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
diff --git a/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp b/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
index 9c095d6..dadd91b 100644
--- a/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
@@ -39,19 +39,23 @@
}
// Get the layer connected to the output slot and determine unique layer name.
- Layer& connectedLayer = layer->GetOutputSlot().GetConnection(0)->GetOwningLayer();
-
- outputName = GenerateUniqueName(connectedLayer, 0);
+ outputName = GenerateUniqueOutputName(*layer, 0);
}
std::vector<TosaSerializationTensor*> tensors;
std::vector<TosaSerializationOperator*> operators;
// Setup input Tensor
- std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape());
- DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType());
+ // Only add tensor if connected layer is an input layer.
+ // As intermediate or constant tensors will be created separately.
+ // There also can't be duplicate tensors.
+ if(inputNames[0].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(inputNames[0], inputShape0, inputDType0, {}));
+ tensors.push_back(new TosaSerializationTensor(inputNames[0], inputShape0, inputDType0, {}));
+ }
// Only add input tensors if weights and bias are not constant or if running validation.
// Constant tensors will be created in the ConvertConstantToTosaOperator function.
@@ -80,12 +84,18 @@
operators.push_back(new TosaSerializationOperator(Op_CONST, Attribute_NONE, nullptr, {}, {constantName}));
+ // The size of the bias must match the channels dimension, so get the correct index.
+ unsigned int index = (conv2dDescriptor->m_DataLayout == DataLayout::NHWC) ? 3 : 1;
+
std::vector<uint8_t> uint8Data;
- std::vector<float> data = { 0.0 };
+ std::vector<float> data(outputs[0]->GetShape()[index], 0.0f);
TosaSerializationHandler::ConvertF32toU8(data, uint8Data);
- tensors.push_back(new TosaSerializationTensor(constantName, {1}, DType_FP32, uint8Data));
+ tensors.push_back(new TosaSerializationTensor(constantName,
+ {static_cast<int32_t>(outputs[0]->GetShape()[index])},
+ DType_FP32,
+ uint8Data));
inputNames.emplace_back(constantName);
}