5809cb0b339612434f4f332a91a2cd3e4570c34d,gpflow/transforms.py,LowerTriangular,backward_tensor,#LowerTriangular#Any#,392

Before Change

        CAVEAT: Requires defined shape and can"t work with unknown shape.
        
        size = np.prod(y.shape.as_list())
        N = int(np.sqrt(size / self.num_matrices))
        reshaped = tf.reshape(y, shape=(self.num_matrices, N, N))
        indices = np.array([np.hstack(x) for x in
                            itertools.product(np.arange(self.num_matrices), np.dstack(np.tril_indices(N))[0])])
        triangular = tf.reshape(tf.gather_nd(reshaped, indices), shape=[-1])
        return triangular

    def log_jacobian_tensor(self, x):
        return tf.zeros((1,), settings.float_type)

After Change

            x tensor with shape self.num_matrices, (self.N**2 + self.N) / 2
        
        if self.squeeze:
            y = tf.expand_dims(y, axis=0)
        indices = np.vstack(np.tril_indices(self.N)).T
        indices = itertools.product(np.arange(self.num_matrices), indices)
        indices = np.array([np.hstack(x) for x in indices])
        triangular = tf.gather_nd(y, indices)
        return tf.reshape(triangular, [self.num_matrices, (self.N**2 + self.N) // 2])

    def log_jacobian_tensor(self, x):
        return tf.zeros((1,), settings.float_type)

Instances