From 16f82f987b44b090a01807a2c79ed7fcc6bf80ea Mon Sep 17 00:00:00 2001
From: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Date: Mon, 14 Sep 2020 16:12:44 +0100
Subject: IVGCVSW-5305 AddBroadcastReshapeLayer as optimizer

 * Remove AddBroadcastReshapeLayer from TfLiteParser
 * Add AddBroadcastReshapeLayer as optimizer
 * AddBroadcastReshapeLayer optimizer unit tests
 * Load-scope dynamic tensor broadcasting unit tests

Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I3549e85b71b41cbd4d96c0f1ece7887acbca76d1
---
 src/armnn/layers/ElementwiseBaseLayer.cpp | 31 ++++++++++++++++++++++++-------
 1 file changed, 24 insertions(+), 7 deletions(-)

(limited to 'src/armnn/layers/ElementwiseBaseLayer.cpp')

diff --git a/src/armnn/layers/ElementwiseBaseLayer.cpp b/src/armnn/layers/ElementwiseBaseLayer.cpp
index b4a3cea9e1..631e08c2ac 100644
--- a/src/armnn/layers/ElementwiseBaseLayer.cpp
+++ b/src/armnn/layers/ElementwiseBaseLayer.cpp
@@ -22,18 +22,29 @@ ElementwiseBaseLayer::ElementwiseBaseLayer(unsigned int numInputSlots, unsigned
 std::vector<TensorShape> ElementwiseBaseLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
 {
     ARMNN_ASSERT(inputShapes.size() == 2);
-    auto& input0 = inputShapes[0];
-    auto& input1 = inputShapes[1];
+    TensorShape input0 = inputShapes[0];
+    TensorShape input1 = inputShapes[1];
+
+    if (m_ShapeInferenceMethod == ShapeInferenceMethod::ValidateOnly)
+    {
+        ARMNN_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions());
+    }
+    else if (m_ShapeInferenceMethod == ShapeInferenceMethod::InferAndValidate &&
+             inputShapes[0].GetNumDimensions() < inputShapes[1].GetNumDimensions())
+    {
+        input1 = inputShapes[0];
+        input0 = inputShapes[1];
+    }
 
-    // Get the max of the inputs.
-    ARMNN_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions());
     unsigned int numDims = input0.GetNumDimensions();
-    std::vector<unsigned int> dims(numDims);
+    unsigned int shiftedDims = input0.GetNumDimensions() - input1.GetNumDimensions();
 
-    for (unsigned int i = 0; i < numDims; i++)
+    // Get the max of the inputs.
+    std::vector<unsigned int> dims(numDims);
+    for (unsigned int i = shiftedDims; i < numDims; i++)
     {
         unsigned int dim0 = input0[i];
-        unsigned int dim1 = input1[i];
+        unsigned int dim1 = input1[i - shiftedDims];
 
 #if !NDEBUG
         // Validate inputs are broadcast compatible.
@@ -44,6 +55,12 @@ std::vector<TensorShape> ElementwiseBaseLayer::InferOutputShapes(const std::vect
         dims[i] = std::max(dim0, dim1);
     }
 
+    // Fill in the rest of the shifted dimensions.
+    for (unsigned int i = 0; i < shiftedDims; i++)
+    {
+        dims[i] = input0[i];
+    }
+
     return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) });
 }
 
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