IVGCVSW-3808 Add ElementwiseBinaryLayer

!android-nn-driver:9329

 * Added ElementwiseBinaryLayer that can represent all ElementwiseBinary
   operations including Add, Div, Sub, Maximum, Mul and Minimum.
 * Updated Delegate to use ElementwiseBinaryLayer instead of the Add,
   Div, Sub, Maximum, Mul and Minimum layers.
 * Updated Deserializer to use ElementwiseBinaryLayer instead of the Add,
   Div, Sub, Maximum, Mul and Minimum layers.
 * Updated OnnxParser to use ElementwiseBinaryLayer instead of the Add
   layer.
 * Updated TfLiteParser to use ElementwiseBinaryLayer instead of the Add,
   Div, Sub, Maximum, Mul and Minimum layers.
 * Updated CL and Neon tests to use ElementwiseBinaryLayer.
 * Updated CL and Neon Backend Specific Optimizations to accept
   ElementBinaryLayers as well as Add, Div, Mul, Sub, Maximum and Minimum
   layers.

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: I7cbb96b60eb01f0e2b57b0541016d48a08b86c75

1 files changed, 30 insertions, 4 deletions

diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index 62dfc6a38b..6a5963ddcb 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -1,5 +1,5 @@
 //
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 
@@ -35,11 +35,8 @@ DataType GetBiasDataType(DataType inputDataType)
         case DataType::Float32:
             return DataType::Float32;
         case DataType::QAsymmS8:
-            return DataType::Signed32;
         case DataType::QAsymmU8:
-            return DataType::Signed32;
         case DataType::QSymmS8:
-            return DataType::Signed32;
         case DataType::QSymmS16:
             return DataType::Signed32;
         default:
@@ -3668,6 +3665,35 @@ void ComparisonQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
     }
 }
 
+void ElementwiseBinaryQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
+{
+    const std::string descriptorName{"ElementwiseBinaryQueueDescriptor"};
+
+    ValidateNumInputs(workloadInfo,  descriptorName, 2);
+    ValidateNumOutputs(workloadInfo, descriptorName, 1);
+
+    const TensorInfo& inputTensorInfo0 = workloadInfo.m_InputTensorInfos[0];
+    const TensorInfo& inputTensorInfo1 = workloadInfo.m_InputTensorInfos[1];
+    const TensorInfo& outputTensorInfo = workloadInfo.m_OutputTensorInfos[0];
+
+    std::vector<DataType> supportedTypes =
+            {
+                    DataType::BFloat16,
+                    DataType::Float16,
+                    DataType::Float32,
+                    DataType::QAsymmS8,
+                    DataType::QAsymmU8,
+                    DataType::QSymmS16,
+                    DataType::Signed32
+            };
+
+    ValidateDataTypes(inputTensorInfo0, supportedTypes, descriptorName);
+    ValidateDataTypes(inputTensorInfo1, supportedTypes, descriptorName);
+
+    ValidateTensorDataTypesMatch(inputTensorInfo0, outputTensorInfo, descriptorName, "input", "output");
+    ValidateTensorDataTypesMatch(inputTensorInfo1, outputTensorInfo, descriptorName, "input", "output");
+}
+
 void ElementwiseUnaryQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
 {
     const std::string descriptorName{"ElementwiseUnaryQueueDescriptor"};