def arange(start, stop=None, step=1.0, repeat=1, infer_range=None, ctx=None, dtype=mx_real_t):
    """Returns evenly spaced values within a given interval.

    Values are generated within the half-open interval [`start`, `stop`). In other
    words, the interval includes `start` but excludes `stop`. The function is
    similar to the built-in Python function `range` and to `numpy.arange`,
    but returns an `NDArray`.

    Parameters
    ----------
    start : number, optional
        Start of interval. The default start value is 0.
    stop : number
        End of interval.
    step : number, optional
        Spacing between values. The default step size is 1.
    repeat : int, optional
        Number of times to repeat each element. The default repeat count is 1.
    infer_range : boolean, optional
        When set to True, infer the stop position from the start, step,
        repeat, and output tensor size.
    ctx : Context, optional
        Device context. Default context is the current default context.
    dtype : str or numpy.dtype, optional
        The data type of the `NDArray`. The default datatype is `np.float32`.

    Returns
    -------
    NDArray
        `NDArray` of evenly spaced values in the specified range.

    Examples
    --------
    >>> mx.nd.arange(3).asnumpy()
    array([ 0.,  1.,  2.], dtype=float32)
    >>> mx.nd.arange(2, 6).asnumpy()
    array([ 2.,  3.,  4.,  5.], dtype=float32)
    >>> mx.nd.arange(2, 6, step=2).asnumpy()
    array([ 2.,  4.], dtype=float32)
    >>> mx.nd.arange(2, 6, step=1.5, repeat=2).asnumpy()
    array([ 2. ,  2. ,  3.5,  3.5,  5. ,  5. ], dtype=float32)
    >>> mx.nd.arange(2, 6, step=2, repeat=3, dtype='int32').asnumpy()
    array([2, 2, 2, 4, 4, 4], dtype=int32)
    """
    if infer_range is not None:
        warnings.warn('`infer_range` argument has been deprecated',
                      DeprecationWarning)
    if ctx is None:
        ctx = current_context()
    return _internal._arange(start=start, stop=stop, step=step, repeat=repeat,
                             infer_range=False, dtype=dtype, ctx=str(ctx))