From ae12306486efc55293a40048618abe5e8b19151b Mon Sep 17 00:00:00 2001 From: Matthew Sloyan Date: Fri, 7 May 2021 14:18:01 +0000 Subject: Revert "MLCE-418 Reduce layer does not support multiple axes" This reverts commit d905decd256558bbee165e636ce4242ac3b9c917. Reason for revert: LargeGraph_TENSOR_FLOAT32/FLOAT16 CTS tests failures Change-Id: Ie69826549e73775825f45134375b5b2c41aebd01 --- src/backends/neon/workloads/NeonReduceWorkload.cpp | 53 +++++----------------- 1 file changed, 11 insertions(+), 42 deletions(-) (limited to 'src/backends/neon/workloads') diff --git a/src/backends/neon/workloads/NeonReduceWorkload.cpp b/src/backends/neon/workloads/NeonReduceWorkload.cpp index 6125f3609d..0e1b46a3a1 100644 --- a/src/backends/neon/workloads/NeonReduceWorkload.cpp +++ b/src/backends/neon/workloads/NeonReduceWorkload.cpp @@ -21,52 +21,22 @@ arm_compute::Status NeonReduceWorkloadValidate(const TensorInfo& input, const ReduceDescriptor& desc) { const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input); + const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); + if (!desc.m_vAxis.empty() && desc.m_vAxis.size() > 1) + { + return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR, + "NeonReduceWorkload: Reduction is supported only on 1 axis."); + } arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclInputInfo.num_dimensions(), input.GetNumDimensions(), desc.m_vAxis); - // As ACL only support one axis, validate the layer for each axis if more than one is present. - if (!desc.m_vAxis.empty() && desc.m_vAxis.size() > 1) - { - arm_compute::Status status; - - for (unsigned int i = 0; i != desc.m_vAxis.size(); ++i) - { - TensorInfo inputToModify = input; - std::vector singleAxis(1, desc.m_vAxis[i]); - - // Calculate the output shape using the input shape for a single axis. - // Currently the output TensorInfo inferred will be reduced upon multiple axis - // which will fail validation as only one axis is supported. - const TensorShape& reducedShape = ComputeReductionTensorShape(inputToModify, singleAxis, desc.m_KeepDims); - inputToModify.SetShape(reducedShape); - - const arm_compute::TensorInfo aclOutputInfoModified = - armcomputetensorutils::BuildArmComputeTensorInfo(inputToModify); - - status = arm_compute::NEReductionOperation::validate(&aclInputInfo, - &aclOutputInfoModified, - static_cast(coords[i]), - ConvertReductionOperationToAcl(desc), - desc.m_KeepDims); - if (!status) - { - break; - } - } - return status; - } - else - { - const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); - - return arm_compute::NEReductionOperation::validate(&aclInputInfo, - &aclOutputInfo, - static_cast(coords[0]), - ConvertReductionOperationToAcl(desc), - desc.m_KeepDims); - } + return arm_compute::NEReductionOperation::validate(&aclInputInfo, + &aclOutputInfo, + static_cast(coords[0]), + ConvertReductionOperationToAcl(desc), + desc.m_KeepDims); } NeonReduceWorkload::NeonReduceWorkload(const ReduceQueueDescriptor& descriptor, const WorkloadInfo& info) @@ -80,7 +50,6 @@ NeonReduceWorkload::NeonReduceWorkload(const ReduceQueueDescriptor& descriptor, arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(input.info()->num_dimensions(), info.m_InputTensorInfos[0].GetNumDimensions(), m_Data.m_Parameters.m_vAxis); - m_Layer.configure(&input, &output, static_cast(coords[0]), -- cgit v1.2.1