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Diffstat (limited to 'src/backends/gpuFsa/layers/GpuFsaCast.cpp')
| -rw-r--r-- | src/backends/gpuFsa/layers/GpuFsaCast.cpp | 101 |
1 files changed, 101 insertions, 0 deletions
diff --git a/src/backends/gpuFsa/layers/GpuFsaCast.cpp b/src/backends/gpuFsa/layers/GpuFsaCast.cpp new file mode 100644 index 0000000000..b5a0747428 --- /dev/null +++ b/src/backends/gpuFsa/layers/GpuFsaCast.cpp @@ -0,0 +1,101 @@ +// +// 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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