code: def nanmin(
      x: JaxArray,
      /,
      *,
      axis: Optional[Union[int, Tuple[int]]] = None,
      keepdims: Optional[bool] = False,
      initial: Optional[Union[int, float, complex]] = None,
      where: Optional[JaxArray] = None,
      out: Optional[JaxArray] = None,
  ) -> JaxArray:
      if isinstance(axis, list):
          axis = tuple(axis)
      return jnp.nanmin(
          x,
          axis=axis,
          keepdims=keepdims,
          initial=initial,
          where=where,
          out=out,
      )
  
imports: import jax.numpy
  from typing import Optional, Union, Tuple, Sequence
  from ivy.functional.backends.jax import JaxArray
  import jax.lax
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
  from ..statistical import _infer_dtype
label_desc: Use image node_id 4 for calling a global function with example usage: nanmin() and returns: jnp