code: def randint(
      low, high=None, size=None, dtype=None, ctx=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'.
      ctx : Context, optional
          Device context of output. Default is current context.
      out : _Symbol, optional
          The output symbol (default is `None`).
  
      Returns
      -------
      out : _Symbol
          `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]])
      """
      if dtype is None:
          dtype = "int"
      if ctx is None:
          ctx = current_context()
      if size is None:
          size = ()
      if high is None:
          high = low
          low = 0
      return _npi.random_randint(
          low, high, shape=size, dtype=dtype, ctx=ctx, out=out
      )
  
imports: import numpy
  from ...context import current_context
  from ...util import is_np_default_dtype
  from .None import _internal
label_desc: Use image node_id 1 for calling a global function with example usage: randint(low, high, size, dtype, ctx, out) and returns: _npi