tf.data.experimental.cardinality

Creates a dataset that deterministically chooses elements from datasets.

tf.data.experimental.choose_from_datasets(
    datasets, choice_dataset
)

For example, given the following datasets:

datasets = [tf.data.Dataset.from_tensors("foo").repeat(),
            tf.data.Dataset.from_tensors("bar").repeat(),
            tf.data.Dataset.from_tensors("baz").repeat()]

# Define a dataset containing `[0, 1, 2, 0, 1, 2, 0, 1, 2]`.
choice_dataset = tf.data.Dataset.range(3).repeat(3)

result = tf.data.experimental.choose_from_datasets(datasets, choice_dataset)

The elements of result will be:

"foo", "bar", "baz", "foo", "bar", "baz", "foo", "bar", "baz"

Args
`datasets`	A list of `tf.data.Dataset` objects with compatible structure.
`choice_dataset`	A `tf.data.Dataset` of scalar `tf.int64` tensors between `0` and `len(datasets) - 1`.

Returns
A dataset that interleaves elements from `datasets` according to the values of `choice_dataset`.

Raises
`TypeError`	If the `datasets` or `choice_dataset` arguments have the wrong type.

TensorFlow

tf.data / experimental / experimental.cardinality

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TensorFlow

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tf.data / experimental / experimental.cardinality

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