tf.data.experimental.assert_cardinality | TensorFlow v2.16.1 (original) (raw)
tf.data.experimental.assert_cardinality
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Asserts the cardinality of the input dataset.
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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 totf.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.