code: def _float_power_helper(draw, *, available_dtypes=None):
      if available_dtypes is None:
          available_dtypes = helpers.get_dtypes("numeric")
      dtype1, x1 = draw(
          helpers.dtype_and_values(
              available_dtypes=available_dtypes,
              small_abs_safety_factor=16,
              large_abs_safety_factor=16,
              safety_factor_scale="log",
          )
      )
      dtype2 = draw(helpers.get_dtypes("numeric"))
      if ivy.is_int_dtype(dtype2[0]):
          min_value = 0
      else:
          min_value = -10
      dtype2, x2 = draw(
          helpers.dtype_and_values(
              min_value=min_value,
              max_value=10,
              dtype=dtype2,
          )
      )
      return (dtype1[0], dtype2[0]), (x1[0], x2[0])
  
imports: from hypothesis import strategies
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test
label_desc: Use image node_id 1 for calling a global function with example usage: _float_power_helper(draw) and returns: dtype1,  dtype2,  x1,  x2