parameters: (dataset)
return_statement: return gen_dataset_ops.dataset_cardinality(dataset._variant_tensor)
docstring: 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.
docstring_summary: Returns the cardinality of `dataset`, if known.
docstring_tokens: Returns the cardinality of dataset if known .
function: 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)
function_tokens: def cardinality ( dataset ) : return gen_dataset_ops . dataset_cardinality ( dataset . _variant_tensor )