code: def _up_and_broadcast(doit):
      def up_and_broadcast(*args):
          broadcasted_shape = broadcast_shapes(*(a.shape for a in args))
          args = [
              broadcast_in_dim(
                  a, broadcasted_shape, list(range(a.ndim))
              )
              for a in args
          ]
  
          a_dtype = args[0].dtype
          needs_upcast = (
              a_dtype == dtypes.bfloat16 or a_dtype == np.float16
          )
          if needs_upcast:
              args = [convert_element_type(a, np.float32) for a in args]
              a_x_type = np.float32
          else:
              a_x_type = a_dtype
          result = doit(*args, dtype=a_x_type)
          if needs_upcast:
              result = convert_element_type(result, a_dtype)
          return result
  
      return up_and_broadcast
  
imports: from enum import Enum
  import numpy
  from functools import partial
  from jax._src.lax.lax import add, bitwise_and, bitwise_not, bitwise_or, broadcast_in_dim, broadcast_shapes, convert_element_type, div, eq, exp, full_like, ge, gt, le, log, log1p, lt, mul, ne, neg, reciprocal, reduce, select, sign, sqrt, square, standard_naryop, standard_unop, sub, _const, _dtype, _float, _nary_lower_hlo, _ones, _isnan, _reduce
  from jax._src.lax.control_flow import while_loop
  from jax._src import dtypes
  from jax._src.interpreters import ad
  from jax._src.interpreters import mlir
  from jax._src.lib.mlir.dialects import chlo
  from jax._src.typing import Array, ArrayLike
label_desc: Use image node_id 32 for calling a global function with example usage: _up_and_broadcast(doit) and returns: up_and_broadcast, result