univariate.py 文件源码

def __init__(self,
                 loc,
                 scale,
                 group_ndims=0,
                 is_reparameterized=True,
                 use_path_derivative=False,
                 check_numerics=False,
                 **kwargs):
        self._loc = tf.convert_to_tensor(loc)
        self._scale = tf.convert_to_tensor(scale)
        dtype = assert_same_float_dtype(
            [(self._loc, 'Laplace.loc'),
             (self._scale, 'Laplace.scale')])

        try:
            tf.broadcast_static_shape(self._loc.get_shape(),
                                      self._scale.get_shape())
        except ValueError:
            raise ValueError(
                "loc and scale should be broadcastable to match each "
                "other. ({} vs. {})".format(
                    self._loc.get_shape(), self._scale.get_shape()))
        self._check_numerics = check_numerics
        super(Laplace, self).__init__(
            dtype=dtype,
            param_dtype=dtype,
            is_continuous=True,
            is_reparameterized=is_reparameterized,
            use_path_derivative=use_path_derivative,
            group_ndims=group_ndims,
            **kwargs)