code: def cardinality(dataset):
      """Returns the cardinality of `dataset`, if known.
  
      The operation returns the cardinality of `dataset`. The operation may return
      `tf.data.experimental.INFINITE_CARDINALITY` if `dataset` contains an infinite
      number of elements or `tf.data.experimental.UNKNOWN_CARDINALITY` if the
      analysis fails to determine the number of elements in `dataset` (e.g. when the
      dataset source is a file).
  
      >>> dataset = tf.data.Dataset.range(42)
      >>> print(tf.data.experimental.cardinality(dataset).numpy())
      42
      >>> dataset = dataset.repeat()
      >>> cardinality = tf.data.experimental.cardinality(dataset)
      >>> print((cardinality == tf.data.experimental.INFINITE_CARDINALITY).numpy())
      True
      >>> dataset = dataset.filter(lambda x: True)
      >>> cardinality = tf.data.experimental.cardinality(dataset)
      >>> print((cardinality == tf.data.experimental.UNKNOWN_CARDINALITY).numpy())
      True
  
      Args:
        dataset: A `tf.data.Dataset` for which to determine cardinality.
  
      Returns:
        A scalar `tf.int64` `Tensor` representing the cardinality of `dataset`. If
        the cardinality is infinite or unknown, the operation returns the named
        constant `INFINITE_CARDINALITY` and `UNKNOWN_CARDINALITY` respectively.
      """
  
      return gen_dataset_ops.dataset_cardinality(
          dataset._variant_tensor
      )
  
file_path: tensorflow-upstream/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 1 for calling a global function with example usage: cardinality(dataset) and returns: gen_dataset_ops