IVGCVSW-7109: Add Batch MatMul front end support - Reference

  * Descriptors added for BatchMatMul
  * Layer definition added
  * Input validation added (will likely change when opt. param support comes in)
  * Ref workload implementation for BatchMatMul added (will also change with opt. param support)
  * Ref layer tests made for BatchMatMul
  * CMake and other build files updated

Signed-off-by: Samuel Yap <samuel.yap@arm.com>
Change-Id: Ic885301da543ee0fbe7922b85e7f9658c4efc617

1 files changed, 82 insertions, 0 deletions

diff --git a/src/armnn/Descriptors.cpp b/src/armnn/Descriptors.cpp
index c740fd03ad..f9576271d5 100644
--- a/src/armnn/Descriptors.cpp
+++ b/src/armnn/Descriptors.cpp
@@ -455,4 +455,86 @@ uint32_t DepthwiseConvolution2dDescriptor::GetNumInputs() const
     return armnn::GetNumInputs(m_BiasEnabled);
 }
 
+std::pair<std::pair<unsigned int, unsigned int>, std::pair<unsigned int, unsigned int>>
+BatchMatMulDescriptor::GetAxesToMul(
+    const BatchMatMulDescriptor& desc,
+    const TensorShape& tensorXShape,
+    const TensorShape& tensorYShape)
+{
+    // May refactor to just work on one input per call - makes it less confusing and also
+    // allows more flexibility (i.e. in Layer output shape inference)
+
+    auto xNumDims = tensorXShape.GetNumDimensions();
+    auto yNumDims = tensorYShape.GetNumDimensions();
+
+    std::pair<unsigned int, unsigned int> xAxes = { xNumDims-2, xNumDims-1 };
+    std::pair<unsigned int, unsigned int> yAxes = { yNumDims-2, yNumDims-1 };
+
+    if(desc.m_DataLayoutX.has_value())
+    {
+        switch(desc.m_DataLayoutX.value())
+        {
+            case DataLayout::NDHWC:
+            case DataLayout::NHWC:
+                xAxes.first -= 1;
+                xAxes.second -= 1;
+                break;
+            case DataLayout::NCDHW:
+            case DataLayout::NCHW:
+            default:
+                break;
+        }
+    }
+
+    if(desc.m_DataLayoutY.has_value())
+    {
+        switch(desc.m_DataLayoutY.value())
+        {
+            case DataLayout::NDHWC:
+            case DataLayout::NHWC:
+                yAxes.first -= 1;
+                yAxes.second -= 1;
+                break;
+            case DataLayout::NCDHW:
+            case DataLayout::NCHW:
+            default:
+                break;
+        }
+    }
+
+    return { xAxes, yAxes};
+}
+
+std::pair<std::vector<unsigned int>, std::vector<unsigned int>> BatchMatMulDescriptor::GetAxesNotMul(
+    const BatchMatMulDescriptor& desc,
+    const TensorShape& inputXShape,
+    const TensorShape& inputYShape)
+{
+    // May refactor to just work on one input per call - makes it less confusing and also
+    // allows more flexibility (i.e. in Layer output shape inference)
+    auto axesToMul = BatchMatMulDescriptor::GetAxesToMul(desc, inputXShape, inputYShape);
+
+    std::vector<unsigned int> axesXNotMul;
+    std::vector<unsigned int> axesYNotMul;
+
+    for(unsigned int i = 0; i < inputXShape.GetNumDimensions(); i++)
+    {
+        if(i == axesToMul.first.first || i == axesToMul.first.second)
+        {
+            continue;
+        }
+        axesXNotMul.push_back(i);
+    }
+    for(unsigned int i = 0; i < inputYShape.GetNumDimensions(); i++)
+    {
+        if(i == axesToMul.second.first || i == axesToMul.second.second)
+        {
+            continue;
+        }
+        axesYNotMul.push_back(i);
+    }
+
+    return { axesXNotMul, axesYNotMul };
+}
+
 }