Samples elements at random from the datasets in datasets. (deprecated)
tf.contrib.data.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.
|
View source on GitHub