From 7ac3ca67b8b38049ff373c35cdcba18c1d358a46 Mon Sep 17 00:00:00 2001 From: Teresa Charlin Date: Tue, 28 Jul 2020 15:17:12 +0100 Subject: IVGCVSW-5167 Use a generic axis in CL/Neon LogSoftmax and Softmax workload Signed-off-by: Teresa Charlin Change-Id: Id72d2c2851adcc1dd8f00a6103642b16ebe3a964 --- src/backends/aclCommon/ArmComputeUtils.hpp | 26 +++++++++++++++++----- src/backends/cl/workloads/ClLogSoftmaxWorkload.cpp | 6 +++-- src/backends/cl/workloads/ClSoftmaxWorkload.cpp | 6 +++-- .../neon/workloads/NeonLogSoftmaxWorkload.cpp | 4 ++-- .../neon/workloads/NeonSoftmaxWorkload.cpp | 4 ++-- 5 files changed, 32 insertions(+), 14 deletions(-) diff --git a/src/backends/aclCommon/ArmComputeUtils.hpp b/src/backends/aclCommon/ArmComputeUtils.hpp index eae152dc20..6b1f975350 100644 --- a/src/backends/aclCommon/ArmComputeUtils.hpp +++ b/src/backends/aclCommon/ArmComputeUtils.hpp @@ -189,19 +189,33 @@ inline std::set ComputeSplitAxis(const armnn::SplitterDescriptor& return splitAxis; } -/// Function to convert ArmNN axis (left to right) to ACL axis (right to left) ranging from [-dim, dim) +/// Function to convert ArmNN axis (left to right) to ACL axis (right to left) ranging from [-rank, rank) inline int ComputeAclAxis(const int& armnnAxis, const armnn::TensorInfo& tensor) { - int dim = static_cast(tensor.GetNumDimensions()); + int rank = static_cast(tensor.GetNumDimensions()); - ARMNN_ASSERT(dim != 0); - ARMNN_ASSERT((-1 * dim) <= armnnAxis); - ARMNN_ASSERT(armnnAxis < dim); + ARMNN_ASSERT(rank != 0); + ARMNN_ASSERT((-1 * rank) <= armnnAxis); + ARMNN_ASSERT(armnnAxis < rank); int sign = (armnnAxis < 0) ? -1 : 1; - int aclAxis = sign * dim - 1 - armnnAxis; + int aclAxis = sign * rank - 1 - armnnAxis; return aclAxis; } +/// Function to convert axis to its positive equivalent value. +/// [-rank, rank) --> [0, rank) +inline unsigned int ComputePositiveAxis(const int& axis, const armnn::TensorInfo& tensor) +{ + int rank = static_cast(tensor.GetNumDimensions()); + + ARMNN_ASSERT(rank != 0); + ARMNN_ASSERT((-1 * rank) <= axis); + ARMNN_ASSERT(axis < rank); + + int positiveAxis = (axis < 0) ? rank + axis : axis; + return static_cast(positiveAxis); +} + } // namespace armnn diff --git a/src/backends/cl/workloads/ClLogSoftmaxWorkload.cpp b/src/backends/cl/workloads/ClLogSoftmaxWorkload.cpp index bd14d514d2..c62c9d24f6 100644 --- a/src/backends/cl/workloads/ClLogSoftmaxWorkload.cpp +++ b/src/backends/cl/workloads/ClLogSoftmaxWorkload.cpp @@ -21,7 +21,8 @@ arm_compute::Status ClLogSoftmaxWorkloadValidate(const TensorInfo& input, const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input); const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); - unsigned int aclAxis = ComputeSoftmaxAclAxis(descriptor, input); + int aclAxis_int = ComputeAclAxis(descriptor.m_Axis, input); + unsigned int aclAxis = ComputePositiveAxis(aclAxis_int, input); return arm_compute::CLLogSoftmaxLayer::validate(&aclInputInfo, &aclOutputInfo, descriptor.m_Beta, aclAxis); } @@ -35,7 +36,8 @@ ClLogSoftmaxWorkload::ClLogSoftmaxWorkload(const LogSoftmaxQueueDescriptor& desc arm_compute::ICLTensor& input = static_cast(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ICLTensor& output = static_cast(m_Data.m_Outputs[0])->GetTensor(); - unsigned int aclAxis = ComputeSoftmaxAclAxis(m_Data.m_Parameters, info.m_InputTensorInfos[0]); + int aclAxis_int = ComputeAclAxis(m_Data.m_Parameters.m_Axis, info.m_InputTensorInfos[0]); + unsigned int aclAxis = ComputePositiveAxis(aclAxis_int, info.m_InputTensorInfos[0]); m_LogSoftmaxLayer.configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis); } diff --git a/src/backends/cl/workloads/ClSoftmaxWorkload.cpp b/src/backends/cl/workloads/ClSoftmaxWorkload.cpp index cbca7668ed..37746c83a6 100644 --- a/src/backends/cl/workloads/ClSoftmaxWorkload.cpp +++ b/src/backends/cl/workloads/ClSoftmaxWorkload.cpp @@ -21,7 +21,8 @@ arm_compute::Status ClSoftmaxWorkloadValidate(const TensorInfo& input, const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input); const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); - unsigned int aclAxis = ComputeSoftmaxAclAxis(descriptor, input); + int aclAxis_int = ComputeAclAxis(descriptor.m_Axis, input); + unsigned int aclAxis = ComputePositiveAxis(aclAxis_int, input); return arm_compute::CLSoftmaxLayer::validate(&aclInputInfo, &aclOutputInfo, descriptor.m_Beta, aclAxis); } @@ -35,7 +36,8 @@ ClSoftmaxWorkload::ClSoftmaxWorkload(const SoftmaxQueueDescriptor& descriptor, c arm_compute::ICLTensor& input = static_cast(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ICLTensor& output = static_cast(m_Data.m_Outputs[0])->GetTensor(); - unsigned int aclAxis = ComputeSoftmaxAclAxis(m_Data.m_Parameters, info.m_InputTensorInfos[0]); + int aclAxis_int = ComputeAclAxis(m_Data.m_Parameters.m_Axis, info.m_InputTensorInfos[0]); + unsigned int aclAxis = ComputePositiveAxis(aclAxis_int, info.m_InputTensorInfos[0]); m_SoftmaxLayer.configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis); } diff --git a/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp b/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp index 058756e9af..9c8ab072c5 100644 --- a/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp +++ b/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp @@ -23,7 +23,7 @@ arm_compute::Status NeonLogSoftmaxWorkloadValidate(const TensorInfo& input, const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input); const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); - int aclAxis = ComputeSoftmaxAclAxis(descriptor, input); + int aclAxis = ComputeAclAxis(descriptor.m_Axis, input); return arm_compute::NELogSoftmaxLayer::validate(&aclInputInfo, &aclOutputInfo, descriptor.m_Beta, aclAxis); } @@ -38,7 +38,7 @@ NeonLogSoftmaxWorkload::NeonLogSoftmaxWorkload(const LogSoftmaxQueueDescriptor& arm_compute::ITensor& output = PolymorphicDowncast(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique(memoryManager); - int aclAxis = ComputeSoftmaxAclAxis(m_Data.m_Parameters, info.m_InputTensorInfos[0]); + int aclAxis = ComputeAclAxis(m_Data.m_Parameters.m_Axis, info.m_InputTensorInfos[0]); layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis); m_LogSoftmaxLayer.reset(layer.release()); } diff --git a/src/backends/neon/workloads/NeonSoftmaxWorkload.cpp b/src/backends/neon/workloads/NeonSoftmaxWorkload.cpp index b36bf7695f..37e7bfbac5 100644 --- a/src/backends/neon/workloads/NeonSoftmaxWorkload.cpp +++ b/src/backends/neon/workloads/NeonSoftmaxWorkload.cpp @@ -23,7 +23,7 @@ arm_compute::Status NeonSoftmaxWorkloadValidate(const TensorInfo& input, const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input); const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); - int aclAxis = ComputeSoftmaxAclAxis(descriptor, input); + int aclAxis = ComputeAclAxis(descriptor.m_Axis, input); return arm_compute::NESoftmaxLayer::validate(&aclInputInfo, &aclOutputInfo, descriptor.m_Beta, aclAxis); } @@ -38,7 +38,7 @@ NeonSoftmaxWorkload::NeonSoftmaxWorkload(const SoftmaxQueueDescriptor& descripto arm_compute::ITensor& output = PolymorphicDowncast(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique(memoryManager); - int aclAxis = ComputeSoftmaxAclAxis(m_Data.m_Parameters, info.m_InputTensorInfos[0]); + int aclAxis = ComputeAclAxis(m_Data.m_Parameters.m_Axis, info.m_InputTensorInfos[0]); layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis); m_SoftmaxLayer.reset(layer.release()); } -- cgit v1.2.1