class_docstr: The basic seq2seq model (without attention).
  
  Example:
  
      .. code-block:: python
  
          model = BasicSeq2seq(data_hparams, model_hparams)
          exor = tx.run.Executor(
              model=model,
              data_hparams=data_hparams,
              config=run_config)
          exor.train_and_evaluate(
              max_train_steps=10000,
              eval_steps=100)
  
  .. document private functions
  .. automethod:: _build
class_docstr_tok: ["The","basic","seq2seq","model","(","without","attention",")",".","Example",":","..","code-block",":",":","python","model","=","BasicSeq2seq","(","data_hparams",",","model_hparams",")","exor","=","tx.run.Executor","(","model=model",",","data_hparams=data_hparams",",","config=run_config",")","exor.train_and_evaluate","(","max_train_steps=10000",",","eval_steps=100",")","..","document","private","functions","..","automethod",":",":","_build"]
docstr: Embeds the target inputs. Used in training.
          
docstr_tok: ["Embeds","the","target","inputs",".","Used","in","training","."]
code: def embed_target(self, features, labels, mode):
      """Embeds the target inputs. Used in training."""
      return self._tgt_embedder(
          ids=labels["target_text_ids"], mode=mode
      )
  
file_path: texar/texar/tf/models/seq2seq/basic_seq2seq.py
imports: import tensorflow
  from texar.tf.models.seq2seq.seq2seq_base import Seq2seqBase
  from texar.tf.modules.decoders.beam_search_decode import beam_search_decode
  from texar.tf.utils import utils
  from texar.tf.utils.shapes import get_batch_size
label_desc: Use image node_id 6 for calling the BasicSeq2seq obj's underlying member method code with example usage: obj.embed_target(features, labels, mode) and returns: self