diff options
author | Francis Murtagh <francis.murtagh@arm.com> | 2018-08-29 12:42:10 +0100 |
---|---|---|
committer | Matthew Bentham <matthew.bentham@arm.com> | 2018-09-17 17:21:23 +0100 |
commit | e7a86a4a3363993fb41b1ea62f23b3643b8b0c78 (patch) | |
tree | 6d054cae92a13412129525e4f9ea441e7d8c6b73 /src/armnn/backends/RefWorkloads/RefDivisionFloat32Workload.cpp | |
parent | a68241066c3e797dab70f515d2c55aaa74abf564 (diff) | |
download | armnn-e7a86a4a3363993fb41b1ea62f23b3643b8b0c78.tar.gz |
IVGCVSW-1200 Division layer
*IVGCVSW-1772 Create QueueDescriptors
*IVGCVSW-1773 Add a CL implementation of the DivisionWorkload
*IVGCVSW-1774 Add Neon implementation of the DivisionWorkload
*IVGCVSW-1775 Add a Ref implementation of the DivisionWorkload
*IVGCVSW-1776 Add a Division Layer
* Added simple division unit tests with broadcasting
Change-Id: I05751fb7f868789f6c06f91e8d25e52b4f12ab5e
Diffstat (limited to 'src/armnn/backends/RefWorkloads/RefDivisionFloat32Workload.cpp')
-rw-r--r-- | src/armnn/backends/RefWorkloads/RefDivisionFloat32Workload.cpp | 31 |
1 files changed, 31 insertions, 0 deletions
diff --git a/src/armnn/backends/RefWorkloads/RefDivisionFloat32Workload.cpp b/src/armnn/backends/RefWorkloads/RefDivisionFloat32Workload.cpp new file mode 100644 index 0000000000..7cbd1fae5b --- /dev/null +++ b/src/armnn/backends/RefWorkloads/RefDivisionFloat32Workload.cpp @@ -0,0 +1,31 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// See LICENSE file in the project root for full license information. +// + +#include "RefDivisionFloat32Workload.hpp" + +#include "Division.hpp" +#include "RefWorkloadUtils.hpp" + +#include "Profiling.hpp" + +namespace armnn +{ + +void RefDivisionFloat32Workload::Execute() const +{ + ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefDivisionFloat32Workload_Execute"); + + const TensorShape& inShape0 = GetTensorInfo(m_Data.m_Inputs[0]).GetShape(); + const TensorShape& inShape1 = GetTensorInfo(m_Data.m_Inputs[1]).GetShape(); + const TensorShape& outShape = GetTensorInfo(m_Data.m_Outputs[0]).GetShape(); + + float* outputData = GetOutputTensorDataFloat(0, m_Data); + const float* inputData0 = GetInputTensorDataFloat(0, m_Data); + const float* inputData1 = GetInputTensorDataFloat(1, m_Data); + + Division(inShape0, inShape1, outShape, inputData0, inputData1, outputData); +} + +} //namespace armnn |