tf.raw_ops.MultiDeviceIteratorInit
Stay organized with collections
Save and categorize content based on your preferences.
Initializes the multi device iterator with the given dataset.
tf.raw_ops.MultiDeviceIteratorInit(
dataset, multi_device_iterator, max_buffer_size, name=None
)
Args |
dataset
|
A Tensor of type variant . Dataset to be iterated upon.
|
multi_device_iterator
|
A Tensor of type resource .
A MultiDeviceIteratorResource.
|
max_buffer_size
|
A Tensor of type int64 .
The maximum size of the host side per device buffer to keep.
|
name
|
A name for the operation (optional).
|
Returns |
A Tensor of type int64 .
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2021-08-16 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2021-08-16 UTC."],[],[]]