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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
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