class StandardCell:
    def __init__(self, name:str, cell_size, cell_count):
        self.scope = tf.VariableScope(False, name)
        with tf.variable_scope(self.scope):
            self.cell = rnn.MultiRNNCell([
                rnn.BasicLSTMCell(cell_size) for _ in range(cell_count)])
            self.std_input = tf.placeholder(tf.float32,
                                            [cell_size],
                                            'std_input')
            self.std_input_state = tf.placeholder(tf.float32,
                                                  [cell_count, 2, 1, cell_size],
                                                  'std_input_state')
            output, output_state = self.cell(
                tf.reshape(self.std_input, [1, cell_size]),
                [rnn.LSTMStateTuple(self.std_input_state[i][0],
                                    self.std_input_state[i][1])
                 for i in range(cell_count)])
            self.std_output = tf.reshape(output, [cell_size], 'std_output')
            self.std_output_state = tf.concat([
                tf.concat([
                    tf.reshape(output_state[i].c, [1, 1, 1, cell_size]),
                    tf.reshape(output_state[i].h, [1, 1, 1, cell_size]),
                    ], 1)
                for i in range(cell_count)
                ], 0, 'std_output_state')

    def __call__(self, input, state):
        with tf