>>> 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.
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2023-10-06 UTC."],[],[]]