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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*
* Copyright (c) 2017-2019 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 "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCoreEx.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfiguration.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include "arm_compute/runtime/MemoryGroup.h"
namespace arm_compute
{
using namespace arm_compute::misc::shape_calculator;
using namespace arm_compute::cl_gemm;
namespace
{
inline bool is_gemm_reshaped(bool reshape_b_only_on_first_run, GPUTarget gpu_target)
{
return (get_arch_from_target(gpu_target) != GPUTarget::MIDGARD) && (reshape_b_only_on_first_run);
}
} // namespace
CLGEMMLowpMatrixMultiplyCoreEx::CLGEMMLowpMatrixMultiplyCoreEx(
std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(std::move(memory_manager)), _mm_midgard_kernel(), _mtx_a_reduction_kernel(),
_mtx_b_reduction_kernel(), _vector_sum_col(), _vector_sum_row(), _a_offset(0), _b_offset(0),
_reshape_b_only_on_first_run(false), _is_prepared(false)
{
}
void CLGEMMLowpMatrixMultiplyCoreEx::configure(const ICLTensor *a, const ICLTensor *b,
const ICLTensor *c, ICLTensor *output,
const GEMMInfo &gemm_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(a, b, output);
ARM_COMPUTE_UNUSED(c);
ARM_COMPUTE_ERROR_THROW_ON(CLGEMMLowpMatrixMultiplyCoreEx::validate(
a->info(), b->info(), c != nullptr ? c->info() : nullptr, output->info(), gemm_info));
_is_prepared = false;
_reshape_b_only_on_first_run = gemm_info.reshape_b_only_on_first_run();
_a_offset = a->info()->quantization_info().uniform().offset;
_b_offset = b->info()->quantization_info().uniform().offset;
// Get the GPU target
const GPUTarget gpu_target = CLScheduler::get().target();
// Set the target for the kernels
_mm_midgard_kernel.set_target(gpu_target);
// GEMMRHSMatrixInfo rhs_info;
// GEMMLHSMatrixInfo lhs_info;
// Arguments used by GEMMReshapeInfo
// If we pass the matrix A and matrix B reshaped to CLGEMMMatrixMultiplyKernel, we need to pass m,
// n, k, mult_transpose1xW_width and mult_interleave4x4_height to CLGEMMReshapeInfo
// in order to know how the matrices have been reshaped
bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
const unsigned int m = reinterpret_input_as_3d
? (a->info()->dimension(1) * a->info()->dimension(2))
: a->info()->dimension(1);
const unsigned int n = b->info()->dimension(0);
const unsigned int k = a->info()->dimension(0);
const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
const ICLTensor *matrix_b = b;
// Configure matrix multiply kernel
_mm_midgard_kernel.configure(
a, matrix_b, output,
GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d));
}
Status CLGEMMLowpMatrixMultiplyCoreEx::validate(const ITensorInfo *a, const ITensorInfo *b,
const ITensorInfo *c, const ITensorInfo *output,
const GEMMInfo &gemm_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(a, 1, DataType::S8);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(a, b);
ARM_COMPUTE_UNUSED(c);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.is_a_reshaped(),
"Matrix A already reshaped is not supported");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.is_b_reshaped(),
"Matrix B already reshaped is not supported");
const ITensorInfo *matrix_a_info = a;
// Get the GPU target
const GPUTarget gpu_target = CLScheduler::get().target();
bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
const unsigned int m =
reinterpret_input_as_3d ? (a->dimension(1) * a->dimension(2)) : a->dimension(1);
const unsigned int n = b->dimension(0);
const unsigned int k = a->dimension(0);
const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
bool reshape_matrix_b = is_gemm_reshaped(gemm_info.reshape_b_only_on_first_run(), gpu_target);
const GEMMReshapeInfo reshape_info =
GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d);
TensorInfo weights_info(*b);
const ITensorInfo *matrix_b_info = &weights_info;
if (reshape_matrix_b)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(false,
"CLGEMMLowpMatrixMultiplyCoreEx does not support reshape_b");
}
// Validate matrix multiply
ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyKernelEx::validate(
matrix_a_info, matrix_b_info, output, reshape_info));
return Status{};
}
void CLGEMMLowpMatrixMultiplyCoreEx::run()
{
prepare();
MemoryGroupResourceScope scope_mg(_memory_group);
// Run matrix multiply
CLScheduler::get().enqueue(_mm_midgard_kernel, false);
}
void CLGEMMLowpMatrixMultiplyCoreEx::prepare()
{
if (!_is_prepared)
{
_is_prepared = true;
}
}
} // namespace arm_compute
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