// // Copyright © 2024 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #include "GpuFsaActivation.hpp" #include #include #include #include #include #include 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 inputTensorInfos = {}; std::vector 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>(inputTensorInfos); blob->outputTensorInfos = std::make_unique>(outputTensorInfos); } } // namespace armnn