code: def nanmin(
      a: np.ndarray,
      /,
      *,
      axis: Optional[Union[int, Tuple[int]]] = None,
      keepdims: Optional[bool] = False,
      initial: Optional[Union[int, float, complex]] = None,
      where: Optional[np.ndarray] = True,
      out: Optional[np.ndarray] = None,
  ) -> np.ndarray:
      axis = tuple(axis) if isinstance(axis, list) else axis
      if where is None:
          where = True
      return np.nanmin(
          a=a,
          axis=axis,
          keepdims=keepdims,
          out=out,
          initial=initial,
          where=where,
      )
  
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 4 for calling a global function with example usage: nanmin() and returns: np