IVGCVSW-4549 Add front end for new QLSTM layer

* Added new layer QLstm (Android R HAL 1.3)
* Made necessary updates to APIs
* Added unit tests
* This layer is functionally equivalent to the
  original unquantized LSTM layer with some
  additonal quantization features added. Due
  to this, original LstmParams are used for
  this layer.

Signed-off-by: James Conroy <james.conroy@arm.com>
Change-Id: I5b7f2d2fb6e17e81573b41a31bc55f49ae79608f

1 files changed, 57 insertions, 1 deletions

diff --git a/src/armnn/test/InferOutputTests.hpp b/src/armnn/test/InferOutputTests.hpp
index b03449b568..70afbc9b3f 100644
--- a/src/armnn/test/InferOutputTests.hpp
+++ b/src/armnn/test/InferOutputTests.hpp
@@ -7,7 +7,6 @@
 
 #include "TestUtils.hpp"
 
-
 #include <Graph.hpp>
 #include <layers/ArgMinMaxLayer.hpp>
 #include <layers/BatchToSpaceNdLayer.hpp>
@@ -530,6 +529,63 @@ void DepthwiseConvolution2dInferOutputShapeTest()
     BOOST_CHECK(expectedOutputShape == depthwiseConvolution2dLayer->InferOutputShapes(shapes).at(0));
 }
 
+// QLstm
+void QLstmInferOutputShapeImpl(const armnn::QLstmDescriptor descriptor,
+                               const std::vector<armnn::TensorShape>& inputShapes,
+                               std::vector<armnn::TensorShape>& outputShapes)
+{
+    armnn::Graph graph;
+    armnn::QLstmLayer* const qLstmLayer = graph.AddLayer<armnn::QLstmLayer>(descriptor, "qLstm");
+    outputShapes = qLstmLayer->InferOutputShapes(inputShapes);
+}
+
+void QLstmInferOutputShapeTest()
+{
+    armnn::QLstmDescriptor descriptor;
+    descriptor.m_PeepholeEnabled = true;
+    descriptor.m_CifgEnabled = false;
+    descriptor.m_ProjectionEnabled = false;
+
+    // Input shapes
+    const std::vector<unsigned int> inputShape{ 2, 5 };
+    const std::vector<unsigned int> previousOutputInShape{ 2, 4 };
+    const std::vector<unsigned int> previousCellStateInShape{ 2, 4 };
+
+    armnn::TensorShape inputTensorShape(2, inputShape.data());
+    armnn::TensorShape previousOutputInTensorShape(2, previousOutputInShape.data());
+    armnn::TensorShape previousCellStateInTensorShape(2, previousCellStateInShape.data());
+
+    std::vector<armnn::TensorShape> inShapes
+    {
+        inputTensorShape,
+        previousOutputInTensorShape,
+        previousCellStateInTensorShape
+    };
+
+    // Output shapes
+    const std::vector<unsigned int> outputStateOutShape{ 2, 4 };
+    const std::vector<unsigned int> cellStateOutShape{ 2, 4 };
+    const std::vector<unsigned int> outputShape{ 2, 4 };
+    armnn::TensorShape outputStateOutTensorShape(2, outputShape.data());
+    armnn::TensorShape cellStateOutTensorShape(2, cellStateOutShape.data());
+    armnn::TensorShape outputTensorShape(2, outputShape.data());
+
+    std::vector<armnn::TensorShape> expectedOutShapes
+    {
+        outputStateOutTensorShape,
+        cellStateOutTensorShape,
+        outputTensorShape
+    };
+
+    std::vector<armnn::TensorShape> actualOutShapes;
+    BOOST_CHECK_NO_THROW(QLstmInferOutputShapeImpl(descriptor, inShapes, actualOutShapes));
+
+    BOOST_CHECK(actualOutShapes.size() == 3);
+    BOOST_CHECK(expectedOutShapes[0] == actualOutShapes[0]);
+    BOOST_CHECK(expectedOutShapes[1] == actualOutShapes[1]);
+    BOOST_CHECK(expectedOutShapes[2] == actualOutShapes[2]);
+}
+
 // QuantizedLstm
 void QuantizedLstmInferOutputShapeImpl(const std::vector<armnn::TensorShape>& inputShapes,
                                        std::vector<armnn::TensorShape>& outputShapes)