From 8bd536064f32b1ce521875e2bc8dd24044c4f5c3 Mon Sep 17 00:00:00 2001
From: Cathal Corbett <cathal.corbett@arm.com>
Date: Thu, 12 May 2022 15:54:58 +0100
Subject: IVGCVSW-6126 ConstTensorsAsInput: Conv2d - Backends

!android-nn-driver:7477

Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: Ibf633ccccc385bd980934ff829407d21981323ef
---
 src/armnn/Network.cpp                              |  3 +++
 .../test/optimizations/FuseActivationTests.cpp     | 31 ++++++++++++----------
 2 files changed, 20 insertions(+), 14 deletions(-)

(limited to 'src/armnn')

diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp
index 479e57fc56..77ad5c4dc2 100644
--- a/src/armnn/Network.cpp
+++ b/src/armnn/Network.cpp
@@ -1832,6 +1832,9 @@ IOptimizedNetworkPtr Optimize(const Graph& inGraph,
         ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "Optimizer_ConvertConstants");
         Optimizer::Pass(optGraph, MakeOptimizations(ConvertConstantsFloatToHalf()));
         Optimizer::Pass(optGraph, MakeOptimizations(ConvertConstantsHalfToFloat()));
+
+        // Once the constants are converted we can now safely call RedirectMembersToConstantInputs
+        Optimizer::Pass(optGraph, MakeOptimizations(RedirectMembersToConstantInputs()));
     }
     return optNet;
 }
diff --git a/src/armnn/test/optimizations/FuseActivationTests.cpp b/src/armnn/test/optimizations/FuseActivationTests.cpp
index 0cca86f93b..3b8917192d 100644
--- a/src/armnn/test/optimizations/FuseActivationTests.cpp
+++ b/src/armnn/test/optimizations/FuseActivationTests.cpp
@@ -56,32 +56,35 @@ struct Convolution2dTest
                                                float scale = 1.f,
                                                int32_t offset = 0)
     {
+        IgnoreUnused(scale);
+        IgnoreUnused(offset);
+
         Convolution2dDescriptor descriptor;
         descriptor.m_DataLayout  = DataLayout::NHWC;
         descriptor.m_StrideX     = 1;
         descriptor.m_StrideY     = 1;
 
+        return network->AddConvolution2dLayer(descriptor, name);
+    }
+
+    static std::vector<IConnectableLayer*> AddConstantLayers(INetwork* network,
+                                                             float scale = 1.f,
+                                                             int32_t offset = 0)
+    {
+
         std::vector<float> weightsData   = {  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,
                                              11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22,
                                              21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
-                                             31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42};
+                                             31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42 };
         std::vector<T>     weightsVector = armnnUtils::QuantizedVector<T>(weightsData, scale, offset);
         TensorInfo         weightsInfo(GetWeightsShape(), ArmnnType, scale, offset, true);
         ConstTensor        weights(weightsInfo, weightsVector);
-        Optional<ConstTensor> optionalBias;
-        ARMNN_NO_DEPRECATE_WARN_BEGIN
-        return network->AddConvolution2dLayer(descriptor, weights, optionalBias, name);
-        ARMNN_NO_DEPRECATE_WARN_END
-    }
 
-    static std::vector<IConnectableLayer*> AddConstantLayers(INetwork* network,
-                                                             float scale = 1.f,
-                                                             int32_t offset = 0)
-    {
-        IgnoreUnused(network);
-        IgnoreUnused(scale);
-        IgnoreUnused(offset);
-        return {};
+        IConnectableLayer* weightsLayer = network->AddConstantLayer(weights, "Weights");
+        weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
+
+        std::vector<IConnectableLayer*> layers = { weightsLayer };
+        return layers;
     }
 };
 
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