code: def get_mean_std(draw, *, dtype):
      """Draws two integers representing the mean and standard deviation for a
      given data type.
  
      Parameters
      ----------
      draw
          special function that draws data randomly (but is reproducible) from a given
          data-set (ex. list).
      dtype
          data type.
  
      Returns
      -------
      A strategy that can be used in the @given hypothesis decorator.
      """
      none_or_float = none_or_float = (
          number_helpers.floats(dtype=dtype) | st.none()
      )
      values = draw(array_helpers.list_of_size(x=none_or_float, size=2))
      values[1] = abs(values[1]) if values[1] else None
      return values[0], values[1]
  
imports: from hypothesis import assume, strategies
  from typing import Tuple
  from functools import lru_cache
  import math
  import numpy
  import ivy
  from .None import array_helpers, number_helpers, dtype_helpers
  from ..pipeline_helper import WithBackendContext
  from ivy.functional.ivy.layers import _deconv_length
  from ..globals import mod_backend
label_desc: Use image node_id 10 for calling a global function with example usage: get_mean_std(draw) and returns: values,  values