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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
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