onnx_ir.tape

Taping module to facilitate building IR graphs.

The onnx_ir.tape module provides utilities for recording nodes and initializers to construct computational graphs or functions.

The Tape class

The Tape class is a recorder that collects nodes and initializers created during the construction of a graph or function. It supports creating nodes with single or multiple outputs and registering initializers.

class onnx_ir.tape.Tape(graph_like: Graph | Function | None = None)

Tape class.

A tape is a recorder that collects nodes and initializers that are created so that they can be used for creating a graph.

Example:

import onnx_ir as ir

tape = ir.tape.Tape()
a = tape.initializer(ir.tensor([1, 2, 3], name="a"))
b: ir.Value = ...
c: ir.Value = ...
x = tape.op("Add", [a, b], attributes={"alpha": 1.0})
y = tape.op("Mul", [x, c], attributes={"beta": 2.0})
model = ir.Model(
    graph := ir.Graph(
        inputs=[b, c],
        outputs=[y],
        nodes=tape.nodes,
        initializers=tape.initializers
        opset_imports={"": 20},
    ),
    ir_version=10,
)

graph_like

The graph to append the new nodes and initializers to. When it is None, the nodes and initializers are creating without owned by a graph. Initializers will not be added to functions because it is not supported by ONNX.

initializer(tensor: TensorProtocol, name: str | None = None) → Value

property initializers: Sequence[Value]

property nodes: Sequence[Node]

op(op_type: str, inputs: Sequence[Value | None], attributes: Mapping[str, str | int | float | Sequence[int] | Sequence[float] | Sequence[str] | TensorProtocol | TensorProto | Attr | GraphProtocol | Sequence[GraphProtocol] | GraphProto | TypeProtocol | Sequence[TypeProtocol] | None] | None = None, *, domain: str = '', overload: str = '', version: int | None = None, graph: Graph | None = None, name: str | None = None, doc_string: str | None = None, metadata_props: dict[str, str] | None = None, output: Value | None = None) → Value

op_multi_out(op_type: str, inputs: Sequence[Value | None], attributes: Mapping[str, str | int | float | Sequence[int] | Sequence[float] | Sequence[str] | TensorProtocol | TensorProto | Attr | GraphProtocol | Sequence[GraphProtocol] | GraphProto | TypeProtocol | Sequence[TypeProtocol] | None] | None = None, *, num_outputs: int | None = None, outputs: Sequence[Value] | None = None, domain: str = '', overload: str = '', version: int | None = None, graph: Graph | None = None, name: str | None = None, doc_string: str | None = None, metadata_props: dict[str, str] | None = None) → Sequence[Value]

property used_opsets: set[tuple[str, int | None]]