code: def randint(
      low, high=None, size=None, dtype=None, device=None, out=None
  ):
      r"""Return random integers from `low` (inclusive) to `high` (exclusive).
  
      Return random integers from the "discrete uniform" distribution of
      the specified dtype in the "half-open" interval [`low`, `high`). If
      `high` is None (the default), then results are from [0, `low`).
  
      Parameters
      ----------
      low : int
          Lowest (signed) integer to be drawn from the distribution (unless
          ``high=None``, in which case this parameter is one above the
          *highest* such integer).
      high : int, optional
          If provided, one above the largest (signed) integer to be drawn
          from the distribution (see above for behavior if ``high=None``).
      size : int or tuple of ints, optional
          Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
          ``m * n * k`` samples are drawn.  Default is None, in which case a
          single value is returned.
      dtype : dtype, optional
          Desired dtype of the result. All dtypes are determined by their
          name, i.e., 'int64', 'int', etc, so byteorder is not available
          and a specific precision may have different C types depending
          on the platform. The default value is 'np.int'.
      device : Device, optional
          Device context of output. Default is current device.
      out : ndarray, optional
          The output ndarray (default is `None`).
  
      Returns
      -------
      out : ndarray of ints
          `size`-shaped array of random integers from the appropriate
          distribution, or a single such random int if `size` not provided.
  
      Examples
      --------
      >>> np.random.randint(2, size=10)
      array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0])
      >>> np.random.randint(1, size=10)
      array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
  
      Generate a 2 x 4 array of ints between 0 and 4, inclusive:
  
      >>> np.random.randint(5, size=(2, 4))
      array([[4, 0, 2, 1],
          [3, 2, 2, 0]])
      """
      return _mx_nd_np.random.randint(
          low, high, size, dtype, device, out
      )
  
imports: from ..ndarray import numpy
  from ..random import seed
  from ..util import wrap_ctx_to_device_func
label_desc: Use image node_id 1 for calling a global function with example usage: randint(low, high, size, dtype, device, out) and returns: _mx_nd_np