4aef40d869462e0aae0920354df6b08a177a54df,gpflow/base.py,Parameter,log_prior,#Parameter#,66

Before Change

    def log_prior(self):
        x = self.read_value()
        y = self._unconstrained
        dtype = x.dtype

        out = tf.convert_to_tensor(0., dtype=dtype)

        bijector = self.transform
        if self.prior is not None:
            out += tf.reduce_sum(self.prior.log_prob(x))

After Change

        x = self.read_value()
        y = self._unconstrained

        if self.prior is not None:
            out = tf.reduce_sum(self.prior.log_prob(x))
            if self.transform is not None:
                log_det_jacobian = self.transform.forward_log_det_jacobian(y, y.shape.ndims)
                out += tf.reduce_sum(log_det_jacobian)
            return out
        else:
            return tf.convert_to_tensor(0., dtype=self.dtype)

    @property
    def handle(self):
        return self._unconstrained.handle

Instances