MLCE-418 Reduce layer does not support multiple axes
* Added backend specific optimization to chain new reduces layers
for each axis to simulate behaviour of a layer with multiple axes.
* Added function to calculate reduced output shape.
* Added unit tests.
* Includes rework to fix IVGCVSW-5987.
Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: I154b3698b5e6756b05b2a0b5a3f0896184efce72
diff --git a/src/backends/neon/NeonBackend.cpp b/src/backends/neon/NeonBackend.cpp
index a1299fb..b496238 100644
--- a/src/backends/neon/NeonBackend.cpp
+++ b/src/backends/neon/NeonBackend.cpp
@@ -29,6 +29,7 @@
#include "workloads/NeonDivisionWorkload.hpp"
#include "workloads/NeonFullyConnectedWorkload.hpp"
#include "workloads/NeonMultiplicationWorkload.hpp"
+#include "workloads/NeonReduceWorkload.hpp"
#include "workloads/NeonSubtractionWorkload.hpp"
#include <Optimizer.hpp>
@@ -161,6 +162,7 @@
--it;
Layer& base = **it;
+ // Fuse activation into previous layer if supported by backend
if ((base.GetType() == LayerType::DepthwiseConvolution2d || base.GetType() == LayerType::Convolution2d
|| base.GetType() == LayerType::BatchNormalization || base.GetType() == LayerType::FullyConnected
|| base.GetType() == LayerType::Addition || base.GetType() == LayerType::Multiplication
@@ -393,6 +395,25 @@
}
}
}
+
+ // Separate reduce layer with multiple axes into multiple reduce layers with 1 axis.
+ if (base.GetType() == LayerType::Reduce)
+ {
+ ReduceLayer* baseLayer = PolymorphicDowncast<ReduceLayer*>(&base);
+ ReduceDescriptor reduceDescriptor = baseLayer->GetParameters();
+
+ if (!reduceDescriptor.m_vAxis.empty() && reduceDescriptor.m_vAxis.size() > 1)
+ {
+ // Add new layers to the graph and connect them.
+ std::vector<Layer*> layers = ChainReduceLayers<ReduceLayer>(optimizationViews,
+ baseLayer,
+ reduceDescriptor);
+
+ // Replace existing baselayer with new subgraph.
+ ReplaceLayers<ReduceLayer>(optimizationViews, baseLayer, layers);
+ untouched.erase(baseLayer->GetGuid());
+ }
+ }
}
if (optimizationViews.GetSubstitutions().empty())
diff --git a/src/backends/neon/workloads/NeonReduceWorkload.cpp b/src/backends/neon/workloads/NeonReduceWorkload.cpp
index 0e1b46a..1436cd1 100644
--- a/src/backends/neon/workloads/NeonReduceWorkload.cpp
+++ b/src/backends/neon/workloads/NeonReduceWorkload.cpp
@@ -20,23 +20,28 @@
const TensorInfo& output,
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)
+ if ( desc.m_vAxis.size()==1 || desc.m_vAxis.empty())
{
- return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR,
- "NeonReduceWorkload: Reduction is supported only on 1 axis.");
+ const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input);
+ const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
+
+ arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclInputInfo.num_dimensions(),
+ input.GetNumDimensions(),
+ desc.m_vAxis);
+
+ return arm_compute::NEReductionOperation::validate(&aclInputInfo,
+ &aclOutputInfo,
+ static_cast<unsigned int>(coords[0]),
+ ConvertReductionOperationToAcl(desc),
+ desc.m_KeepDims);
}
-
- arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclInputInfo.num_dimensions(),
- input.GetNumDimensions(),
- desc.m_vAxis);
-
- return arm_compute::NEReductionOperation::validate(&aclInputInfo,
- &aclOutputInfo,
- static_cast<unsigned int>(coords[0]),
- ConvertReductionOperationToAcl(desc),
- desc.m_KeepDims);
+ else
+ {
+ // Validate layer if there are multiple axes.
+ arm_compute::Status status;
+ IS_MULTI_AXES_REDUCE_SUPPORTED(NeonReduceWorkloadValidate, input, desc, status);
+ return status;
+ }
}
NeonReduceWorkload::NeonReduceWorkload(const ReduceQueueDescriptor& descriptor, const WorkloadInfo& info)
@@ -50,6 +55,7 @@
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<unsigned int>(coords[0]),