tf.raw_ops.PrefetchDataset
Creates a dataset that asynchronously prefetches elements from input_dataset.
tf.raw_ops.PrefetchDataset(
input_dataset,
buffer_size,
output_types,
output_shapes,
slack_period=0,
legacy_autotune=True,
buffer_size_min=0,
metadata='',
name=None
)
| Args | |
|---|---|
input_dataset |
A Tensor of type variant. |
buffer_size |
A Tensor of type int64. The maximum number of elements to buffer in an iterator over this dataset. |
output_types |
A list of tf.DTypes that has length >= 1. |
output_shapes |
A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1. |
slack_period |
An optional int. Defaults to 0. |
legacy_autotune |
An optional bool. Defaults to True. |
buffer_size_min |
An optional int. Defaults to 0. |
metadata |
An optional string. Defaults to "". |
name |
A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor of type variant. |
© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/raw_ops/PrefetchDataset