def __init__(self, axis=None, keep_dims=None): super(Moments, self).__init__() if axis is None: axis = () if isinstance(axis, tuple): for idx, item in enumerate(axis): validator.check_value_type("axis[%d]" % idx, item, [int], self.cls_name) self.axis = validator.check_value_type('axis', axis, [int, tuple], self.cls_name) if keep_dims is None: keep_dims = False self.keep_dims = validator.check_value_type('keep_dims', keep_dims, [bool], self.cls_name) self.cast = P.Cast() self.reduce_mean = P.ReduceMean(keep_dims=True) self.square_diff = P.SquaredDifference() self.squeeze = P.Squeeze(self.axis)
def __init__(self): super(SquaredDifference, self).__init__() self.squaredDiff = P.SquaredDifference()
def __init__(self): super(Net, self).__init__() self.ops = P.SquaredDifference()