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Diffstat (limited to 'src/backends/gpuFsa/layers/GpuFsaActivation.cpp')
| -rw-r--r-- | src/backends/gpuFsa/layers/GpuFsaActivation.cpp | 126 |
1 files changed, 126 insertions, 0 deletions
diff --git a/src/backends/gpuFsa/layers/GpuFsaActivation.cpp b/src/backends/gpuFsa/layers/GpuFsaActivation.cpp new file mode 100644 index 0000000000..4b0773fb48 --- /dev/null +++ b/src/backends/gpuFsa/layers/GpuFsaActivation.cpp @@ -0,0 +1,126 @@ +// +// Copyright © 2024 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "GpuFsaActivation.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/GpuTanh.h> +#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuSigmoid.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 GpuFsaActivationValidate(const TensorInfo& input, + const ActivationDescriptor& 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 aclInputInfo = BuildArmComputeTensorInfo(input, input.GetNumDimensions()); + aclInputInfo.set_are_values_constant(input.IsConstant()); + + arm_compute::ITensorInfo* inputInfo = workloadContext.create_tensor_info(aclInputInfo); + + switch (descriptor.m_Function) + { + case ActivationFunction::TanH: + { + if ( descriptor.m_A != 1 || descriptor.m_B != 1) + { + return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR, + "Activation function TanH only works with a=1 and b=1"); + } + return GpuTanh::validate_op(sketch, inputInfo); + } + case ActivationFunction::Sigmoid: + { + return GpuSigmoid::validate_op(sketch, inputInfo); + } + default: + return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR, + std::string("Activation function currently not supported in GpuFsa: ") + + GetActivationFunctionAsCString(descriptor.m_Function)); + } + +} + +void GpuFsaActivationCreateOp(GpuFsaPreCompiledBlob* blob, + const TensorInfo& input, + const ActivationDescriptor& 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(input, input.GetNumDimensions()); + + aclInput0Info.set_are_values_constant(input.IsConstant()); + + inputTensorInfos.emplace_back(workloadContext->create_tensor_info(aclInput0Info)); + + // Validate operator, check status and update reasonIfUnsupported + arm_compute::Status aclStatus{}; + switch (descriptor.m_Function) + { + case ActivationFunction::TanH: + { + aclStatus = GpuTanh::validate_op(*sketch, inputTensorInfos[0]); + break; + } + case ActivationFunction::Sigmoid: + { + aclStatus = GpuSigmoid::validate_op(*sketch, inputTensorInfos[0]); + break; + } + default: + throw InvalidArgumentException(std::string("Activation function currently not supported in GpuFsa: ") + + GetActivationFunctionAsCString(descriptor.m_Function)); + + } + const bool supported = aclStatus.error_code() == arm_compute::ErrorCode::OK; + if (!supported) + { + throw BackendCapabilityException("\"GpuFsa\" backend failed during Activation layer validation"); + } + + arm_compute::ITensorInfo* activationOutputInfo{}; + switch (descriptor.m_Function) + { + case ActivationFunction::TanH: + { + activationOutputInfo = GpuTanh::create_op(*sketch, inputTensorInfos[0]); + break; + } + case ActivationFunction::Sigmoid: + { + activationOutputInfo = GpuSigmoid::create_op(*sketch, inputTensorInfos[0]); + break; + } + default: + throw InvalidArgumentException(std::string("Activation function currently not supported in GpuFsa: ") + + GetActivationFunctionAsCString(descriptor.m_Function)); + + } + + // 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, activationOutputInfo, 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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