(self, inputs, state)
return self._get_state(inputs, initial_state=state)
Computes the new RNN-NADE state from a batch of inputs.

    Args:
      inputs: A batch of values to compute the log probabilities of,
          sized `[batch_size, length, num_dims]`.
      state: An RnnNadeStateTuple containing the RNN-NADE for each value, sized
          `([batch_size, self._nade.num_hidden], [batch_size, num_dims],
            [batch_size, self._rnn_cell.state_size]`).

    Returns:
      new_state: The updated RNN-NADE state tuple given the new inputs.
Computes the new RNN-NADE state from a batch of inputs.
Computes the new RNN - NADE state from a batch of inputs .
def steps(self, inputs, state):
    """Computes the new RNN-NADE state from a batch of inputs.

    Args:
      inputs: A batch of values to compute the log probabilities of,
          sized `[batch_size, length, num_dims]`.
      state: An RnnNadeStateTuple containing the RNN-NADE for each value, sized
          `([batch_size, self._nade.num_hidden], [batch_size, num_dims],
            [batch_size, self._rnn_cell.state_size]`).

    Returns:
      new_state: The updated RNN-NADE state tuple given the new inputs.
    """
    return self._get_state(inputs, initial_state=state)
def steps ( self , inputs , state ) : return self . _get_state ( inputs , initial_state = state )