GpuFsaBatchMatMul.cpp

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//
// Copyright © 2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "GpuFsaBatchMatMul.hpp"
#include "UtilsGpuFsa.hpp"
 
#include <aclCommon/ArmComputeTensorUtils.hpp>
 
#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadContext.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuMatMul.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h>
 
using namespace arm_compute::experimental::dynamic_fusion;
using namespace armnn::armcomputetensorutils;
 
namespace armnn
{
 
arm_compute::Status GpuFsaBatchMatMulValidate(const TensorInfo& input0,
                                              const TensorInfo& input1,
                                              const BatchMatMulDescriptor& descriptor)
{
    // Create a new workload sketch, for validation purposes
    auto compileCtx         = arm_compute::CLKernelLibrary::get().get_compile_context();
    auto workloadContext    = GpuWorkloadContext(&compileCtx);
    GpuWorkloadSketch sketch{ &workloadContext };
 
    arm_compute::TensorInfo aclInput0Info = BuildArmComputeTensorInfo(input0, input0.GetNumDimensions());
    arm_compute::TensorInfo aclInput1Info = BuildArmComputeTensorInfo(input1, input1.GetNumDimensions());
 
    aclInput0Info.set_are_values_constant(input0.IsConstant());
    aclInput1Info.set_are_values_constant(input1.IsConstant());
 
    arm_compute::ITensorInfo*  inputInfo0 = workloadContext.create_tensor_info(aclInput0Info);
    arm_compute::ITensorInfo*  inputInfo1 = workloadContext.create_tensor_info(aclInput1Info);
 
    MatMulAttributes matMulAttributes{};
    matMulAttributes.adj_lhs(descriptor.m_TransposeX);
    matMulAttributes.adj_rhs(descriptor.m_TransposeY);
    GpuMatMulSettings matmulSettings{};
    matmulSettings.m0(1);
    matmulSettings.n0(1);
    matmulSettings.k0(1);
 
    return GpuMatMul::validate_op(sketch, inputInfo0, inputInfo1, matMulAttributes, matmulSettings);
}
 
void GpuFsaBatchMatMulCreateOp(GpuFsaPreCompiledBlob* blob,
                               const TensorInfo& input0,
                               const TensorInfo& input1,
                               const BatchMatMulDescriptor& descriptor)
{
    GpuWorkloadSketch* sketch           = blob->sketch.get();
    GpuWorkloadContext* workloadContext = blob->workloadContext.get();
    std::vector<arm_compute::ITensorInfo*> inputTensorInfos  = {};
    std::vector<arm_compute::ITensorInfo*> outputTensorInfos = {};
 
    arm_compute::TensorInfo aclInput0Info = BuildArmComputeTensorInfo(input0, input0.GetNumDimensions());
    arm_compute::TensorInfo aclInput1Info = BuildArmComputeTensorInfo(input1, input1.GetNumDimensions());
 
    aclInput0Info.set_are_values_constant(input0.IsConstant());
    aclInput1Info.set_are_values_constant(input1.IsConstant());
 
    inputTensorInfos.emplace_back(workloadContext->create_tensor_info(aclInput0Info));
    inputTensorInfos.emplace_back(workloadContext->create_tensor_info(aclInput1Info));
 
    MatMulAttributes matMulAttributes{};
    matMulAttributes.adj_lhs(descriptor.m_TransposeX);
    matMulAttributes.adj_rhs(descriptor.m_TransposeY);
    GpuMatMulSettings matmulSettings{};
    matmulSettings.m0(1);
    matmulSettings.n0(1);
    matmulSettings.k0(1);
 
    // Validate operator, check status and update reasonIfUnsupported
    arm_compute::Status aclStatus = GpuMatMul::validate_op(*sketch,
                                                           inputTensorInfos[0],
                                                           inputTensorInfos[1],
                                                           matMulAttributes,
                                                           matmulSettings);
 
    const bool supported = aclStatus.error_code() == arm_compute::ErrorCode::OK;
    if (!supported)
    {
        throw BackendCapabilityException("\"GpuFsa\" backend failed during elementwise binary add validation");
    }
 
    arm_compute::ITensorInfo* addOutputInfo = GpuMatMul::create_op(*sketch,
                                                                   inputTensorInfos[0],
                                                                   inputTensorInfos[1],
                                                                   matMulAttributes,
                                                                   matmulSettings);
 
    // Temporary fix until fusing attempt is make for GpuFsa backend and Output layer workload is created.
    outputTensorInfos.emplace_back(workloadContext->create_tensor_info());
    GpuOutput::create_op(*sketch, addOutputInfo, outputTensorInfos[0]);
 
    // Store the TensorInfos within the blob as unique_ptrs to be used later
    blob->inputTensorInfos  = std::make_unique<std::vector<arm_compute::ITensorInfo*>>(inputTensorInfos);
    blob->outputTensorInfos = std::make_unique<std::vector<arm_compute::ITensorInfo*>>(outputTensorInfos);
}
 
} // namespace armnn