code: def rand_like(rng, x):
      shape = np.shape(x)
      dtype = _dtype(x)
      randn = lambda: np.asarray(rng.randn(*shape), dtype=dtype)
      if _dtypes.issubdtype(dtype, np.complexfloating):
          result = randn() + dtype.type(1.0j) * randn()
      else:
          result = randn()
      return result.item() if is_python_scalar(x) else result
  
imports: from functools import partial
  import operator
  from jax._src import api
  from jax._src import config
  from jax._src import dtypes
  from jax._src.tree_util import tree_map, tree_reduce
  import numpy
label_desc: Use image node_id 13 for calling a global function with example usage: rand_like(rng, x) and returns: unknown