code: def assert_cardinality(expected_cardinality):
      """Asserts the cardinality of the input dataset.
  
      NOTE: The following assumes that "examples.tfrecord" contains 42 records.
  
      >>> dataset = tf.data.TFRecordDataset("examples.tfrecord")
      >>> cardinality = tf.data.experimental.cardinality(dataset)
      >>> print((cardinality == tf.data.experimental.UNKNOWN_CARDINALITY).numpy())
      True
      >>> dataset = dataset.apply(tf.data.experimental.assert_cardinality(42))
      >>> print(tf.data.experimental.cardinality(dataset).numpy())
      42
  
      Args:
        expected_cardinality: The expected cardinality of the input dataset.
  
      Returns:
        A `Dataset` transformation function, which can be passed to
        `tf.data.Dataset.apply`.
  
      Raises:
        FailedPreconditionError: The assertion is checked at runtime (when iterating
          the dataset) and an error is raised if the actual and expected cardinality
          differ.
      """
  
      def _apply_fn(dataset):
          return _AssertCardinalityDataset(
              dataset, expected_cardinality
          )
  
      return _apply_fn
  
file_path: tensorflow/tensorflow/python/data/experimental/ops/cardinality.py
imports: from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import gen_dataset_ops
  from tensorflow.python.ops import gen_experimental_dataset_ops
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling a global function with example usage: assert_cardinality(expected_cardinality) and returns: _apply_fn, _AssertCardinalityDataset