def zero_state(self, sample_batch_shape=()):
h0 = tf.zeros([<NUM_LIT:1>, self.hidden_size])<EOL>c0 = tf.zeros([<NUM_LIT:1>, self.hidden_size])<EOL>combined_shape = tf.concat((tf.convert_to_tensor(<EOL>value=sample_batch_shape, dtype=tf.int32), [self.dimensions]),<EOL>axis=-<NUM_LIT:1>)<EOL>previous_output = tf.zeros(combined_shape)<EOL>return previous_output, (h0, c0)<EOL>
Returns an initial state for the LSTM cell.

        Args:
          sample_batch_shape: A 0D or 1D tensor of the combined sample and
            batch shape.

        Returns:
          A tuple of the initial previous output at timestep 0 of shape
          [sample_batch_shape, dimensions], and the cell state.