tensorflow/models · error · ValueError

Expected to find {} users, but found {}

Error message

Expected to find {} users, but found {}

What it means

Error "Expected to find {} users, but found {}" thrown in tensorflow/models.

Source

Thrown at official/recommendation/data_preprocessing.py:234

    constructor_type: The name of the constructor subclass that should be used
      for the input pipeline.
    deterministic: Tell the data constructor to produce deterministically.
    epoch_dir: Directory in which to store the training epochs.
    generate_data_offline: Boolean, whether current pipeline is done offline or
      while training.
  """
  logging.info("Beginning data preprocessing.")

  st = timeit.default_timer()
  raw_rating_path = os.path.join(data_dir, dataset, movielens.RATINGS_FILE)
  cache_path = os.path.join(data_dir, dataset, rconst.RAW_CACHE_FILE)

  raw_data, _ = _filter_index_sort(raw_rating_path, cache_path)
  user_map, item_map = raw_data["user_map"], raw_data["item_map"]
  num_users, num_items = movielens.DATASET_TO_NUM_USERS_AND_ITEMS[dataset]

  if num_users != len(user_map):
    raise ValueError("Expected to find {} users, but found {}".format(
        num_users, len(user_map)))
  if num_items != len(item_map):
    raise ValueError("Expected to find {} items, but found {}".format(
        num_items, len(item_map)))

  producer = data_pipeline.get_constructor(constructor_type or "materialized")(
      maximum_number_epochs=params["train_epochs"],
      num_users=num_users,
      num_items=num_items,
      user_map=user_map,
      item_map=item_map,
      train_pos_users=raw_data[rconst.TRAIN_USER_KEY],
      train_pos_items=raw_data[rconst.TRAIN_ITEM_KEY],
      train_batch_size=params["batch_size"],
      batches_per_train_step=params["batches_per_step"],
      num_train_negatives=params["num_neg"],
      eval_pos_users=raw_data[rconst.EVAL_USER_KEY],
      eval_pos_items=raw_data[rconst.EVAL_ITEM_KEY],

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/recommendation/data_preprocessing.py:234 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/99758b403b26a9b1. Report an issue: GitHub.