From 81beae3a870004795275e9266bc43d845b9f78db Mon Sep 17 00:00:00 2001
From: Matthew Sloyan <matthew.sloyan@arm.com>
Date: Tue, 13 Jul 2021 19:46:11 +0100
Subject: IVGCVSW-6119 ConstTensorsAsInput: FullyConnected

 * Constant weights and biases are now stored as Constant layers.
 * Updated Serializer, Deserializer and unit tests to reflect this.
 * Updated TfLiteDelegate, TfLiteParser and OnnxParser.
 * Updated Schema with IsConstant and ConstantTensorsAsInputs.
 * Updated Ref backend to handle constant weights and
   bias as inputs rather than reading from member variables.
 * Added dynamic or constant input EndToEnd tests.

!android-nn-driver:5959

Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: Ibf3cf437df1100e4b322b0d303c575c6339f9696
---
 .../workloads/RefFullyConnectedWorkload.cpp        | 42 ++++++----------------
 1 file changed, 11 insertions(+), 31 deletions(-)

(limited to 'src/backends/reference/workloads')

diff --git a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
index 99e3eab075..5a7951ec48 100644
--- a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
+++ b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
@@ -16,20 +16,6 @@ RefFullyConnectedWorkload::RefFullyConnectedWorkload(
     const FullyConnectedQueueDescriptor& descriptor, const WorkloadInfo& info)
         : BaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info)
 {
-    if (descriptor.m_Parameters.m_ConstantWeights)
-    {
-        m_Weight = std::make_unique<ScopedTensorHandle>(*(descriptor.m_Weight));
-        const TensorInfo& rWeightInfo = m_Weight->GetTensorInfo();
-        m_WeightShape = rWeightInfo.GetShape();
-        m_WeightDecoder = MakeDecoder<float>(rWeightInfo, m_Weight->Map(true));
-
-        if (descriptor.m_Parameters.m_BiasEnabled)
-        {
-            m_Bias = std::make_unique<ScopedTensorHandle>(*(descriptor.m_Bias));
-            const TensorInfo& biasInfo = m_Bias->GetTensorInfo();
-            m_BiasDecoder = MakeDecoder<float>(biasInfo, m_Bias->Map(true));
-        }
-    }
 }
 
 void RefFullyConnectedWorkload::PostAllocationConfigure()
@@ -44,18 +30,15 @@ void RefFullyConnectedWorkload::PostAllocationConfigure(std::vector<ITensorHandl
     ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
     m_InputShape = inputInfo.GetShape();
 
-    if (!m_Data.m_Parameters.m_ConstantWeights)
+    const TensorInfo& rWeightInfo = GetTensorInfo(inputs[1]);
+    ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
+    m_WeightShape = rWeightInfo.GetShape();
+    m_WeightDecoder = MakeDecoder<float>(rWeightInfo);
+
+    if (m_Data.m_Parameters.m_BiasEnabled)
     {
-        const TensorInfo& rWeightInfo = GetTensorInfo(inputs[1]);
-        ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
-        m_WeightShape = rWeightInfo.GetShape();
-        m_WeightDecoder = MakeDecoder<float>(rWeightInfo);
-
-        if (m_Data.m_Parameters.m_BiasEnabled)
-        {
-            const TensorInfo& biasInfo = GetTensorInfo(inputs[2]);
-            m_BiasDecoder = MakeDecoder<float>(biasInfo);
-        }
+        const TensorInfo& biasInfo = GetTensorInfo(inputs[2]);
+        m_BiasDecoder = MakeDecoder<float>(biasInfo);
     }
 
     const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
@@ -87,13 +70,10 @@ void RefFullyConnectedWorkload::Execute(std::vector<ITensorHandle*> inputs, std:
     std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(inputs[0]), inputs[0]->Map());
     std::unique_ptr<Encoder<float>> OutputEncoder = MakeEncoder<float>(GetTensorInfo(outputs[0]), outputs[0]->Map());
 
-    if (!m_Data.m_Parameters.m_ConstantWeights)
+    m_WeightDecoder->Reset(inputs[1]->Map());
+    if (m_Data.m_Parameters.m_BiasEnabled)
     {
-        m_WeightDecoder->Reset(inputs[1]->Map());
-        if (m_Data.m_Parameters.m_BiasEnabled)
-        {
-            m_BiasDecoder->Reset(inputs[2]->Map());
-        }
+        m_BiasDecoder->Reset(inputs[2]->Map());
     }
 
     FullyConnected(m_InputShape,
-- 
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