse needs to be here in order to tune the Z dimension of LWS
Window collapsed = win.collapse(win, Window::DimZ);
// Reconfigure window size, one arm_matrix_multiply call needs 16 threads to finish.
Window::Dimension x_dimension = collapsed.x();
Window::Dimension y_dimension = collapsed.y();
const int m = dst->dimension(1);
const int n = dst->dimension(0);
const int m0 = std::min(matmul_kernel_info.m0, m);
const int n0 = adjust_vec_size(matmul_kernel_info.n0, n);
// Make M and N multiple of M0 and N0 respectively
const unsigned int ceil_to_multiple_n_n0 = ceil_to_multiple(n, n0);
const unsigned int ceil_to_multiple_m_m0 = ceil_to_multiple(m, m0);
// Divide M and N by M0 and N0 respectively
const unsigned int n_div_n0 = ceil_to_multiple_n_n0 / n0;
const unsigned int m_div_m0 = ceil_to_multiple_m_m0 / m0;
// Make n_div_n0 and m_div_m0 multiple of mmul_n0 and mmul_m0 respectively
const unsigned int ceil_to_multiple_n_div_n0_mmul_n0 = ceil_to_multiple(n_div_n0, mmul_n0);
const unsigned int ceil_to_multiple_m_div_m0_mmul_m0 = ceil_to_multiple(m_div_m0, mmul_m0);
// Ensure x_dimension is multiple of MMUL block size (mmul_m0 * mmul_n0)
x_dimension.set_end(ceil_to_multiple_n_div_n0_mmul_n0 * mmul_m0);
y_dimension.set_end(ceil_to_multiple_m_div_m0_mmul_m0 / mmul_m0);
collapsed.set(Window::DimX, x_dimension);
collapsed.set(Window::DimY, y_dimension);
return std::make_pair(Status{}, collapsed);
}
} // namespace kernels
} // namespace opencl
} // namespace arm_compute
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