code: def get_default_dataset_config():
      """Gets default configs for wit_internal (en) dataset."""
      dataset_configs = ml_collections.ConfigDict()
      # Add path to your data here:
      dataset_configs.dataset = ""
      dataset_configs.train_split = "train"
      dataset_configs.output_max_num_tokens = OUTPUT_MAX_LENGTH
      dataset_configs.knowledge_max_num_tokens = OUTPUT_MAX_LENGTH
      dataset_configs.image_size = IMAGE_SIZE
      dataset_configs.pp_train = (
          f"get_table_knowledge|decode|resize(resize_size={IMAGE_SIZE})|value_range(-1,1)|t5_tokenize(max_num_tokens={KNOWLEDGE_MAX_LENGTH},"
          ' inkey="knowledge", outkey="knowledge_tokens",'
          f' prompt="{data_utils.KNOWLEDGE_PREFIX}")|keep("image",'
          ' "knowledge_tokens", "canonical_doc_id")'
      )
      dataset_configs.vocab_size = data_utils.VOCAB_SIZE_T5
      dataset_configs.prefetch_to_device = 2
      return dataset_configs
  
file_path: scenic/scenic/projects/knowledge_visual_language/data/wit_table_dataset.py
imports: import functools
  from typing import Optional
  from absl import logging
  import jax
  import jax.numpy
  import ml_collections
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib import datasets
  from scenic.dataset_lib.big_transfer import builder
  from scenic.dataset_lib.big_transfer import registry
  from scenic.dataset_lib import web_image_text_dataset
  from scenic.projects.knowledge_visual_language.data import data_utils
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: get_default_dataset_config() and returns: dataset_configs