From c625f000198218fc8d03130ee5658f73b94b2683 Mon Sep 17 00:00:00 2001
From: Sadik Armagan <sadik.armagan@arm.com>
Date: Mon, 17 Dec 2018 11:32:16 +0000
Subject: IVGCVSW-1048 RESIZE_BILINEAR NEON operator

 * Implemented NeonResizeBilinearWorkload
 * Enable ResizeBilinear Operator unit tests for Neon

!android-nn-driver:405

Change-Id: Iec3100ccaf7d246e8eaf683d1f3ec9191df5241e
---
 .../neon/workloads/NeonResizeBilinearWorkload.cpp  | 59 ++++++++++++++++++++++
 1 file changed, 59 insertions(+)
 create mode 100644 src/backends/neon/workloads/NeonResizeBilinearWorkload.cpp

(limited to 'src/backends/neon/workloads/NeonResizeBilinearWorkload.cpp')

diff --git a/src/backends/neon/workloads/NeonResizeBilinearWorkload.cpp b/src/backends/neon/workloads/NeonResizeBilinearWorkload.cpp
new file mode 100644
index 0000000000..37f97bfe0e
--- /dev/null
+++ b/src/backends/neon/workloads/NeonResizeBilinearWorkload.cpp
@@ -0,0 +1,59 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "NeonResizeBilinearWorkload.hpp"
+
+#include <aclCommon/ArmComputeUtils.hpp>
+#include <aclCommon/ArmComputeTensorUtils.hpp>
+#include <backendsCommon/CpuTensorHandle.hpp>
+#include <neon/NeonTensorHandle.hpp>
+#include <neon/NeonLayerSupport.hpp>
+
+using namespace armnn::armcomputetensorutils;
+
+namespace armnn
+{
+
+arm_compute::Status NeonResizeBilinearWorkloadValidate(const TensorInfo& input, const TensorInfo& output)
+{
+    const arm_compute::TensorInfo aclInputInfo  = armcomputetensorutils::BuildArmComputeTensorInfo(input);
+    const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
+
+    return arm_compute::NEScale::validate(&aclInputInfo,
+                                          &aclOutputInfo,
+                                          arm_compute::InterpolationPolicy::BILINEAR,
+                                          arm_compute::BorderMode::REPLICATE,
+                                          arm_compute::PixelValue(0.f),
+                                          arm_compute::SamplingPolicy::TOP_LEFT);
+}
+
+NeonResizeBilinearWorkload::NeonResizeBilinearWorkload(const ResizeBilinearQueueDescriptor& descriptor,
+                                                       const WorkloadInfo& info)
+    : BaseWorkload<ResizeBilinearQueueDescriptor>(descriptor, info)
+{
+    m_Data.ValidateInputsOutputs("NeonResizeBilinearWorkload", 1, 1);
+
+    arm_compute::ITensor& input = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+    arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+
+    arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
+    input.info()->set_data_layout(aclDataLayout);
+    output.info()->set_data_layout(aclDataLayout);
+
+    m_ResizeBilinearLayer.configure(&input,
+                                    &output,
+                                    arm_compute::InterpolationPolicy::BILINEAR,
+                                    arm_compute::BorderMode::REPLICATE,
+                                    arm_compute::PixelValue(0.f),
+                                    arm_compute::SamplingPolicy::TOP_LEFT);
+};
+
+void NeonResizeBilinearWorkload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonResizeBilinearWorkload_Execute");
+    m_ResizeBilinearLayer.run();
+}
+
+} //namespace armnn
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