code: def interpret_onnx(graph, *args):
      vals = dict(
          {n.name: a for n, a in zip(graph.input, args)},
          **{n.name: _asarray(n) for n in graph.initializer},
      )
      for node in graph.node:
          args = (vals[name] for name in node.input)
          attrs = {
              a.name: attribute_handlers[a.type](a)
              for a in node.attribute
          }
          outputs = onnx_ops[node.op_type](*args, **attrs)
          for name, output in zip(node.output, outputs):
              vals[name] = output
      return [vals[n.name] for n in graph.output]
  
file_path: jax/examples/onnx2xla.py
imports: from io import BytesIO
  import hashlib
  import urllib.request
  import sys
  import numpy
  import onnx
  from onnx import numpy_helper
  import jax.numpy
  from jax import jit, grad
  from jax import lax
label_desc: Use image node_id 5 for calling a global function with example usage: interpret_onnx(graph) and returns: unknown