class_docstr: Base class for image question answer problem.
class_docstr_tok: ["Base","class","for","image","question","answer","problem","."]
code: def feature_encoders(self, data_dir):
      input_encoder = text_encoder.ImageEncoder(
          channels=self.num_channels
      )
      vocab_file = os.path.join(data_dir, self.vocab_filename)
      question_encoder = text_encoder.TokenTextEncoder(
          vocab_file, replace_oov="UNK"
      )
      label_file = os.path.join(data_dir, self.label_filename)
      target_encoder = text_encoder.ClassLabelEncoder(
          class_labels_fname=label_file
      )
      return {
          "inputs": input_encoder,
          "question": question_encoder,
          "targets": target_encoder,
      }
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import base64
  import csv
  import json
  import os
  import random
  import sys
  import tarfile
  import zipfile
  import numpy
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import image_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import vqa_utils
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import metrics
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 11 for calling the ImageQuestion2MultilabelProblem obj's underlying member method code with example usage: obj.feature_encoders(data_dir) and returns: dict