GpuFsaCast.cpp

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//
// Copyright © 2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "GpuFsaCast.hpp"
#include "gpuFsa/GpuFsaBackendId.hpp"
 
#include <aclCommon/ArmComputeTensorUtils.hpp>
 
#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuCast.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadContext.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h>
 
using namespace arm_compute::experimental::dynamic_fusion;
 
namespace armnn
{
 
static constexpr arm_compute::ConvertPolicy g_AclConvertPolicy = arm_compute::ConvertPolicy::SATURATE;
 
static CastAttributes CastAttributesFromTensorInfo(const TensorInfo& input)
{
    using namespace armcomputetensorutils;
 
    CastAttributes cast_attr;
    arm_compute::DataType dataType = GetArmComputeDataType(input.GetDataType(), false);
    cast_attr.data_type(dataType).convert_policy(g_AclConvertPolicy);
    return cast_attr;
}
 
arm_compute::Status GpuFsaCastValidate(const TensorInfo& input, const TensorInfo& output)
{
    using namespace armcomputetensorutils;
 
    // 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 aclinputInfo = BuildArmComputeTensorInfo(input, input.GetNumDimensions());
 
    aclinputInfo.set_are_values_constant(input.IsConstant());
 
    arm_compute::ITensorInfo*  inputInfo0 = workloadContext.create_tensor_info(aclinputInfo);
 
    CastAttributes cast_attr = CastAttributesFromTensorInfo(output);
 
    arm_compute::Status aclStatus = GpuCast::validate_op(sketch, inputInfo0, cast_attr);
#ifndef NDEBUG
    const bool validated = aclStatus.error_code() == arm_compute::ErrorCode::OK;
    if (!validated)
    {
        std::cout << "GpuFsaCastValidate failed: " << aclStatus.error_description() << std::endl;
    }
#endif
    return aclStatus;
}
 
void GpuFsaCastCreateOp(GpuFsaPreCompiledBlob* blob,
                        const TensorInfo& input,
                        const TensorInfo& output)
{
    using namespace armcomputetensorutils;
 
    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 aclinputInfo = BuildArmComputeTensorInfo(input, input.GetNumDimensions());
 
    aclinputInfo.set_are_values_constant(input.IsConstant());
 
    inputTensorInfos.emplace_back(workloadContext->create_tensor_info(aclinputInfo));
 
    CastAttributes cast_attr = CastAttributesFromTensorInfo(output);
 
    // Validate operator, check status and update reasonIfUnsupported
    arm_compute::Status aclStatus = GpuCast::validate_op(*sketch, inputTensorInfos[0], cast_attr);
    const bool validated = aclStatus.error_code() == arm_compute::ErrorCode::OK;
    if (!validated)
    {
        throw BackendCapabilityException("\"" + std::string(GpuFsaBackendId())
                                         + "\" backend failed during cast operator validation");
    }
 
    arm_compute::ITensorInfo* castOutputInfo =
            GpuCast::create_op(*sketch, inputTensorInfos[0], cast_attr);
 
    // 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, castOutputInfo, 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