tf.data.experimental.assert_cardinality

Asserts the cardinality of the input dataset.

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Compat aliases for migration

tf.compat.v1.data.experimental.assert_cardinality

tf.data.experimental.assert_cardinality(
    expected_cardinality
)

Used in the notebooks

Used in the tutorials
Fine tuning models for plant disease detection

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.

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Last updated 2024-04-26 UTC.

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Used in the notebooks

Args

Returns

Raises

tf.data.experimental.assert_cardinality