Missed TensorFlow Dev Summit? Check out the video playlist. Watch recordings

tf.data.experimental.assert_cardinality

View source on GitHub

Asserts the cardinality of the input dataset.

tf.data.experimental.assert_cardinality(
    expected_cardinality
)

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.