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tf.data.experimental.prefetch_to_device

A transformation that prefetches dataset values to the given device.

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.
Returns
A Dataset transformation function, which can be passed to tf.data.Dataset.apply.

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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/data/experimental/prefetch_to_device