From 460a179b53d5543d98d3e72c60458d4b0e3225a4 Mon Sep 17 00:00:00 2001
From: Mike Kelly <mike.kelly@arm.com>
Date: Tue, 1 Aug 2023 11:31:55 +0100
Subject: IVGCVSW-7899 Cannot handle tensors with more than 5 dimensions

 * Fixed issue where then dimensions specificity didn't match the number
   of dimensions.

Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: Ic4da6f23c1e8ca38f321aa88c69ef57558a8f393
---
 delegate/classic/src/ClassicDelegateUtils.hpp | 16 ++++++++--------
 delegate/opaque/src/OpaqueDelegateUtils.hpp   | 14 +++++++-------
 shim/sl/canonical/CanonicalUtils.cpp          |  8 +++++---
 3 files changed, 20 insertions(+), 18 deletions(-)

diff --git a/delegate/classic/src/ClassicDelegateUtils.hpp b/delegate/classic/src/ClassicDelegateUtils.hpp
index 52e9f5cf63..2806716334 100644
--- a/delegate/classic/src/ClassicDelegateUtils.hpp
+++ b/delegate/classic/src/ClassicDelegateUtils.hpp
@@ -371,7 +371,7 @@ armnn::TensorInfo GetTensorInfoForTfLiteTensor(const TfLiteTensor& tfLiteTensor,
         {
             std::vector<unsigned int> safeShape = { 1 };
             bool dimensionsSpecificity[1] = { true };
-            armnn::TensorShape tensorShape(armnn::numeric_cast<unsigned int>(safeShape.size()),
+            armnn::TensorShape tensorShape(safeShape.size(),
                                            safeShape.data(),
                                            dimensionsSpecificity);
             ret = armnn::TensorInfo(tensorShape, type);
@@ -388,21 +388,21 @@ armnn::TensorInfo GetTensorInfoForTfLiteTensor(const TfLiteTensor& tfLiteTensor,
     }
     else
     {
-        std::vector<unsigned int> tensorDims(static_cast<unsigned int>(tensorDimensionSize));
-        bool dimensionsSpecificity[5] = { true, true, true, true, true };
-        for (unsigned int i = 0; i < static_cast<unsigned int>(tensorDimensionSize); ++i) {
+        std::vector<unsigned int> tensorDims(tensorDimensionSize);
+        std::vector<unsigned char> dimensionsSpecificity(tensorDimensionSize, true);
+        for (int i = 0; i < tensorDimensionSize; ++i) {
             auto dim = tfLiteTensor.dims->data[i];
-            if (dim == 0)
+            if (dim <= 0)
             {
                 dimensionsSpecificity[i] = false;
             }
             tensorDims[i] = static_cast<unsigned int>(dim);
         }
-        armnn::TensorShape tensorShape(static_cast<unsigned int>(tensorDimensionSize),
+        armnn::TensorShape tensorShape(tensorDimensionSize,
                                        tensorDims.data(),
-                                       dimensionsSpecificity);
+                                       reinterpret_cast<const bool *>(dimensionsSpecificity.data()));
 
-        if(tflite::IsConstantTensor(&tfLiteTensor))
+        if (tflite::IsConstantTensor(&tfLiteTensor))
         {
             ret = armnn::TensorInfo(tensorShape, type);
             ret.SetConstant(true);
diff --git a/delegate/opaque/src/OpaqueDelegateUtils.hpp b/delegate/opaque/src/OpaqueDelegateUtils.hpp
index fd943c8ec9..1c90ee0722 100644
--- a/delegate/opaque/src/OpaqueDelegateUtils.hpp
+++ b/delegate/opaque/src/OpaqueDelegateUtils.hpp
@@ -443,7 +443,7 @@ armnn::TensorInfo GetTensorInfoForTfLiteOpaqueTensor(const TfLiteOpaqueTensor* t
             std::vector<unsigned int> safeShape = { 1 };
             bool dimensionsSpecificity[1] = { true };
 
-            armnn::TensorShape tensorShape(armnn::numeric_cast<unsigned int>(safeShape.size()),
+            armnn::TensorShape tensorShape(safeShape.size(),
                                            safeShape.data(),
                                            dimensionsSpecificity);
             ret = armnn::TensorInfo(tensorShape, type);
@@ -461,25 +461,25 @@ armnn::TensorInfo GetTensorInfoForTfLiteOpaqueTensor(const TfLiteOpaqueTensor* t
     }
     else
     {
-        std::vector<unsigned int> tensorDims(static_cast<unsigned int>(tensorDimensionSize));
-        bool dimensionsSpecificity[5] = { true, true, true, true, true };
+        std::vector<unsigned int> tensorDims(tensorDimensionSize);
+        std::vector<unsigned char> dimensionsSpecificity(tensorDimensionSize, true);
 
         for (int32_t i = 0; i < tensorDimensionSize; ++i)
         {
             int32_t dim = TfLiteOpaqueTensorDim(tfLiteTensor, i);
 
-            if (dim == 0)
+            if (dim <= 0)
             {
                 dimensionsSpecificity[i] = false;
             }
             tensorDims[i] = static_cast<unsigned int>(dim);
         }
 
-        armnn::TensorShape tensorShape(static_cast<unsigned int>(tensorDimensionSize),
+        armnn::TensorShape tensorShape(tensorDimensionSize,
                                        tensorDims.data(),
-                                       dimensionsSpecificity);
+                                       reinterpret_cast<const bool *>(dimensionsSpecificity.data()));
 
-        if(IsConstantTensor(tfLiteTensor))
+        if (IsConstantTensor(tfLiteTensor))
         {
             ret = armnn::TensorInfo(tensorShape, type);
             ret.SetConstant(true);
diff --git a/shim/sl/canonical/CanonicalUtils.cpp b/shim/sl/canonical/CanonicalUtils.cpp
index 622d4b111d..08a728c293 100644
--- a/shim/sl/canonical/CanonicalUtils.cpp
+++ b/shim/sl/canonical/CanonicalUtils.cpp
@@ -1,5 +1,5 @@
 //
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 
@@ -152,7 +152,7 @@ armnn::TensorInfo GetTensorInfoForOperand(const Operand& operand)
         }
         else
         {
-            bool dimensionsSpecificity[5] = { true, true, true, true, true };
+            std::vector<unsigned char> dimensionsSpecificity(operand.dimensions.size(), true);
             int count = 0;
             std::for_each(operand.dimensions.data(),
                           operand.dimensions.data() +  operand.dimensions.size(),
@@ -165,7 +165,9 @@ armnn::TensorInfo GetTensorInfoForOperand(const Operand& operand)
                               count++;
                           });
 
-            TensorShape tensorShape(operand.dimensions.size(), operand.dimensions.data(), dimensionsSpecificity);
+            TensorShape tensorShape(operand.dimensions.size(),
+                                    operand.dimensions.data(),
+                                    reinterpret_cast<const bool *>(dimensionsSpecificity.data()));
             ret = TensorInfo(tensorShape, type);
         }
     }
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