(self, state)
return sample, log_prob
Computes a sample and its probability from each of a batch of states.

    Args:
      state: An RnnNadeStateTuple containing the state of the RNN-NADE for each
          sample, sized
          `([batch_size, self._nade.num_hidden], [batch_size, num_dims],
            [batch_size, self._rnn_cell.state_size]`).

    Returns:
      sample: A sample for each input state, sized `[batch_size, num_dims]`.
      log_prob: The log probability of each sample, sized `[batch_size, 1]`.
Computes a sample and its probability from each of a batch of states.
Computes a sample and its probability from each of a batch of states .
def sample_single(self, state):
    """Computes a sample and its probability from each of a batch of states.

    Args:
      state: An RnnNadeStateTuple containing the state of the RNN-NADE for each
          sample, sized
          `([batch_size, self._nade.num_hidden], [batch_size, num_dims],
            [batch_size, self._rnn_cell.state_size]`).

    Returns:
      sample: A sample for each input state, sized `[batch_size, num_dims]`.
      log_prob: The log probability of each sample, sized `[batch_size, 1]`.
    """
    sample, log_prob = self._nade.sample(state.b_enc, state.b_dec)

    return sample, log_prob
def sample_single ( self , state ) : sample , log_prob = self . _nade . sample ( state . b_enc , state . b_dec ) return sample , log_prob