'Run the cell with the declared dropouts.'

def __call__(self, inputs, state, scope=None):

    is_training = config.get_training_mode()
    if ((not isinstance(self._input_keep_prob, float)) or (self._input_keep_prob < 1)):
        inputs = tf.cond(is_training, (lambda : tf.nn.dropout(inputs, self._input_keep_prob, seed=self._seed)), (lambda : inputs))
    (output, new_state) = self._cell(inputs, state)
    if ((not isinstance(self._output_keep_prob, float)) or (self._output_keep_prob < 1)):
        output = tf.cond(is_training, (lambda : tf.nn.dropout(output, self._output_keep_prob, seed=self._seed)), (lambda : output))
    return (output, new_state)
