diff options
Diffstat (limited to 'src/armnn/optimizations/FuseBatchNorm.hpp')
| -rw-r--r-- | src/armnn/optimizations/FuseBatchNorm.hpp | 8 |
1 files changed, 3 insertions, 5 deletions
diff --git a/src/armnn/optimizations/FuseBatchNorm.hpp b/src/armnn/optimizations/FuseBatchNorm.hpp index bca0c7d00a..88ac97cd0c 100644 --- a/src/armnn/optimizations/FuseBatchNorm.hpp +++ b/src/armnn/optimizations/FuseBatchNorm.hpp @@ -1,5 +1,5 @@ // -// Copyright © 2020 Arm Ltd and Contributors. All rights reserved. +// Copyright © 2020,2022 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // @@ -167,8 +167,6 @@ public: auto& newConv2dLayer = *graph.InsertNewLayer<ConvLayer>(base.GetInputSlot(0), convDescriptor, name.c_str()); - newConv2dLayer.m_Weight = std::make_unique<ScopedTensorHandle>(fusedWeightsTensor); - newConv2dLayer.m_Bias = std::make_unique<ScopedTensorHandle>(ConstTensor(fusedBiasTensor)); // Connect weights and bias from old to new Conv2d layer // This optimization will always have 3 input slots on the Conv2d base layer @@ -177,7 +175,7 @@ public: // Remove old connection and connect to new layer2d weightLayer->GetOutputSlot(0).Disconnect(base.GetInputSlot(1)); weightLayer->GetOutputSlot(0).Connect(newConv2dLayer.GetInputSlot(1)); - weightLayer->m_LayerOutput = newConv2dLayer.m_Weight; + weightLayer->m_LayerOutput = std::make_unique<ScopedTensorHandle>(fusedWeightsTensor); // Move bias const layers as normal if it was enabled before the optimisation ConstantLayer* biasLayer; @@ -198,7 +196,7 @@ public: biasLayer->GetOutputSlot(0).SetTensorInfo(fusedBiasTensor.GetInfo()); biasLayer->GetOutputSlot(0).Connect(newConv2dLayer.GetInputSlot(2)); } - biasLayer->m_LayerOutput = newConv2dLayer.m_Bias; + biasLayer->m_LayerOutput = std::make_unique<ScopedTensorHandle>(ConstTensor(fusedBiasTensor)); } |