MLCE-753 Expand Tensorshape for relevent layers before verifying support

   Previously we were adding a reshape layer to "broadcast" tensors
   for elementwise operations. This broadcast was happening too late
   and was really just an expand dims. This was breaking the constant
   attributes of tensors and layer support of certain backends.

 * Remove addition of reshape layer when expanding dimensions
 * Replace broadcast function with expand dims to equal rank function
 * Fix some error status checks in various layers
 * Add new TensorUtil function that expands dims to a defined rank
 * Add unit tests to new TensorUtil function

Signed-off-by: Ryan OShea <ryan.oshea3@arm.com>
Change-Id: I31aca47c98075fef4f86864a15470f5faa55ab8d

1 files changed, 7 insertions, 72 deletions

diff --git a/delegate/src/DelegateUtils.hpp b/delegate/src/DelegateUtils.hpp
index 3e74225b15..1aa9029271 100644
--- a/delegate/src/DelegateUtils.hpp
+++ b/delegate/src/DelegateUtils.hpp
@@ -13,6 +13,7 @@
 #include <armnn/utility/NumericCast.hpp>
 
 #include <armnnUtils/Permute.hpp>
+#include <armnnUtils/TensorUtils.hpp>
 
 #include <tensorflow/lite/builtin_ops.h>
 #include <tensorflow/lite/c/builtin_op_data.h>
@@ -188,91 +189,25 @@ TfLiteStatus Connect(armnn::IConnectableLayer* layer,
     return kTfLiteOk;
 }
 
-armnn::IConnectableLayer* BroadcastTensor(const armnn::TensorInfo& inputInfo0,
-                                          const armnn::TensorInfo& inputInfo1,
-                                          armnn::IConnectableLayer* startLayer,
-                                          TfLiteContext* tfLiteContext,
-                                          TfLiteNode* tfLiteNode,
-                                          armnnDelegate::DelegateData& delegateData)
+void ExpandTensorRankToEqual(armnn::TensorInfo& inputInfo0,
+                             armnn::TensorInfo& inputInfo1)
 {
     unsigned int inputDimensions0 = inputInfo0.GetNumDimensions();
     unsigned int inputDimensions1 = inputInfo1.GetNumDimensions();
 
     if (inputDimensions0 == inputDimensions1)
     {
-        auto status = Connect(startLayer, tfLiteNode, delegateData);
-        return status == kTfLiteOk ? startLayer : nullptr;
+        return;
     }
 
     unsigned int biggerInputDimensions = std::max(inputDimensions0, inputDimensions1);
-    unsigned int dimDifference = static_cast<unsigned int>(std::abs(armnn::numeric_cast<int>(inputDimensions0) -
-                                                                    armnn::numeric_cast<int>(inputDimensions1)));
 
     bool input0IsSmaller = inputDimensions0 < inputDimensions1;
-    const armnn::TensorInfo& smallInfo = input0IsSmaller ? inputInfo0 : inputInfo1;
-    const armnn::TensorShape& smallShape = smallInfo.GetShape();
-
-    std::vector<unsigned int> reshapedDimensions(biggerInputDimensions, 1);
-    for (unsigned int i = dimDifference; i < biggerInputDimensions; ++i)
-    {
-        reshapedDimensions[i] = smallShape[i - dimDifference];
-    }
-
-    armnn::TensorInfo reshapedInfo = smallInfo;
-    reshapedInfo.SetShape(armnn::TensorShape{ armnn::numeric_cast<unsigned int>(reshapedDimensions.size()),
-                                              reshapedDimensions.data() });
-
-    armnn::ReshapeDescriptor reshapeDescriptor;
-    reshapeDescriptor.m_TargetShape = reshapedInfo.GetShape();
-    bool isSupported = false;
-    armnn::BackendId setBackend;
-    FORWARD_LAYER_SUPPORT_FUNC("RESHAPE",
-                               tfLiteContext,
-                               IsReshapeSupported,
-                               delegateData.m_Backends,
-                               isSupported,
-                               setBackend,
-                               smallInfo,
-                               reshapedInfo,
-                               reshapeDescriptor);
-    if (!isSupported)
-    {
-        return nullptr;
-    }
+    armnn::TensorInfo& smallInfo = input0IsSmaller ? inputInfo0 : inputInfo1;
+    const armnn::TensorShape& newShape = armnnUtils::ExpandDimsToRank(smallInfo.GetShape(), biggerInputDimensions);
 
-    ARMNN_ASSERT(delegateData.m_Network != nullptr);
-    // Add Reshape layer
-    armnn::IConnectableLayer* reshapeLayer = delegateData.m_Network->AddReshapeLayer(reshapeDescriptor);
-    reshapeLayer->SetBackendId(setBackend);
-    ARMNN_ASSERT(reshapeLayer != nullptr);
-    reshapeLayer->GetOutputSlot(0).SetTensorInfo(reshapedInfo);
+    smallInfo.SetShape(newShape);
 
-    if (input0IsSmaller)
-    {
-        delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tfLiteNode->inputs->data[0])]
-            ->Connect(reshapeLayer->GetInputSlot(0));
-        reshapeLayer->GetOutputSlot(0).Connect(startLayer->GetInputSlot(0));
-        delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tfLiteNode->inputs->data[1])]
-            ->Connect(startLayer->GetInputSlot(1));
-    }
-    else
-    {
-        delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tfLiteNode->inputs->data[1])]
-            ->Connect(reshapeLayer->GetInputSlot(0));
-        reshapeLayer->GetOutputSlot(0).Connect(startLayer->GetInputSlot(1));
-        delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tfLiteNode->inputs->data[0])]
-            ->Connect(startLayer->GetInputSlot(0));
-    }
-
-    // Prepare output slots
-    for (unsigned int outputIndex = 0; outputIndex < startLayer->GetNumOutputSlots(); ++outputIndex)
-    {
-        armnn::IOutputSlot& outputSlot = startLayer->GetOutputSlot(outputIndex);
-        delegateData.m_OutputSlotForNode
-            [static_cast<unsigned long>(tfLiteNode->outputs->data[outputIndex])] = &outputSlot;
-    }
-
-    return reshapeLayer;
 }
 
 TfLiteStatus FusedActivation(TfLiteContext* tfLiteContext,