| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ClConvertFp16ToFp32Workload.hpp" |
| #include <backends/cl/ClTensorHandle.hpp> |
| |
| #include "ClWorkloadUtils.hpp" |
| |
| namespace armnn |
| { |
| using namespace armcomputetensorutils; |
| |
| static constexpr arm_compute::ConvertPolicy g_AclConvertPolicy = arm_compute::ConvertPolicy::SATURATE; |
| |
| ClConvertFp16ToFp32Workload::ClConvertFp16ToFp32Workload( |
| const ConvertFp16ToFp32QueueDescriptor& descriptor, const WorkloadInfo& info) : |
| Float16ToFloat32Workload<ConvertFp16ToFp32QueueDescriptor>(descriptor, info) |
| { |
| this->m_Data.ValidateInputsOutputs("ClConvertFp16ToFp32Workload", 1, 1); |
| |
| arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(this->m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(this->m_Data.m_Outputs[0])->GetTensor(); |
| |
| m_Layer.configure(&input, &output, g_AclConvertPolicy, 0); |
| } |
| |
| void ClConvertFp16ToFp32Workload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL("ClConvertFp16ToFp32Workload_Execute"); |
| m_Layer.run(); |
| } |
| |
| arm_compute::Status ClConvertFp16ToFp32WorkloadValidate(const TensorInfo& input, const TensorInfo& output) |
| { |
| if (input.GetDataType() != DataType::Float16) |
| { |
| return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR, "Input should be Float16"); |
| } |
| if (output.GetDataType() != DataType::Float32) |
| { |
| return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR, "Output should be Float32"); |
| } |
| |
| const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input); |
| const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output); |
| |
| const arm_compute::Status aclStatus = arm_compute::CLDepthConvertLayer::validate( |
| &aclInputInfo, &aclOutputInfo, g_AclConvertPolicy, 0); |
| |
| return aclStatus; |
| } |
| |
| |
| } //namespace armnn |