IVGCVSW-7244 ConcatLayer overlapping views on TFLiteParser

 * Added ability to calculate dynamic tensors and propagate
   them through the model so that when those tensors are later
   used as inputs they have the right shapes.
 * Added InferOutputShapes to DetectionPostProcessLayer.
 * Added InferOutputShapes to MeanLayer.
 * Added InferOutputShapes to RankLayer.
 * Added InferOutputShapes to ReduceLayer.
 * Fixed typos in TfLiteParser.

Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: I880c0716938ef278f5dbf01a8a73a5cc99ce5ded

1 files changed, 25 insertions, 9 deletions

diff --git a/src/armnn/layers/DetectionPostProcessLayer.cpp b/src/armnn/layers/DetectionPostProcessLayer.cpp
index 28c6d50659..33f894414a 100644
--- a/src/armnn/layers/DetectionPostProcessLayer.cpp
+++ b/src/armnn/layers/DetectionPostProcessLayer.cpp
@@ -1,5 +1,5 @@
 //
-// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 
@@ -49,30 +49,46 @@ void DetectionPostProcessLayer::ValidateTensorShapesFromInputs()
 
     ARMNN_ASSERT_MSG(GetNumOutputSlots() == 4, "DetectionPostProcessLayer: The layer should return 4 outputs.");
 
-    unsigned int detectedBoxes = m_Param.m_MaxDetections * m_Param.m_MaxClassesPerDetection;
+    std::vector<TensorShape> inferredShapes = InferOutputShapes(
+            { GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
+              GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape() });
 
-    const TensorShape& inferredDetectionBoxes = TensorShape({ 1, detectedBoxes, 4 });
-    const TensorShape& inferredDetectionScores = TensorShape({ 1, detectedBoxes });
-    const TensorShape& inferredNumberDetections = TensorShape({ 1 });
+    ARMNN_ASSERT(inferredShapes.size() == 4);
+    ARMNN_ASSERT(inferredShapes[0].GetDimensionality() == Dimensionality::Specified);
+    ARMNN_ASSERT(inferredShapes[1].GetDimensionality() == Dimensionality::Specified);
+    ARMNN_ASSERT(inferredShapes[2].GetDimensionality() == Dimensionality::Specified);
+    ARMNN_ASSERT(inferredShapes[3].GetDimensionality() == Dimensionality::Specified);
 
-    ValidateAndCopyShape(outputShape, inferredDetectionBoxes, m_ShapeInferenceMethod, "DetectionPostProcessLayer");
+    ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "DetectionPostProcessLayer");
 
     ValidateAndCopyShape(GetOutputSlot(1).GetTensorInfo().GetShape(),
-                         inferredDetectionScores,
+                         inferredShapes[1],
                          m_ShapeInferenceMethod,
                          "DetectionPostProcessLayer", 1);
 
     ValidateAndCopyShape(GetOutputSlot(2).GetTensorInfo().GetShape(),
-                         inferredDetectionScores,
+                         inferredShapes[2],
                          m_ShapeInferenceMethod,
                          "DetectionPostProcessLayer", 2);
 
     ValidateAndCopyShape(GetOutputSlot(3).GetTensorInfo().GetShape(),
-                         inferredNumberDetections,
+                         inferredShapes[3],
                          m_ShapeInferenceMethod,
                          "DetectionPostProcessLayer", 3);
 }
 
+std::vector<TensorShape> DetectionPostProcessLayer::InferOutputShapes(const std::vector<TensorShape>&) const
+{
+    unsigned int detectedBoxes = m_Param.m_MaxDetections * m_Param.m_MaxClassesPerDetection;
+
+    std::vector<TensorShape> results;
+    results.push_back({ 1, detectedBoxes, 4 });
+    results.push_back({ 1, detectedBoxes });
+    results.push_back({ 1, detectedBoxes });
+    results.push_back({ 1 });
+    return results;
+}
+
 Layer::ConstantTensors DetectionPostProcessLayer::GetConstantTensorsByRef()
 {
     // For API stability DO NOT ALTER order and add new members to the end of vector