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/*
* Copyright (c) 2023-2024 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/dynamic_fusion/sketch/gpu/components/cl/ClComponentMatMul.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/dynamic_fusion/sketch/attributes/MatMulAttributes.h"
#include "src/core/CL/CLValidate.h"
#include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwMatMul.h"
#include "src/gpu/cl/kernels/helpers/MatMulKernelHelpers.h"
namespace arm_compute
{
namespace experimental
{
namespace dynamic_fusion
{
namespace
{
using Attributes = MatMulAttributes;
using Settings = GpuMatMulSettings;
Status validate_matmul_kernel_info(Attributes attributes, Settings settings)
{
const bool adj_lhs = attributes.adj_lhs();
const bool adj_rhs = attributes.adj_rhs();
const int m0 = settings.m0();
const int n0 = settings.n0();
const int k0 = settings.k0();
// Validate M0
ARM_COMPUTE_RETURN_ERROR_ON_MSG(m0 < 1, "Only positive integers are supported for M0");
if (adj_lhs)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(((m0 & (m0 - 1)) && (m0 != 3)) || (m0 > 16),
"Only 1,2,3,4,8,16 are supported for M0 for Lhs transposed");
}
// Validate N0
ARM_COMPUTE_RETURN_ERROR_ON_MSG(n0 < 1, "Only positive integers are supported for N0");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(((n0 & (n0 - 1)) && (n0 != 3)) || (n0 > 16),
"Only 1,2,3,4,8,16 are supported for N0");
// Validate K0
ARM_COMPUTE_RETURN_ERROR_ON_MSG(k0 < 1, "Only positive integers are supported for K0");
if (!adj_lhs || adj_rhs)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(((k0 & (k0 - 1)) && (k0 != 3)) || (k0 > 16),
"Only 1,2,3,4,8,16 are supported for K0");
}
return Status{};
}
} // namespace
Status ClComponentMatMul::validate(const Properties &properties,
const ArgumentPack<ITensorInfo> &tensors,
const Attributes &attributes,
const Settings &settings)
{
ARM_COMPUTE_UNUSED(properties);
ARM_COMPUTE_UNUSED(attributes);
const auto lhs = tensors.get_const_tensor(TensorType::ACL_SRC_0);
const auto rhs = tensors.get_const_tensor(TensorType::ACL_SRC_1);
const auto dst = tensors.get_const_tensor(TensorType::ACL_DST_0);
// Currently, the only supported case is when adj_lhs = false and adj_rhs = true
ARM_COMPUTE_RETURN_ERROR_ON((attributes.adj_lhs() != false) && (attributes.adj_rhs() != true));
// Check if Matching data type
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst);
// Data type
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst);
// All tensor infos are initialized
ARM_COMPUTE_RETURN_ERROR_ON(lhs->tensor_shape().total_size() == 0);
ARM_COMPUTE_RETURN_ERROR_ON(rhs->tensor_shape().total_size() == 0);
ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0);
// Device requirements are met
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(lhs);
// Check if block sizes are supported
MatMulKernelInfo matmul_kernel_info =
MatMulKernelInfo(attributes.adj_lhs(), attributes.adj_rhs(), settings.m0(), settings.n0(), settings.k0());
ARM_COMPUTE_RETURN_ON_ERROR(validate_matmul_kernel_info(attributes, settings));
ARM_COMPUTE_RETURN_ON_ERROR(
opencl::kernels::validate_matmul_input_shapes(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info));
// Check if dst shape is correct
const auto expected_dst_shape =
misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), expected_dst_shape);
return Status{};
}
ClComponentMatMul::ClComponentMatMul(ComponentId id,
const Properties &properties,
const ArgumentPack<ITensorInfo> &tensors,
const Attributes &attributes,
const Settings &settings)
: IGpuKernelComponent{id, properties, tensors},
_component_writer{std::make_unique<GpuCkwMatMul>(id, tensors, attributes, settings)}
{
}
ClComponentMatMul::~ClComponentMatMul()
{
}
const IGpuCkwComponentDriver *ClComponentMatMul::ckw_component_driver() const
{
return _component_writer.get();
}
} // namespace dynamic_fusion
} // namespace experimental
} // namespace arm_compute
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