Function Differences with tf.data.Dataset.prefetch
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)