code: def feed_shape_type_def(self):
      TS = tf.TensorShape
      types = {"tokens": tf.int32}
      shapes = {
          "tokens": TS([self.target_dim, None]),
      }
      if self.config.use_auxiliary_info:
          TS = tf.TensorShape
          types["context"] = tf.float32
          shapes["context"] = TS(
              [self.target_dim, None, self.config.context_dim]
          )
      return (
          (
              types,
              tf.float32,
          ),
          (
              shapes,
              TS([]),
          ),
      )
  
imports: import numpy
  from finetune.base import BaseModel
  from finetune.input_pipeline import BasePipeline
  from finetune.encoding.input_encoder import EncodedOutput
  from finetune.encoding.target_encoders import IDEncoder
  import tensorflow
  from finetune.nn.target_blocks import multi_choice_question
  from finetune.util import list_transpose
  from finetune.encoding.input_encoder import tokenize_context
  from finetune.model import PredictMode
label_desc: Use image node_id 6 for calling the MultipleChoicePipeline obj's underlying member method code with example usage: obj.feed_shape_type_def() and returns: types,  tf,  shapes,  TS