| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "RefStackWorkload.hpp" |
| |
| #include "RefWorkloadUtils.hpp" |
| #include "Stack.hpp" |
| |
| #include <Profiling.hpp> |
| |
| namespace armnn |
| { |
| |
| RefStackWorkload::RefStackWorkload(const StackQueueDescriptor& descriptor, |
| const WorkloadInfo& info) |
| : BaseWorkload(descriptor, info) |
| {} |
| |
| void RefStackWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefStackWorkload_Execute"); |
| |
| // Can perform a simple concatenation when axis == 0 |
| if (!m_Data.m_Parameters.m_Axis) |
| { |
| float* output = GetOutputTensorData<float>(0, m_Data); |
| ARMNN_ASSERT(output != nullptr); |
| |
| unsigned int numInputs = m_Data.m_Parameters.m_NumInputs; |
| unsigned int inputLength = GetTensorInfo(m_Data.m_Inputs[0]).GetNumElements(); |
| |
| for (unsigned int inputIdx=0; inputIdx<numInputs; ++inputIdx) |
| { |
| const float* input = GetInputTensorData<float>(inputIdx, m_Data); |
| for (unsigned int elmt=0; elmt<inputLength; ++elmt) |
| { |
| output[(inputIdx * inputLength) + elmt] = input[elmt]; |
| } |
| } |
| return; |
| } |
| |
| std::vector<std::unique_ptr<Decoder<float>>> inputDecoders; |
| for (unsigned int i=0; i<m_Data.m_Inputs.size(); ++i) |
| { |
| inputDecoders.push_back(MakeDecoder<float>(GetTensorInfo(m_Data.m_Inputs[i]), |
| m_Data.m_Inputs[i]->Map())); |
| } |
| std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(m_Data.m_Outputs[0]), |
| m_Data.m_Outputs[0]->Map()); |
| |
| Stack(m_Data, inputDecoders, *outputEncoder); |
| } |
| |
| } // namespace armnn |