Function Differences with tf.data.Dataset.prefetch

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tf.data.Dataset.prefetch

tf.data.Dataset.prefetch(
    buffer_size
)

For more information, see tf.data.Dataset.prefetch.

mindspore.dataset.config.set_prefetch_size

mindspore.dataset.config.set_prefetch_size(
    size
)

For more information, see mindspore.dataset.config.set_prefetch_size.

Differences

TensorFlow: A method of the Dataset class, used to set the size of the current data pipeline cache queue.

MindSpore: A function to set the global size of all data pipeline cache queues.

Code Example

# The following implements set_prefetch_size with MindSpore.
import mindspore.dataset as ds

ds.config.set_prefetch_size(2)

# The following implements prefetch with TensorFlow.
import tensorflow as tf

data = tf.constant([[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]])
dataset = tf.data.Dataset.from_tensor_slices(data)
dataset = dataset.prefetch(2)