Method ParseLogSoftmax

src/armnnTfLiteParser/TfLiteParser.cpp:2298–2323

}

void TfLiteParserImpl::ParseLogSoftmax(size_t subgraphIndex, size_t operatorIndex)
{
    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);

    LogSoftmaxDescriptor desc;

    auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
    CHECK_VALID_SIZE(inputs.size(), 1);
    auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
    CHECK_VALID_SIZE(outputs.size(), 1);

    auto layerName = fmt::format("LogSoftmax:{}:{}", subgraphIndex, operatorIndex);
    IConnectableLayer* const layer = m_Network->AddLogSoftmaxLayer(desc, layerName.c_str());

    armnn::TensorInfo outputTensorInfo = OutputTensorInfoFromInputs(subgraphIndex, operatorIndex, layer, 0, {0});
    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);

    // register the input connection slots for the layer, connections are made after all layers have been created
    // only the tensors for the inputs are relevant, exclude the const tensors
    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});

    // register the output connection slots for the layer, connections are made after all layers have been created
    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
}

void TfLiteParserImpl::ParseScatterNd(size_t subgraphIndex, size_t operatorIndex)
{