tf.data.experimental.sample_from_datasets

Samples elements at random from the datasets in datasets.

Compat aliases for migration

See Migration guide for more details.

tf.data.experimental.sample_from_datasets(
    datasets, weights=None, seed=None
)

Args
`datasets`	A list of `tf.data.Dataset` objects with compatible structure.
`weights`	(Optional.) A list of `len(datasets)` floating-point values where `weights[i]` represents the probability with which an element should be sampled from `datasets[i]`, or a `tf.data.Dataset` object where each element is such a list. Defaults to a uniform distribution across `datasets`.
`seed`	(Optional.) A `tf.int64` scalar `tf.Tensor`, representing the random seed that will be used to create the distribution. See `tf.compat.v1.set_random_seed` for behavior.

Returns
A dataset that interleaves elements from `datasets` at random, according to `weights` if provided, otherwise with uniform probability.

Raises
`TypeError`	If the `datasets` or `weights` arguments have the wrong type.
`ValueError`	If the `weights` argument is specified and does not match the length of the `datasets` element.

Args