tf.contrib.data.sample_from_datasets

Samples elements at random from the datasets in datasets. (deprecated)

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

Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.data.experimental.sample_from_datasets(...).

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.