IVGCVSW-2792 Update Neon Mul/Sub workload for latest CL master

* Update Neon Subtraction/Multiplication to use BaseWorkload
* Add Uint8 tests for Subtraction/Multiplication

Change-Id: Ied2aa048924817a4db0025b9bd9e54151667bd74
Signed-off-by: Conor Kennedy <conor.kennedy@arm.com>

1 files changed, 63 insertions, 0 deletions

diff --git a/src/backends/neon/workloads/NeonMultiplicationWorkload.cpp b/src/backends/neon/workloads/NeonMultiplicationWorkload.cpp
new file mode 100644
index 0000000000..6398b65946
--- /dev/null
+++ b/src/backends/neon/workloads/NeonMultiplicationWorkload.cpp
@@ -0,0 +1,63 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "NeonMultiplicationWorkload.hpp"
+
+#include "NeonWorkloadUtils.hpp"
+
+#include <arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h>
+
+namespace armnn
+{
+
+arm_compute::Status NeonMultiplicationWorkloadValidate(const TensorInfo& input0,
+                                                       const TensorInfo& input1,
+                                                       const TensorInfo& output)
+{
+    const arm_compute::TensorInfo aclInput1 = armcomputetensorutils::BuildArmComputeTensorInfo(input0);
+    const arm_compute::TensorInfo aclInput2 = armcomputetensorutils::BuildArmComputeTensorInfo(input1);
+    const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output);
+
+    // At the time of writing, configure() will fail if a rounding policy other than TO_ZERO is supplied to it,
+    // when providing a scale of 1.0 for F32 tensors, even though the provided rounding policy appears to be
+    // ignored for F32 tensors.
+    return arm_compute::NEPixelWiseMultiplication::validate(&aclInput1,
+                                                            &aclInput2,
+                                                            &aclOutput,
+                                                            1.0f,
+                                                            arm_compute::ConvertPolicy::SATURATE,
+                                                            arm_compute::RoundingPolicy::TO_ZERO);
+}
+
+NeonMultiplicationWorkload::NeonMultiplicationWorkload(const MultiplicationQueueDescriptor& descriptor,
+                                                       const WorkloadInfo& info)
+    : BaseWorkload<MultiplicationQueueDescriptor>(descriptor, info)
+{
+    m_Data.ValidateInputsOutputs("NeonMultiplicationWorkload", 2, 1);
+
+    arm_compute::ITensor& input1 = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+    arm_compute::ITensor& input2 = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
+    arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+
+    // At the time of writing, configure() will fail if a rounding policy other than TO_ZERO is supplied to it,
+    // when providing a scale of 1.0 for F32 tensors, even though the provided rounding policy appears to be
+    // ignored for F32 tensors.
+    auto layer = std::make_unique<arm_compute::NEPixelWiseMultiplication>();
+    layer->configure(&input1,
+                     &input2,
+                     &output,
+                     1.0f,
+                     arm_compute::ConvertPolicy::SATURATE,
+                     arm_compute::RoundingPolicy::TO_ZERO);
+    m_PixelWiseMultiplication.reset(layer.release());
+}
+
+void NeonMultiplicationWorkload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonMultiplicationWorkload_Execute");
+    m_PixelWiseMultiplication->run();
+}
+
+} //namespace armnn