code: def cummin(
      x: np.ndarray,
      /,
      *,
      axis: int = 0,
      exclusive: bool = False,
      reverse: bool = False,
      dtype: Optional[np.dtype] = None,
      out: Optional[np.ndarray] = None,
  ) -> np.ndarray:
      if dtype is None:
          dtype = _infer_dtype(x.dtype)
      if not (reverse):
          return np.minimum.accumulate(x, axis, dtype=dtype, out=out)
      elif reverse:
          x = np.minimum.accumulate(
              np.flip(x, axis=axis), axis=axis, dtype=dtype
          )
          return np.flip(x, axis=axis)
  
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 19 for calling a global function with example usage: cummin() and returns: np, np