code: def quantile(
      a: np.ndarray,
      q: Union[float, np.ndarray],
      /,
      *,
      axis: Optional[Union[int, Sequence[int]]] = None,
      keepdims: bool = False,
      interpolation: str = "linear",
      out: Optional[np.ndarray] = None,
  ) -> np.ndarray:
      # quantile method in numpy backend, always return an array with dtype=float64.
      # in other backends, the output is the same dtype as the input.
      # added the nearest_jax mode to enable jax-like calculations for method="nearest"
      return _compute_quantile_wrapper(
          a,
          q,
          axis=axis,
          keepdims=keepdims,
          interpolation=interpolation,
          out=out,
      )
  
imports: from typing import Optional, Union, Tuple, Sequence
  import numpy
  import math
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
  from ..statistical import _infer_dtype
  from copy import deepcopy
label_desc: Use image node_id 11 for calling a global function with example usage: quantile() and returns: _compute_quantile_wrapper