code: def quantile(
      a: torch.Tensor,
      q: Union[torch.Tensor, float],
      /,
      *,
      axis: Optional[Union[Sequence[int], int]] = None,
      keepdims: bool = False,
      interpolation: str = "linear",
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      # 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 torch
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  import ivy
  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