Tensorflow Data API - Prefetch

Question

I'm trying to use the new TF features, namely the Data API, and I'm not sure how prefetch works . In the code below

def dataset_input_fn(...)
    dataset = tf.data.TFRecordDataset(filenames, compression_type="ZLIB")
    dataset = dataset.map(lambda x:parser(...))
    dataset = dataset.map(lambda x,y: image_augmentation(...)
                      , num_parallel_calls=num_threads
                     )

    dataset = dataset.shuffle(buffer_size)
    dataset = dataset.batch(batch_size)    
    dataset = dataset.repeat(num_epochs)
    iterator = dataset.make_one_shot_iterator()

Does it matter between each line above i put dataset=dataset.prefetch(batch_size)? Or maybe it should be after every operation that will use output_buffer_sizeif the data set came from tf.contrib.data?

Answer 1

In the github discussion I found a comment from mrry:

, TF 1.4 Dataset.prefetch(), , (). ( , .)

, Dataset.prefetch() , tf.FIFOQueue, . () , tf.FIFOQueue.

, prefetch , . , .

buffer_size Dataset.map, Dataset.prefetch Dataset.shuffle, mrry .