openvino/docs/OV_Runtime_UG/model_representation.md

Model Representation in OpenVINO™ Runtime

In OpenVINO™ Runtime a model is represented by the ov::Model class.

The ov::Model object stores shared pointers to ov::op::v0::Parameter, ov::op::v0::Result and ov::op::Sink operations that are inputs, outputs and sinks of the graph. Sinks of the graph have no consumers and are not included in the results vector. All other operations hold each other via shared pointers: child operation holds its parent (hard link). If an operation has no consumers and it's not the Result or Sink operation (shared pointer counter is zero), then it will be destructed and won't be accessible anymore.

Each operation in ov::Model has the std::shared_ptr<ov::Node> type.

For details on how to build a model in OpenVINO™ Runtime, see the [Build a Model in OpenVINO™ Runtime](@ref ov_ug_build_model) section.

OpenVINO™ Runtime allows to use different approaches to work with model inputs/outputs:

• ov::Model::inputs()/ov::Model::outputs() methods allow to get vector of all input/output ports.
• For a model which has only one input or output you can use methods ov::Model::input() or ov::Model::output() without arguments to get input or output port respectively.
• Methods ov::Model::input() and ov::Model::output() can be used with index of input or output from the framework model to get specific port by index.
• You can use tensor name of input or output from the original framework model together with methods ov::Model::input() or ov::Model::output() to get specific port. It means that you don't need to have any additional mapping of names from framework to OpenVINO, as it was before, OpenVINO™ Runtime allows using of native framework tensor names.

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@snippet docs/snippets/ov_model_snippets.cpp all_inputs_ouputs

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@snippet docs/snippets/ov_model_snippets.py all_inputs_ouputs

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OpenVINO™ Runtime model representation uses special classes to work with model data types and shapes. For data types the ov::element::Type is used.

Shapes Representation

OpenVINO™ Runtime provides two types for shape representation:

• ov::Shape - Represents static (fully defined) shapes.

• ov::PartialShape - Represents dynamic shapes. That means that the rank or some of dimensions are dynamic (dimension defines an interval or undefined). ov::PartialShape can be converted to ov::Shape using the get_shape() method if all dimensions are static; otherwise the conversion raises an exception.

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@snippet docs/snippets/ov_model_snippets.cpp ov:partial_shape

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@snippet docs/snippets/ov_model_snippets.py ov:partial_shape

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But in most cases before getting static shape using get_shape() method, you need to check that shape is static.

Operations

The ov::Op class represents any abstract operation in the model representation. Use this class to create custom operations.

Operation Sets

Operation set (opset) is a collection of operations that can be used to construct a model. The ov::OpSet class provides a functionality to work with operation sets. For each operation set, OpenVINO™ Runtime provides a separate namespace, for example opset8. Each OpenVINO™ Release introduces new operations and add these operations to a new operation set. New operation sets help to introduce a new version of operations that change behavior of previous operations. Using operation sets allows you to avoid changes in your application if new operations have been introduced. For a complete list of operation sets supported in OpenVINO™ toolkit, see Available Operations Sets. To add support of custom operations, see the Add Custom OpenVINO Operations document.

Build a Model in OpenVINO™ Runtime

You can create a model from source. This section illustrates how to construct a model composed of operations from an available operation set.

Operation set opsetX integrates a list of pre-compiled operations that work for this purpose. In other words, opsetX defines a set of operations for building a graph.

To build an ov::Model instance from opset8 operations, include the following files:

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@snippet docs/snippets/ov_model_snippets.cpp ov:include

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@snippet docs/snippets/ov_model_snippets.py import

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The following code demonstrates how to create a simple model:

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@snippet docs/snippets/ov_model_snippets.cpp ov:create_simple_model

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@snippet docs/snippets/ov_model_snippets.py ov:create_simple_model

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The following code creates a model with several outputs:

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@snippet docs/snippets/ov_model_snippets.cpp ov:create_advanced_model

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@snippet docs/snippets/ov_model_snippets.py ov:create_advanced_model

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Model debug capabilities

OpenVINO™ provides several debug capabilities:

• To receive additional messages about applied model modifications, rebuild the OpenVINO™ Runtime library with the -DENABLE_OPENVINO_DEBUG=ON option.
• Model can be visualized to image from the xDot format:

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@snippet docs/snippets/ov_model_snippets.cpp ov:visualize

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@snippet docs/snippets/ov_model_snippets.py ov:visualize

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`ov::pass::VisualizeTree` can be parametrized via environment variables:

    OV_VISUALIZE_TREE_OUTPUT_SHAPES=1       - visualize shapes
    OV_VISUALIZE_TREE_OUTPUT_TYPES=1        - visualize types
    OV_VISUALIZE_TREE_MIN_MAX_DENORMAL=1    - pretty denormal values
    OV_VISUALIZE_TREE_RUNTIME_INFO=1        - print runtime information
    OV_VISUALIZE_TREE_IO=1                  - print I/O ports
    OV_VISUALIZE_TREE_MEMBERS_NAME=1        - print member names

• Also model can be serialized to IR:

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  @snippet docs/snippets/ov_model_snippets.cpp ov:serialize

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  @snippet docs/snippets/ov_model_snippets.py ov:serialize

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See Also

• Available Operation Sets
• OpenVINO™ Runtime Extensibility Developer Guide
• Transformations Developer Guide.