tf.data.experimental.prefetch_to_device
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A transformation that prefetches dataset values to the given device
.
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more details.
tf.compat.v1.data.experimental.prefetch_to_device
tf . data . experimental . prefetch_to_device (
device , buffer_size = None
)
Note: Although the transformation creates a tf.data.Dataset
, the
transformation must be the final Dataset
in the input pipeline.
For example,
>>> dataset = tf . data . Dataset . from_tensor_slices ([ 1 , 2 , 3 ])
>>> dataset = dataset . apply ( tf . data . experimental . prefetch_to_device ( "/cpu:0" ))
>>> for element in dataset :
... print ( f 'Tensor { element } is on device { element . device } ' )
Tensor 1 is on device / job : localhost / replica : 0 / task : 0 / device : CPU : 0
Tensor 2 is on device / job : localhost / replica : 0 / task : 0 / device : CPU : 0
Tensor 3 is on device / job : localhost / replica : 0 / task : 0 / device : CPU : 0
Args
device
A string. The name of a device to which elements will be prefetched.
buffer_size
(Optional.) The number of elements to buffer on device
.
Defaults to an automatically chosen value.
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 2024-04-26 UTC.
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