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-rw-r--r--src/armnn/backends/RefWorkloads/RefBaseConstantWorkload.cpp49
1 files changed, 0 insertions, 49 deletions
diff --git a/src/armnn/backends/RefWorkloads/RefBaseConstantWorkload.cpp b/src/armnn/backends/RefWorkloads/RefBaseConstantWorkload.cpp
deleted file mode 100644
index 647677b4fb..0000000000
--- a/src/armnn/backends/RefWorkloads/RefBaseConstantWorkload.cpp
+++ /dev/null
@@ -1,49 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "RefBaseConstantWorkload.hpp"
-
-#include "RefWorkloadUtils.hpp"
-
-#include <armnn/Types.hpp>
-
-#include <boost/assert.hpp>
-
-#include <cstring>
-
-namespace armnn
-{
-
-template <armnn::DataType DataType>
-void RefBaseConstantWorkload<DataType>::Execute() const
-{
- // Considering the reference backend independently, it could be possible to initialise the intermediate tensor
- // created by the layer output handler at workload construction time, rather than at workload execution time.
- // However, this is not an option for other backends (e.g. CL). For consistency, we prefer to align all
- // implementations.
- // A similar argument can be made about performing the memory copy in the first place (the layer output handler
- // could have a non-owning reference to the layer output tensor managed by the const input layer); again, this is
- // not an option for other backends, and the extra complexity required to make this work for the reference backend
- // may not be worth the effort (skipping a memory copy in the first inference).
- if (!m_RanOnce)
- {
- const ConstantQueueDescriptor& data = this->m_Data;
-
- BOOST_ASSERT(data.m_LayerOutput != nullptr);
-
- const TensorInfo& outputInfo = GetTensorInfo(data.m_Outputs[0]);
- BOOST_ASSERT(data.m_LayerOutput->GetTensorInfo().GetNumBytes() == outputInfo.GetNumBytes());
-
- memcpy(GetOutputTensorData<void>(0, data), data.m_LayerOutput->GetConstTensor<void>(),
- outputInfo.GetNumBytes());
-
- m_RanOnce = true;
- }
-}
-
-template class RefBaseConstantWorkload<DataType::Float32>;
-template class RefBaseConstantWorkload<DataType::QuantisedAsymm8>;
-
-} //namespace armnn