tf.data.experimental.sample_from_datasets
Samples elements at random from the datasets in datasets.
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.random.set_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. |