'Initializes a GRU cell.
The Variables of the GRU cell are initialized in a way that exactly matches
the skip-thoughts paper: recurrent weights are initialized from random
orthonormal matrices and non-recurrent weights are initialized from random
uniform matrices.
Args:
num_units: Number of output units.
Returns:
cell: An instance of RNNCell with variable initializers that match the
skip-thoughts paper.'

def _initialize_gru_cell(self, num_units):

    return gru_cell.LayerNormGRUCell(num_units, w_initializer=self.uniform_initializer, u_initializer=random_orthonormal_initializer, b_initializer=tf.constant_initializer(0.0))
