code: def sparse_array_mlir_type_handler(a):
      return (
          ir.RankedTensorType.get(
              a.data_aval.shape,
              mlir.dtype_to_ir_type(a.data_aval.dtype),
          ),
          ir.RankedTensorType.get(
              a.indices_aval.shape,
              mlir.dtype_to_ir_type(a.indices_aval.dtype),
          ),
      )
  
imports: from absl.testing import absltest
  import math
  import unittest
  import numpy
  import jax.numpy
  from jax import jit, lax, make_jaxpr
  from jax import config
  from jax.interpreters import mlir
  from jax.interpreters import xla
  from jax._src import core
  from jax._src import dtypes
  from jax._src import test_util
  from jax._src import xla_bridge
  from jax._src.lib.mlir import ir
  from jax._src.lib import xla_client
label_desc: Use image node_id 2 for calling a global function with example usage: sparse_array_mlir_type_handler(a) and returns: ir,  ir