# Function Differences with tf.data.Dataset.prefetch ## tf.data.Dataset.prefetch ```python tf.data.Dataset.prefetch( buffer_size ) ``` For more information, see [tf.data.Dataset.prefetch](https://www.tensorflow.org/versions/r2.6/api_docs/python/tf/data/Dataset#prefetch). ## mindspore.dataset.config.set_prefetch_size ```python mindspore.dataset.config.set_prefetch_size( size ) ``` For more information, see [mindspore.dataset.config.set_prefetch_size](https://mindspore.cn/docs/en/r2.0.0-alpha/api_python/dataset/mindspore.dataset.config.set_prefetch_size.html#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 ```python # 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) ```