This section illustrates how to construct an nGraph function composed of operations from the opset3
namespace. Once created, it can wrap into a CNNNetwork
, creating utility for data scientists or app developers to define a deep-learning model in a neutral way that does not depend on existing Deep Learning (DL) frameworks.
Operation Set opsetX
integrates a list of nGraph pre-compiled operations that work for this purpose. In other words, opsetX
defines a set of operations for building a graph.
For a complete list of operation sets supported by Inference Engine, see Available Operations Sets.
To add custom nGraph operations to an existing CNNNetwork
, see the Add Custom nGraph Operations document.
Now that you can build graphs with anything from the opset3
definition, some parameters for shape-relevant (or shape-specific) inputs can be added. The following code prepares a graph for shape-relevant parameters.
NOTE:
validate_nodes_and_infer_types(ops)
must be included for partial shape inference.
To wrap it into a CNNNetwork, use: