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| author | Teresa Charlin <teresa.charlinreyes@arm.com> | 2020-05-11 16:10:38 +0100 |
|---|---|---|
| committer | TeresaARM <teresa.charlinreyes@arm.com> | 2020-05-13 18:34:12 +0000 |
| commit | c1f6b09cc22b6e2de3d9eb88aec1778d0308a2b3 (patch) | |
| tree | 14a70415b6d17b42246798a293dfdd13cbe4c123 /src/backends/cl/workloads/ClSoftmaxUint8Workload.cpp | |
| parent | 0c32ccfcd0b770cdd4eeb9d778b7f72a233e229a (diff) | |
| download | armnn-c1f6b09cc22b6e2de3d9eb88aec1778d0308a2b3.tar.gz | |
IVGCVSW-4753 Refactor CL Softmax workload generalizing for different datatype
* Change ComputeSoftmaxAclAxis to work with int and uint axis
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ibbfa9ec7e2f0416e6885673212a767419c871cca
Diffstat (limited to 'src/backends/cl/workloads/ClSoftmaxUint8Workload.cpp')
| -rw-r--r-- | src/backends/cl/workloads/ClSoftmaxUint8Workload.cpp | 46 |
1 files changed, 0 insertions, 46 deletions
diff --git a/src/backends/cl/workloads/ClSoftmaxUint8Workload.cpp b/src/backends/cl/workloads/ClSoftmaxUint8Workload.cpp deleted file mode 100644 index f14ea11c82..0000000000 --- a/src/backends/cl/workloads/ClSoftmaxUint8Workload.cpp +++ /dev/null @@ -1,46 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "ClSoftmaxUint8Workload.hpp" -#include "ClWorkloadUtils.hpp" - -#include <aclCommon/ArmComputeUtils.hpp> -#include <cl/ClTensorHandle.hpp> -#include <backendsCommon/CpuTensorHandle.hpp> - -namespace armnn -{ - -ClSoftmaxUint8Workload::ClSoftmaxUint8Workload(const SoftmaxQueueDescriptor& descriptor, const WorkloadInfo& info, - std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager) - : Uint8Workload<SoftmaxQueueDescriptor>(descriptor, info) - , m_SoftmaxLayer(memoryManager) -{ - m_Data.ValidateInputsOutputs("ClSoftmaxUint8Workload", 1, 1); - - arm_compute::ICLTensor& input = static_cast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ICLTensor& output = static_cast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); - - const auto outputQuantization = output.info()->quantization_info(); - - if ((!outputQuantization.scale().empty() && outputQuantization.scale()[0] != (1.0f / 256.0f)) || - (!outputQuantization.offset().empty() && outputQuantization.offset()[0] != 0) || - outputQuantization.scale().empty() || outputQuantization.offset().empty()) - { - throw InvalidArgumentException( - "Invalid quantization for output. Only scale = 1.0f / 256.0f and offset = 0 supported"); - } - - unsigned int aclAxis = ComputeSoftmaxAclAxis(m_Data.m_Parameters, info.m_InputTensorInfos[0]); - m_SoftmaxLayer.configure(&input, &output, descriptor.m_Parameters.m_Beta, aclAxis); -} - -void ClSoftmaxUint8Workload::Execute() const -{ - ARMNN_SCOPED_PROFILING_EVENT_CL("ClSoftmaxUint8Workload_Execute"); - RunClFunction(m_SoftmaxLayer, CHECK_LOCATION()); -} - -} //namespace armnn |