Deploying a TensorFlow MNIST model using the Arm NN SDK

Import graph

Arm NN provides parsers for reading model files from neural network frameworks. There are typically two steps to do this:

1. Load the model.
2. Bind the input and output points of its graph.

 The following sample code imports the graph:

// Import the TensorFlow model. Note: use CreateNetworkFromBinaryFile for .pb files.
armnnTfParser::ITfParserPtr parser = armnnTfParser::ITfParser::Create();
armnn::TensorInfo inputTensorInfo({1, 784, 1, 1}, armnn::DataType::Float32);
armnn::INetworkPtr network = parser->CreateNetworkFromTextFile("model/simple_mnist_tf.prototxt",
                                                                   { {"Placeholder", {1, 784, 1, 1}} },
                                                                   { "Softmax" });

TensorFlow graphs in both text and binary ProtoBuf formats are supported. For more details on freezing TensorFlow graphs to include their weights, see the Customization basics: tensors and operations guide in the Related information section.

Note: After this step, the code is common regardless of the framework that you started with. This is because the INetwork and two BindingPointInfo objects provide everything that is needed.