class_docstr: Wrapper class for machine translation.
class_docstr_tok: ["Wrapper","class","for","machine","translation","."]
docstr: Predict on a single minibatch of examples.
code: def predict(self, inputs):
      """Predict on a single minibatch of examples."""
      model_inputs = (self.preprocess(ex) for ex in inputs)
      outputs = self.wrapped.predict(model_inputs)
      return (
          utils.remap_dict(mo, self.FIELD_RENAMES) for mo in outputs
      )
  
imports: import re
  import attr
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.examples.models import model_utils
  from lit_nlp.lib import file_cache
  from lit_nlp.lib import utils
  import tensorflow
  import tensorflow_text
  import transformers
  from rouge_score import rouge_scorer
label_desc: Use image node_id 4 for calling the TranslationWrapper obj's underlying member method code with example usage: obj.predict(inputs) and returns: unknown