_truediv__(self, value): return numpy.ndarray([0, 0])
        def __xor__(self, value): return numpy.ndarray([0, 0])
        def all(self, axis=None, out=None, keepdims=False): return np.ndarray([0, 0])
        def any(self, axis=None, out=None, keepdims=False): return np.ndarray([0, 0])
        def argmax(self, axis=None, out=None): return np.ndarray([0, 0])
        def argmin(self, axis=None, out=None): return np.ndarray([0, 0])
        def argpartition(self, kth, axis=-1, kind='introselect', order=None): return np.ndarray([0, 0])
        def argsort(self, axis=-1, kind='quicksort', order=None): return np.ndarray([0, 0])
        def astype(self, dtype, order='K', casting='unsafe', subok=True, copy=True): return np.ndarray([0, 0])
        def byteswap(self, inplace=False): return np.ndarray([0, 0])
        def choose(self, choices, out=None, mode='raise'): return np.ndarray([0, 0])
        def clip(self, min=None, max=None, out=None): return np.ndarray([0, 0])
        def compress(self, condition, axis=None, out=None): return np.ndarray([0, 0])
        def conj(self): return np.ndarray([0, 0])
        def conjugate(self): return np.ndarray([0, 0])
        def copy(self, order='C'): return np.ndarray([0, 0])
        def cumprod(self, axis=None, dtype=None, out=None): return np.ndarray([0, 0])
        def cumsum(self, axis=None, dtype=None, out=None): return np.ndarray([0, 0])
        def diagonal(self, offset=0, axis1=0, axis2=1): return np.ndarray([0, 0])
        def dot(self, b, out=None): return np.ndarray([0, 0])
        def dump(self, file): return None
        def dumps(self): return str()
        def fill(self, value): return None
        def flatten(self, order='C'): return np.ndarray([0, 0])
        def getfield(self, dtype, offset=0): return np.ndarray([0, 0])
        def item(self, *args): return uninferable
        def itemset(self, *args): return None
        def max(self, axis=None, out=None): return np.ndarray([0, 0])
        def mean(self, axis=None, dtype=None, out=None, keepdims=False): return np.ndarray([0, 0])
        def min(self, axis=None, out=None, keepdims=False): return np.ndarray([0, 0])
        def newbyteorder(self, new_order='S'): return np.ndarray([0, 0])
        def nonzero(self): return (1,)
        def partition(self, kth, axis=-1, kind='introselect', order=None): return None
        def prod(self, axis=None, dtype=None, out=None, keepdims=False): return np.ndarray([0, 0])
        def ptp(self, axis=None, out=None): return np.ndarray([0, 0])
        def put(self, indices, values, mode='raise'): return None
        def ravel(self, order='C'): return np.ndarray([0, 0])
        def repeat(self, repeats, axis=None): return np.ndarray([0, 0])
        def reshape(self, shape, order='C'): return np.ndarray([0, 0])
        def resize(self, new_shape, refcheck=True): return None
        def round(self, decimals=0, out=None): return np.ndarray([0, 0])
        def searchsorted(self, v, side='left', sorter=None): return np.ndarray([0, 0])
        def setfield(self, val, dtype, offset=0): return None
        def setflags(self, write=None, align=None, uic=None): return None
        def sort(self, axis=-1, kind='quicksort', order=None): return None
        def squeeze(self, axis=None): return np.ndarray([0, 0])
        def std(self, axis=None, dtype=None, out=None, ddof=0, keepdims=False): return np.ndarray([0, 0])
        def sum(self, axis=None, dtype=None, out=None, keepdims=False): return np.ndarray([0, 0])
        def swapaxes(self, axis1, axis2): return np.ndarray([0, 0])
        def take(self, indices, axis=None, out=None, mode='raise'): return np.ndarray([0, 0])
        def tobytes(self, order='C'): return b''
        def tofile(self, fid, sep="", format="%s"): return None
        def tolist(self, ): return []
        def tostring(self, order='C'): return b''
        def trace(self, offset=0, axis1=0, axis2=1, dtype=None, out=None): return np.ndarray([0, 0])
        def transpose(self, *axes): return np.ndarray([0, 0])
        def var(self, axis=None, dtype=None, out=None, ddof=0, keepdims=False): return np.ndarray([0, 0])
        def view(self, dtype=None, type=None): return np.ndarray([0, 0])
    z`
        @classmethod
        def __class_getitem__(cls, value):
            return cls
        )