code: def get_inputs(params):
      """Returns some parameters used by the model."""
      if FLAGS.download_if_missing and not FLAGS.use_synthetic_data:
          movielens.download(FLAGS.dataset, FLAGS.data_dir)
  
      if FLAGS.seed is not None:
          np.random.seed(FLAGS.seed)
  
      if FLAGS.use_synthetic_data:
          producer = data_pipeline.DummyConstructor()
          (
              num_users,
              num_items,
          ) = data_preprocessing.DATASET_TO_NUM_USERS_AND_ITEMS[
              FLAGS.dataset
          ]
          num_train_steps = rconst.SYNTHETIC_BATCHES_PER_EPOCH
          num_eval_steps = rconst.SYNTHETIC_BATCHES_PER_EPOCH
      else:
          (
              num_users,
              num_items,
              producer,
          ) = data_preprocessing.instantiate_pipeline(
              dataset=FLAGS.dataset,
              data_dir=FLAGS.data_dir,
              params=params,
              constructor_type=FLAGS.constructor_type,
              deterministic=FLAGS.seed is not None,
          )
          num_train_steps = producer.train_batches_per_epoch
          num_eval_steps = producer.eval_batches_per_epoch
  
      return (
          num_users,
          num_items,
          num_train_steps,
          num_eval_steps,
          producer,
      )
  
file_path: autodist/examples/benchmark/utils/recommendation/ncf_common.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import json
  import os
  import numpy
  from absl import flags
  from absl import logging
  import tensorflow
  from utils.recommendation import constants
  from utils.recommendation import data_pipeline
  from utils.recommendation import data_preprocessing
  from utils.recommendation import movielens
  from utils.flags import core
  from utils.misc import keras_utils
label_desc: Use image node_id 1 for calling a global function with example usage: get_inputs(params) and returns: num_users,  num_items,  num_train_steps,  num_eval_steps,  producer