diff --git a/1.1/HalPolicy.cpp b/1.1/HalPolicy.cpp
index 9f2c9be..fbd2e08 100644
--- a/1.1/HalPolicy.cpp
+++ b/1.1/HalPolicy.cpp
@@ -178,10 +178,11 @@
         return false;
     }
 
-    const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
+    armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*outputOperand);
     if (IsDynamicOutput(outputInfo))
     {
-        return Fail("%s: Dynamic output not supported", __func__);
+        ALOGD("Output shape not set, will infer from inputs");
+        outputInfo.SetShape(InferSubOutputShape(input0.GetTensorInfo().GetShape(), input1.GetTensorInfo().GetShape()));
     }
 
     if (!IsLayerSupportedForAnyBackend(__func__,
@@ -203,7 +204,12 @@
     if (endLayer)
     {
         BroadcastTensor(input0, input1, startLayer, *data.m_Network);
-        return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, 0, *endLayer, model, data);
+        return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation,
+                                                                0,
+                                                                *endLayer,
+                                                                model,
+                                                                data,
+                                                                armnn::Optional<armnn::TensorInfo>(outputInfo));
     }
 
     return Fail("%s: ProcessActivation failed", __func__);
diff --git a/OutputShapeUtils.cpp b/OutputShapeUtils.cpp
index a1a49d7..739038a 100644
--- a/OutputShapeUtils.cpp
+++ b/OutputShapeUtils.cpp
@@ -8,6 +8,42 @@
 #include <algorithm>
 #include <vector>
 
+namespace
+{
+
+using namespace armnn;
+
+TensorShape CalculateMaxShape(const TensorShape& inShape0, const TensorShape& inShape1)
+{
+    // NOTE: The inferred output size will be the maximum size along each dimension
+    // of inShape0 and inShape1, starting with the trailing dimensions, and working its way forward.
+    //
+    // Example: inShape0={4, 1, 2}, inShape1={5, 4, 3, 1} => outputShape={5, 4, 3, 2}
+
+    const unsigned int numInput0Dims = inShape0.GetNumDimensions();
+    const unsigned int numInput1Dims = inShape1.GetNumDimensions();
+
+    const unsigned int maxNumDims = std::max(numInput0Dims, numInput1Dims);
+
+    TensorShape outputShape = TensorShape(maxNumDims);
+    for (unsigned int reverseIdx = 1u; reverseIdx <= maxNumDims; ++reverseIdx)
+    {
+        const int input0Idx = numInput0Dims - reverseIdx;
+        const int input1Idx = numInput1Dims - reverseIdx;
+
+        const unsigned int input0DimSize = input0Idx >= 0 ? inShape0[input0Idx] : 0u;
+        const unsigned int input1DimSize = input1Idx >= 0 ? inShape1[input1Idx] : 0u;
+
+        const unsigned int outputIdx = maxNumDims - reverseIdx;
+        outputShape[outputIdx] = std::max(input0DimSize, input1DimSize);
+    }
+
+    return outputShape;
+}
+
+} // namespace annonymous
+
+
 namespace armnn_driver
 {
 
@@ -38,30 +74,12 @@
 
 TensorShape InferPreluOutputShape(const TensorShape& inputShape, const TensorShape& alphaShape)
 {
-    // NOTE: The inferred PReLU output size will be the maximum size along each dimension
-    // of input and alpha, starting with the trailing dimensions, and working its way forward.
-    //
-    // Example: inputShape={4, 1, 2}, alphaShape={5, 4, 3, 1} => outputShape={5, 4, 3, 2}
+    return CalculateMaxShape(inputShape, alphaShape);
+}
 
-    const unsigned int numInputDims = inputShape.GetNumDimensions();
-    const unsigned int numAlphaDims = alphaShape.GetNumDimensions();
-
-    const unsigned int maxNumDims = std::max(numInputDims, numAlphaDims);
-
-    TensorShape outputShape = TensorShape(maxNumDims);
-    for (unsigned int reverseIdx = 1u; reverseIdx <= maxNumDims; ++reverseIdx)
-    {
-        const int inputIdx = numInputDims - reverseIdx;
-        const int alphaIdx = numAlphaDims - reverseIdx;
-
-        const unsigned int inputDimSize = inputIdx >= 0 ? inputShape[inputIdx] : 0u;
-        const unsigned int alphaDimSize = alphaIdx >= 0 ? alphaShape[alphaIdx] : 0u;
-
-        const unsigned int outputIdx = maxNumDims - reverseIdx;
-        outputShape[outputIdx] = std::max(inputDimSize, alphaDimSize);
-    }
-
-    return outputShape;
+TensorShape InferSubOutputShape(const TensorShape& input0Shape, const TensorShape& input1Shape)
+{
+    return CalculateMaxShape(input0Shape, input1Shape);
 }
 
 } // namespace armnn_driver
\ No newline at end of file
diff --git a/OutputShapeUtils.hpp b/OutputShapeUtils.hpp
index d1818db..be255c2 100644
--- a/OutputShapeUtils.hpp
+++ b/OutputShapeUtils.hpp
@@ -17,6 +17,8 @@
 
 armnn::TensorShape InferPreluOutputShape(const armnn::TensorShape& inputShape, const armnn::TensorShape& alphaShape);
 
+armnn::TensorShape InferSubOutputShape(const armnn::TensorShape& input0Shape, const armnn::TensorShape& input1Shape);
+
 } // namespace armnn_driver