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author | Matthew Sloyan <matthew.sloyan@arm.com> | 2022-12-14 10:16:27 +0000 |
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committer | TeresaARM <teresa.charlinreyes@arm.com> | 2022-12-15 12:21:16 +0000 |
commit | da6bf9e2eac374cd92147d3c60a8af8bd6bc5a37 (patch) | |
tree | 9999b8d92c2b14b4bb349cbfd250dc33af252fb7 /src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp | |
parent | fc9d5e7d1e0c1a4d7fed4ebc363832e03c3e2543 (diff) | |
download | armnn-da6bf9e2eac374cd92147d3c60a8af8bd6bc5a37.tar.gz |
IVGCVSW-7168 Support simple model in the TOSA Reference Backend
* Fixed issue where duplicate tensors where being created.
* Fixed issue where output name could be generated with the wrong id.
* Updated bias tensor for Conv2d, so the size matches the channel.
Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: I1de6947e036b3e629ec6446d24d69e50603a5593
Diffstat (limited to 'src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp')
-rw-r--r-- | src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp | 22 |
1 files changed, 15 insertions, 7 deletions
diff --git a/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp b/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp index 265901e1ae..ee02425c17 100644 --- a/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp +++ b/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp @@ -26,8 +26,7 @@ TosaSerializationBasicBlock* ConvertPooling2DToTosaOperator(const Layer* layer, input0Name = GenerateUniqueName(connectedInputLayer, 0); // Get the layer connected to the output slot and determine unique layer name. - Layer& connectedOutputLayer = layer->GetOutputSlot().GetConnection(0)->GetOwningLayer(); - outputName = GenerateUniqueName(connectedOutputLayer, 0); + outputName = GenerateUniqueOutputName(*layer, 0); } std::vector<int> pad = {static_cast<int>(poolDescriptor->m_PadTop), @@ -46,20 +45,29 @@ TosaSerializationBasicBlock* ConvertPooling2DToTosaOperator(const Layer* layer, {input0Name}, {outputName}); - std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape()); - DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType()); + std::vector<TosaSerializationTensor*> tensors; + + // Only add input tensors if connected layer is an input layer. + // As intermediate or constant tensors will be created separately. + // There also can't be duplicate tensor. + if(input0Name.find("input0_") != std::string::npos) + { + std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape()); + DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType()); + + tensors.push_back(new TosaSerializationTensor(input0Name, inputShape0, inputDType0, {})); + } std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape()); DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType()); - auto* inputTensor0 = new TosaSerializationTensor(input0Name, inputShape0, inputDType0, {}); - auto* outputTensor0 = new TosaSerializationTensor(outputName, outputShape0, outputDType0, {}); + tensors.push_back(new TosaSerializationTensor(outputName, outputShape0, outputDType0, {})); // operatorInputNames/operatorOutputNames ends up being the same as // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings return new TosaSerializationBasicBlock(blockName, // name {op}, // operators - {inputTensor0, outputTensor0}, // tensors + tensors, // tensors {input0Name}, // inputs {outputName}); // outputs }
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