Node

class onnx_ir.Node(domain: str, op_type: str, inputs: Iterable[Value | None], attributes: Iterable[Attr] = (), *, overload: str = '', num_outputs: int | None = None, outputs: Sequence[Value] | None = None, version: int | None = None, graph: Graph | Function | None = None, name: str | None = None, doc_string: str | None = None, metadata_props: dict[str, str] | None = None)

IR Node.

If the graph is provided, the node will be added to the graph. Otherwise, user is responsible to call graph.append(node) (or other mutation methods in Graph) to add the node to the graph.

After the node is initialized, it will add itself as a user of the input values.

The output values of the node are created during node initialization and are immutable. To change the output values, create a new node and replace the each of the inputs of output.uses() with the new output values by calling replace_input_with() on the using nodes of this node’s outputs.

doc_string

append(nodes: Node | Iterable[Node]) → None

Insert a node after this node in the list of nodes in the graph.

It is the same as calling graph.insert_after(self, nodes).

Example:

Before: previous_node -> self
        previous_node' -> node -> next_node'
After:  previous_node -> self -> node
        previous_node' -> next_node'

Parameters:

nodes – A node or a sequence of nodes to put after this node.

property attributes: OrderedDict[str, Attr]

The attributes of the node.

display(*, page: bool = False) → None

Pretty print the node.

This method is used for debugging and visualization purposes.

property domain: str

The domain of the operator. For onnx operators, this is an empty string.

property graph: Graph | None

The graph that the node belongs to.

If the node is not added to any graph, this property is None.

property inputs: Sequence[Value | None]

The input values of the node.

The inputs are immutable. To change the inputs, create a new node and replace the inputs of the using nodes of this node’s outputs by calling replace_input_with() on the using nodes of this node’s outputs.

property meta: MetadataStore

The metadata store for intermediate analysis.

Write to the metadata_props if you would like the metadata to be serialized to the ONNX proto.

property metadata_props: dict[str, str]

The metadata properties of the node.

The metadata properties are used to store additional information about the node. Unlike meta, this property is serialized to the ONNX proto.

property name: str | None

Optional name of the node.

op_identifier() → tuple[str, str, str]

Return the operator identifier of the node.

The operator identifier is a tuple of the domain, op_type and overload.

property op_type: str

The name of the operator called.

property outputs: Sequence[Value]

The output values of the node.

The outputs are immutable. To change the outputs, create a new node and replace the inputs of the using nodes of this node’s outputs by calling replace_input_with() on the using nodes of this node’s outputs.

property overload: str

The overload name when the node is invoking a function.

predecessors() → Sequence[Node]

Return the predecessor nodes of the node, deduplicated, in a deterministic order.

prepend(nodes: Node | Iterable[Node]) → None

Insert a node before this node in the list of nodes in the graph.

It is the same as calling graph.insert_before(self, nodes).

Example:

Before: previous_node -> self
        previous_node' -> node -> next_node'
After:  previous_node -> node -> self
        previous_node' -> next_node'

Parameters:

nodes – A node or a sequence of nodes to put before this node.

replace_input_with(index: int, value: Value | None) → None

Replace an input with a new value.

successors() → Sequence[Node]

Return the successor nodes of the node, deduplicated, in a deterministic order.

property version: int | None

Opset version of the operator called.

If None, the version is unspecified and will follow that of the graph. This property is special to ONNX IR to allow mixed opset usage in a graph for supporting more flexible graph transformations. It does not exist in the ONNX serialization (protobuf) spec.