onnx-ir

import onnx_ir as ir import numpy as np # Create input values with specific types and shapes input_a = ir.Value("input_a", ir.Type(ir.Shape([2, 2]), ir.TensorElementDataType.FLOAT)) input_b = ir.Value("input_b", ir.Type(ir.Shape([2, 2]), ir.TensorElementDataType.FLOAT)) # Define the output value for the Add node output_c = ir.Value("output_c") # Create an 'Add' node with inputs and outputs add_node = ir.Node("Add", inputs=[input_a, input_b], outputs=[output_c]) # Assemble a graph from inputs, outputs, and nodes graph = ir.Graph( [input_a, input_b], # Graph inputs [output_c], # Graph outputs [add_node], # Nodes in the graph "simple_add_graph" # Name of the graph ) print(f"Created graph: {graph.name}") print(f"Graph has {len(graph.nodes)} node(s).") print(f"Input 'input_a' shape: {input_a.type.shape.dims}")