tf.compat.v1.data.experimental.sample_from_datasets
Samples elements at random from the datasets in datasets
.
tf.compat.v1.data.experimental.sample_from_datasets( datasets, weights=None, seed=None )
Args | |
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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 | |
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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. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/compat/v1/data/experimental/sample_from_datasets