class_docstr: Problem spec for French Street Name recognition.
class_docstr_tok: ["Problem","spec","for","French","Street","Name","recognition","."]
code: def feature_encoders(self, data_dir):
      # This vocab file must be present within the data directory.
      vocab_filename = os.path.join(data_dir, "charset_size134.txt")
      return {
          "inputs": text_encoder.ImageEncoder(),
          "targets": text_encoder.SubwordTextEncoder(vocab_filename),
      }
  
file_path: tensor2tensor/tensor2tensor/data_generators/fsns.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  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.layers import modalities
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the ImageFSNS obj's underlying member method code with example usage: obj.feature_encoders(data_dir) and returns: dict