code: def get_helper(
      helper_type,
      inputs=None,
      sequence_length=None,
      embedding=None,
      start_tokens=None,
      end_token=None,
      **kwargs,
  ):
      """Creates a Helper instance.
  
      Args:
          helper_type: A :tf_main:`Helper <contrib/seq2seq/Helper>` class, its
              name or module path, or a class instance. If a class instance
              is given, it is returned directly.
          inputs (optional): Inputs to the RNN decoder, e.g., ground truth
              tokens for teacher forcing decoding.
          sequence_length (optional): A 1D int Tensor containing the
              sequence length of :attr:`inputs`.
          embedding (optional): A callable that takes a vector tensor of
              indexes (e.g., an instance of subclass of
              :class:`~texar.tf.modules.EmbedderBase`), or the `params` argument
              for `embedding_lookup` (e.g., the embedding Tensor).
          start_tokens (optional): A int Tensor of shape `[batch_size]`,
              the start tokens.
          end_token (optional): A int 0D Tensor, the token that marks end
              of decoding.
          **kwargs: Additional keyword arguments for constructing the helper.
  
      Returns:
          A helper instance.
      """
      module_paths = [
          "texar.tf.modules.decoders.rnn_decoder_helpers",
          "texar.tf.modules.decoders.tf_helpers",
          # 'tensorflow.contrib.seq2seq',
          "texar.tf.custom",
      ]
      class_kwargs = {
          "inputs": inputs,
          "sequence_length": sequence_length,
          "embedding": embedding,
          "start_tokens": start_tokens,
          "end_token": end_token,
      }
      class_kwargs.update(kwargs)
      return utils.check_or_get_instance_with_redundant_kwargs(
          helper_type, class_kwargs, module_paths
      )
  
imports: import tensorflow
  from tensorflow.python.ops import array_ops
  from tensorflow_probability import distributions
  from texar.tf.modules.decoders.tf_helpers import Helper, TrainingHelper, GreedyEmbeddingHelper
  from texar.tf.modules.embedders.embedder_utils import soft_embedding_lookup
  from texar.tf.utils import utils
label_desc: Use image node_id 3 for calling a global function with example usage: get_helper(helper_type, inputs, sequence_length, embedding, start_tokens, end_token) and returns: utils