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authorKevin May <kevin.may@arm.com>2022-12-15 10:15:21 +0000
committerTeresa Charlin <teresa.charlinreyes@arm.com>2022-12-15 17:16:12 +0000
commit5b58e31109f661f70331048e22f8a66934e74d15 (patch)
tree7ad8f88bf7427a1dd2622b53fcd0b4b8632ee34e /src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
parent3fbad94012ee6b1c6ec8e93d760619b15d98c464 (diff)
downloadarmnn-5b58e31109f661f70331048e22f8a66934e74d15.tar.gz
IVGCVSW-7170 Add Concat support to TOSA Reference Backend
* Change comment for the unique tensor names in all tosa common operators Signed-off-by: Kevin May <kevin.may@arm.com> Change-Id: I247b4b2365d5f0173218c5dfd11fba12d2399959
Diffstat (limited to 'src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp')
-rw-r--r--src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp10
1 files changed, 5 insertions, 5 deletions
diff --git a/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp b/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
index 6fc1678c81..a7af08347a 100644
--- a/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
@@ -24,21 +24,21 @@ TosaSerializationBasicBlock* ConvertConv2dToTosaOperator(const Layer* layer,
inputNames.emplace_back("input2_");
}
}
+ // If a layer is present then the block will be used for execution, so input and output names need to be
+ // determined using the previous and following layers so the graph is connected correctly.
+ // For validation this doesn't matter.
else
{
- // If a layer is present then the block will be used for execution, so input and output names need to be
- // determined using the previous and following layers so the graph is connected correctly.
- // For validation this doesn't matter.
+ // Get the layer connected to the input slot and determine unique tensor names.
for (uint32_t i = 0; i < inputs.size(); ++i)
{
- // Get the layer connected to the input slot and determine unique layer name.
Layer& connectedLayer = layer->GetInputSlot(i).GetConnectedOutputSlot()->GetOwningLayer();
std::string inputName = GenerateUniqueName(connectedLayer, i);
inputNames.push_back(inputName);
}
- // Get the layer connected to the output slot and determine unique layer name.
+ // Determine unique output tensor name.
outputName = GenerateUniqueOutputName(*layer, 0);
}