1 files changed, 20 insertions, 7 deletions
diff --git a/src/armnn/layers/ComparisonLayer.cpp b/src/armnn/layers/ComparisonLayer.cpp
index b6cd48b268..c097cddf4d 100644
--- a/src/armnn/layers/ComparisonLayer.cpp
+++ b/src/armnn/layers/ComparisonLayer.cpp
@@ -1,5 +1,5 @@
 //
-// Copyright © 2019 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2019-2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 
@@ -36,24 +36,37 @@ ComparisonLayer* ComparisonLayer::Clone(Graph& graph) const
 std::vector<TensorShape> ComparisonLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
 {
     ARMNN_ASSERT(inputShapes.size() == 2);
-    const TensorShape& input0 = inputShapes[0];
-    const TensorShape& input1 = inputShapes[1];
+    TensorShape input0 = inputShapes[0];
+    TensorShape input1 = inputShapes[1];
 
-    ARMNN_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions());
-    unsigned int numDims = input0.GetNumDimensions();
+    if (inputShapes[0].GetNumDimensions() < inputShapes[1].GetNumDimensions())
+    {
+        input1 = inputShapes[0];
+        input0 = inputShapes[1];
+    }
+    unsigned int numDims     = input0.GetNumDimensions();
+    unsigned int shiftedDims = input0.GetNumDimensions() - input1.GetNumDimensions();
 
+    // Get the max of the inputs.
     std::vector<unsigned int> dims(numDims);
-    for (unsigned int i = 0; i < numDims; i++)
+    for (unsigned int i = shiftedDims; i < numDims; i++)
     {
         unsigned int dim0 = input0[i];
-        unsigned int dim1 = input1[i];
+        unsigned int dim1 = input1[i - shiftedDims];
 
+        // Validate inputs are broadcast compatible.
         ARMNN_ASSERT_MSG(dim0 == dim1 || dim0 == 1 || dim1 == 1,
                          "Dimensions should either match or one should be of size 1.");
 
         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()) });
 }