code: def index_table_from_dataset(
      dataset=None,
      num_oov_buckets=0,
      vocab_size=None,
      default_value=-1,
      hasher_spec=lookup_ops.FastHashSpec,
      key_dtype=dtypes.string,
      name=None,
  ):
      """Returns an index lookup table based on the given dataset.
  
      This operation constructs a lookup table based on the given dataset of keys.
  
      Any lookup of an out-of-vocabulary token will return a bucket ID based on its
      hash if `num_oov_buckets` is greater than zero. Otherwise it is assigned the
      `default_value`.
      The bucket ID range is
      `[vocabulary size, vocabulary size + num_oov_buckets - 1]`.
  
      Sample Usages:
  
      >>> ds = tf.data.Dataset.range(100).map(lambda x: tf.strings.as_string(x * 2))
      >>> table = tf.data.experimental.index_table_from_dataset(
      ...                                     ds, key_dtype=dtypes.int64)
      >>> table.lookup(tf.constant(['0', '2', '4'], dtype=tf.string)).numpy()
      array([0, 1, 2])
  
      Args:
        dataset: A dataset of keys.
        num_oov_buckets: The number of out-of-vocabulary buckets.
        vocab_size: Number of the elements in the vocabulary, if known.
        default_value: The value to use for out-of-vocabulary feature values.
          Defaults to -1.
        hasher_spec: A `HasherSpec` to specify the hash function to use for
          assignation of out-of-vocabulary buckets.
        key_dtype: The `key` data type.
        name: A name for this op (optional).
  
      Returns:
        The lookup table based on the given dataset.
  
      Raises:
        ValueError: If
          * `num_oov_buckets` is negative
          * `vocab_size` is not greater than zero
          * The `key_dtype` is not integer or string
      """
      return table_from_dataset(
          dataset.enumerate().map(lambda v, k: (k, v)),
          num_oov_buckets,
          vocab_size,
          default_value,
          hasher_spec,
          key_dtype,
          name,
      )
  
file_path: tensorflow/tensorflow/python/data/experimental/ops/lookup_ops.py
imports: from tensorflow.python.data.experimental.ops.cardinality import assert_cardinality
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import gen_experimental_dataset_ops
  from tensorflow.python.ops import lookup_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 3 for calling a global function with example usage: index_table_from_dataset(dataset, num_oov_buckets, vocab_size, default_value, hasher_spec, key_dtype, name) and returns: table_from_dataset