commit 55518ca7faaf6c2b0cd567afe9fb39d529a10150
author Narumol Prangnawarat <narumol.prangnawarat@arm.com> Fri Nov 20 14:50:54 2020 +0000
committer Francis Murtagh <francis.murtagh@arm.com> Fri Nov 20 17:35:57 2020 +0000
tree eed61cf0055788a96ab2dc4b16f16d944d2d7ef1
parent 63e75dce4d685521f53b26b987d20d11829a4126

IVGCVSW-5544 Fix FullyConnected Delegate tests

 * Correct input shape

Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I9d1fe4c8ef32a9dfba7f7fdd6af314e9a522fce8

delegate/src/FullyConnected.hpp

diff --git a/delegate/src/FullyConnected.hpp b/delegate/src/FullyConnected.hpp
index b79f6a2..53251f7 100644
--- a/delegate/src/FullyConnected.hpp
+++ b/delegate/src/FullyConnected.hpp
@@ -129,6 +129,27 @@
         biasTensorInfo = armnn::TensorInfo(armnn::TensorShape({1}), GetDataType(tfLiteInputTensor));
     }
 
+    armnn::TensorInfo reshapedTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
+
+    if (inputTensorInfo.GetNumDimensions() > 2)
+    {
+        // Calculate reshape to flatten to 2D [batch_size, input_size]
+        std::vector<unsigned int> reshapedDimensions(2);
+        reshapedDimensions[1] = weightsTensorInfo.GetShape()[1];
+        reshapedDimensions[0] = inputTensorInfo.GetNumElements() / reshapedDimensions[1];
+
+        if (inputTensorInfo.GetNumElements() % reshapedDimensions[1] != 0)
+        {
+            TF_LITE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnDelegate: Failed to deduce input tensor shape from filter size #%d #%d node #%d: ",
+                reshapedDimensions[1], operatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+
+        reshapedTensorInfo.SetShape(armnn::TensorShape{ 2, reshapedDimensions.data() });
+    }
+
     armnn::FullyConnectedDescriptor descriptor;
     descriptor.m_TransposeWeightMatrix = true;
     descriptor.m_BiasEnabled           = biasEnabled;
@@ -141,7 +162,7 @@
                                    IsFullyConnectedSupported,
                                    delegateData.m_Backends,
                                    isSupported,
-                                   inputTensorInfo,
+                                   reshapedTensorInfo,
                                    outputTensorInfo,
                                    weightsTensorInfo,
                                    biasTensorInfo,
@@ -184,22 +205,6 @@
     if (inputTensorInfo.GetNumDimensions() > 2)
     {
         // Add reshape to flatten to 2D [batch_size, input_size]
-        std::vector<unsigned int> reshapedDimensions(2);
-        reshapedDimensions[1] = weightsTensorInfo.GetShape()[1];
-        reshapedDimensions[0] = inputTensorInfo.GetNumElements() / reshapedDimensions[1];
-
-        if (inputTensorInfo.GetNumElements() % reshapedDimensions[1] != 0)
-        {
-            TF_LITE_MAYBE_KERNEL_LOG(
-                tfLiteContext,
-                "TfLiteArmnnDelegate: Failed to deduce input tensor shape from filter size #%d #%d node #%d: ",
-                reshapedDimensions[1], operatorCode, nodeIndex);
-            return kTfLiteError;
-        }
-
-        armnn::TensorInfo reshapedTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
-        reshapedTensorInfo.SetShape(armnn::TensorShape{ 2, reshapedDimensions.data() });
-
         armnn::ReshapeDescriptor reshapeDescriptor;
         reshapeDescriptor.m_TargetShape = reshapedTensorInfo.GetShape();
         reshapeLayer = delegateData.m_Network->AddReshapeLayer(reshapeDescriptor);
@@ -210,7 +215,6 @@
         // Connect
         delegateData.m_OutputSlotForNode[tfLiteNode->inputs->data[0]]->Connect(reshapeLayer->GetInputSlot(0));
         reshapeLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
-        armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
         delegateData.m_OutputSlotForNode[tfLiteNode->outputs->data[0]] = &outputSlot;
     }