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Add Custom nGraph Operations
Inference Engine Extension API allows to register operation sets (opsets) with custom nGraph operations, it allows to support Networks with unknown operations.
Operation Class
To add your custom nGraph operation, create a new class that extends ngraph::Op, which is in turn derived from ngraph::Node, the base class for all graph operations in nGraph. Follow the steps below:
-
Define a
NodeTypeInfoobject that identifies the type of the operation to the graph users and helps with dynamic type resolution. The type info of an nGraph operation currently consists of a string identifier and a version number, but this may change in the future. -
Implement constructors that can optionally take the operation inputs and attributes as parameters.
-
Override the shape inference method
validate_and_infer_types. This method is called multiple times during graph manipulations to determine the shapes and element types of the outputs of the operations. You can access the input shapes through theget_input_partial_shape()method and input element types through theget_input_element_type()method ofngraph::Node. Set the inferred shape and element type of the output usingset_output_type. -
Override the
clone_with_new_inputsmethod, which allows graph manipulation routines to create copies of this operation and connect it to different nodes during optimization. -
Override the
visit_attributesmethod, which allows serialization and deserialization of attributes. AnAttributeVisitoris passed to the method, and the implementation is expected to walk over all the attributes in the op using the type-awareon_attributehelper. Helpers are already implemented for standard C++ types likeint64_t,float,bool,vectorand for existing nGraph defined types. -
Override
evaluate, which is an optional method that enables the application of constant folding if there is a custom operation on the constant branch.
Based on that, declaration of a operation class can look as follows:
@snippet template_extension/op.hpp op:header
Class Fields
The provided implementation has several fields:
addof typeint64_tis an attribute of custom operationtype_infoof typengraph::NodeTypeInfodefines the type and version of operation
Operation Constructors
nGraph operation contains two constructors: a default constructor, which allows to create operation without attributes and a constructor that creates and validates operation with specified inputs and attributes.
@snippet template_extension/op.cpp op:ctor
validate_and_infer_types()
ngraph::Node::validate_and_infer_types method validates operation attributes and calculates output shapes using attributes of operation.
@snippet template_extension/op.cpp op:validate
clone_with_new_inputs()
ngraph::Node::clone_with_new_inputs method creates a copy of nGraph operation with new inputs.
@snippet template_extension/op.cpp op:copy
visit_attributes()
ngraph::Node::visit_attributes method allows to visit all operation attributes.
@snippet template_extension/op.cpp op:visit_attributes
evaluate()
ngraph::Node::evaluate method allows to apply constant folding to an operation.
@snippet template_extension/op.cpp op:evaluate
Register Custom Operations in Extension Class
To add custom operations to the Extension class, create an operation set with custom operations and implement the InferenceEngine::IExtension::getOpSets method:
@snippet template_extension/extension.cpp extension:getOpSets
This method returns a map of opsets that exist in the extension library.
nGraph provides opsets mechanism for operation versioning. Different opsets distinguish between different versions of one operation.
When specifying opset names, follow the rules below:
- Use unique opset names.
- Do not use the following built-in opset names:
extension,experimental,opset1,opest2. - Make sure that the Model Optimizer and your extension use the same opset names.
- IR v10 layers have the mandatory
versionattribute specifying the opset. opset1is the name of default operations set. Operations from the default opset cannot be redefined.
Use a custom opset to create a new operation or extend functionality of an existing operation from another opset.