code: def filter_text_length(d, filter_len):
      if "texts" in d:
          return tf.strings.length(d["texts"][0]) > filter_len
      elif "caption" in d:
          return tf.strings.length(d["caption"]) > filter_len
      elif "alt_texts" in d:
          return tf.strings.length(d["alt_texts"][0]) > filter_len
      return True
  
imports: import functools
  from big_vision.datasets.imagenet import class_names
  import numpy
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib.big_transfer import registry
  from scenic.dataset_lib.big_transfer.preprocessing import utils
  from scenic.projects.t5 import tokenizer
  import tensorflow
label_desc: Use image node_id 10 for calling a global function with example usage: filter_text_length(d, filter_len) and returns: True, unknown, unknown, unknown