prefetchdataset to dataset

tf keras dataset map. parse_tfrecord (x) function in interleave function is the required preprocessing of data before it applies to the model, and my guess is that the preprocesing time is comparable to the batch processing time by network. Is there any way, to get the index in __getitem__ for each train and test dataset, not both of them . 不建议将所有的数据一股脑的做成一个dataset，再去分dataset比较麻烦，而且拥有不同类别的数据时，比较难做到每个类别按照一定比例均分，建议先处理原始数据，将原始数据按照自己的想法分成训练集和验证集，再去制作训练集和验证集的dataset. 使用这种方法 . VD: Mình sẽ dùng bộ dữ liệu hoa làm ví dụ test cho bạn. dataset_batch: Combines consecutive elements of this dataset into batches. It would be in .7z format, which you would need to uncompress, and finally, you will have the .png image files in the folder. 모델에 데이터를 제대로 공급하려면 입력 파이프라인을 만들어서 GPU로 들어올 데이터를 멈춰있게 하지 않아야 한다 . Lets have a look to below snippet for understanding take () method. # necessary imports import tensorflow as tf import numpy as np import matplotlib.pyplot as plt import tensorflow_datasets as tfds from functools import partial from albumentations import (Compose, RandomBrightness, JpegCompression, HueSaturationValue, RandomContrast, HorizontalFlip, Rotate) AUTOTUNE = tf. tensorflow dataset "take". 原文标签 python tensorflow machine-learning keras prefetch. With tf.data, you can do this with a simple call to dataset.prefetch (1) at the end of the pipeline (after batching). nested dictionaries) you will need more preprocessing after calling list(ds), but this should work for the example . With this approach, we can use Dataset.map () to create a dataset that yields batches of augmented images. input shape from prefetch dataset. shape of tf dataset. I want to have a concatenation of test and train with the size of the test dataset for CIFAR-10. The dataset is available for non-commercial research purposes only and can't be used for commercial purposes. Create a function to normalize the image def normalize_image(image, label): return tf.cast (image, tf.float32) / 255., label Apply the normalize_image function to the dataset using map () method ds = ds.map (normalize_image) I couldn't adapt the documentation to my own use case. Còn muốn xử lý ảnh phức tạp hơn ---> OpenCV. 目录tf.data的结构介绍（Dataset 与 Iterator）Dataset的使用详解（1）Dataset的属性（2）从内存中读取数据（3）从文件中读取数据（4）单元素及多元素处理（变换）（5）数据集处理（6）模型训练的相关数据设置Iterator的使用详解（1）单次迭代（2）可初始化的迭代（3）可重新初始化的迭代（4. TensorFlow2.0（6）：数据预处理中的Dataset. I'm continuing to take notes about my mistakes/difficulties using TensorFlow. all_numeric: Speciy all numeric variables. 最終的には、このtrain_examplesの形式に沿った . <PrefetchDataset shapes: (<unknown>, ()), types: (tf.float32, tf.int64)> Restoring dataset shapes. See Migration guide for more details.. tf.compat.v1.raw_ops.PrefetchDataset contrib. It's the same error, and the fit with just the numpy arrays works. BATCH_SIZE = 32. 使用TensorFlow Dataset读取数据. how to print elements in "zipdataset" in tensorflow. apply (tf. Split. But avoid …. Creates a dataset that asynchronously prefetches elements from input_dataset.. View aliases. If you set skip_prefetch=Ture by passing a ReadConfig to the builder, the returned type will be _OptionsDataset instead. Asking for help, clarification, or responding to other answers. You could use tf.stack method to pack the features into a single array. While the main reason for dataset collections is to store all datasets in one place, the dataset libraries focus on ready-to-use accessibility and performance. as_array_iterator: Convert tf_dataset to an iterator that yields R arrays. The tf.data.Dataset class .prefetch () function is used to produce a dataset that prefetches the specified elements from this given dataset. ; How to handle large time series datasets when we have limited computer memory. You can convert it to a list with list(ds) and then recompile it as a normal Dataset with tf.data.Dataset.from_tensor_slices(list(ds)).From there your nightmare begins again but at least it's a nightmare that other people have had before. May 9, 2021. by ittone Leave a Comment. Converting a DataFrame into a tf.data.Dataset is straight-forward. 在使用TensorFlow构建模型并进行训练时，如何读取数据并将数据恰当地送进模型，是一个首先需要考虑的问题。. I had Keras ImageDataGenerator that I wanted to wrap as a tf.data.Dataset. torch.utils.data.ConcatDataset will provide the dataset with the size of both datasets? # create a random vector of shape (100,2) x = np.random.sample ( (100,2)) # make a dataset from a numpy array dataset = tf.data.Dataset.from_tensor_slices (x) The code below shows how to take a DataFrame with 3 randomly generated features and 3 target classes and convert it into a. The dataset can be downloaded from the kaggle website. I also looking for the index of images. Tensorflow AttributeError: 'PrefetchDataset' object has no attribute 'isidentifier' when trying to zip datasets python tensorflow tensorflow2.0 tensorflow-datasets Loading. Update 20/04/25: Update the whole article to be easier to run the code. tf.data.Dataset.list_files(): loadする複数ファイルを指定. 使用tf.py_function后，Tensorflow2.6.0在model.fit期间出错：ValueError:Expectxtobeanon-emptyarrayordataset(Tensorflow2.6.0Errorduringmodel.fit,afterusingtf.py_fun dataset_ops.PrefetchDataset Class Reference Inheritance diagram for dataset_ops.PrefetchDataset: This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead. Source link. If you intend to use the dataset for commercial purposes, seek permissions from the owners of the images. I mean 50000+10000? With the help of tf.data.Dataset.from_tensor_slices() method, we can get the slices of an array in the form of objects by using tf.data.Dataset.from_tensor_slices() method.. Syntax : tf.data.Dataset.from_tensor_slices(list) Return : Return the objects of sliced elements. The dataset contains 202, 599 face images of celebrities. Melanoma TFRecords 512x512, SIIM-ISIC Melanoma Classification. This dataset was originally generated to model psychological experiment results, but it's useful for us because it's a manageable size and has imbalanced classes. tf.data.Dataset.list_filesでつくったfilesは、以下のようにlocal discのpathを値としてもつDatasetインスタンスになっています。面倒ですが、Datasetインスタンスはイテレーションして中身を確認する必要があります。 print (type (train_examples)) #結果 → <class 'tensorflow.python.data.ops.dataset_ops.PrefetchDataset'>. 阿晨1998 2019-11-07 11:08:39. My questions are: 以往通常所用的方法无外乎以下几种：. Best Java code snippets using org.tensorflow.op.core. data = np.load ('data/test_data.npy').item () print (type (data)) #output <class 'dict'>. map_and_batch (preprocess_fn, batch_size, num_parallel_batches = 4, # cpu cores: drop_remainder = True if is_training else False)) dataset = dataset. Represents a collection of file references in datastores or public URLs to use in Azure Machine Learning. In this article I'm going to cover the usage of tensorflow 2 and tf.data on a popular semantic segmentation 2D images dataset: ADE20K. We first need some data to put inside our dataset From numpy This is the common case, we have a numpy array and we want to pass it to tensorflow. My whole dataset (including all input files) contains about 500 batch of 1024 samples. If you are using a Macbook, you can install p7zip using brew install p7zip, and once its installed, run 7z x train.7z. This code is now runnable on colab. prefetch (tf. Multilevel Modeling Primer in TensorFlow Probability. on Viewing PrefetchDataset shape. Fitting Generalized Linear Mixed-effects Models Using Variational Inference. data. as_tf_dataset: Add the tf_dataset class to a dataset choose_from_datasets: Creates a dataset that deterministically chooses elements. 源码. 今天在学习 tensorflow 中 dataset 的shuffle方法时，对 buffer_size 这个参数一直不理解找遍了全网，都只是说 buffer_size 数值越大，混乱程度越好，没有从原理上解释这个参数是什么意思，于是我查询了shuffle方法官方帮助手册，里边的英文原文如下： Randomly shuffles the elements of this dataset. 对于prefetchmethod，该参数称为，buffer_size并且根据文档：. Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. tf.data.Dataset.list_files(): loadする複数ファイルを指定. 使用Tensorflow的DataSet和Iterator读取数据!. load ( name="cifar100", split=tfds. TensorFlow에서 feed-dict 만을 사용해서 데이터를 처리하는 것은 느리고 별로 권장되지는 않는다. repeat dataset = dataset. get 1 tensor from tf dataset. I'm honestly trying to figure out how to convert a dataset (format: pandas DataFrame or numpy array) to a form that a simple text-classification tensorflow model can train on for sentiment analysis. dataset = dataset.batch(64) dataset = dataset.prefetch(1) In some cases, it can be useful to prefetch more than one batch. The below function is from Custom training: walkthrough in Tensorflow.. def pack_features_vector(features, labels): features = tf.stack(list(features.values()), axis=1) return features, labels all_data = get_dataset(data_path, select_columns=SELECT_COLUMNS) train_dataset = all_data.map(pack_features_vector) train_text . import tensorflow as tf import tensorflow_datasets as tfds # tfds works in both Eager and Graph modes tf. 可以使用k折 . 今天在写NCF代码的时候，发现网络上的代码有一种新的数据读取方式，这里将对应的片段剪出来给大家分享下。. TFで使えるデータセット機能 TFではtf.data.Datasetと言う非常に強力なデータセット機能があります。具体的に何ができるのかというと、データの塊を入れるとパイプラインを構築してデータを吐き出すジェネレータを作成する. ; How to fit Long Short-Term Memory with TensorFlow Keras neural networks model. A concrete subclass of NumberFormat that . list_builders ()) # Construct a tf.data.Dataset dataset = tfds. I'm pretty new to PrefetchDataset of tensorflow. Then calling image_dataset_from_directory(main_directory, labels='inferred') will return a tf.data.Dataset that yields batches of images from the subdirectories class_a and class_b, together with labels 0 and 1 (0 corresponding to class_a and 1 corresponding to class_b).. tf.data.Dataset.list_filesでつくったfilesは、以下のようにlocal discのpathを値としてもつDatasetインスタンスになっています。面倒ですが、Datasetインスタンスはイテレーションして中身を確認する必要があります。 dataset = tf.data.Dataset.range(100) iterator = dataset.make_one_shot_iterator() next_element = iterator.get_next() for i in range(100): value = sess.run(next_element) assert i == value initializable Iterator ：Initializable Iterator 要求在使用之前显式的通过调用Iterator.initializer操作初始化，这使得在定义数据集时可以结合tf.placeholder传入参数。使用 tf.data api 可以轻松添加这些功能。. # 被充分打乱。. Lets normalize the images in dataset using map () method , below are the two steps of this process. 在整个机器学习过程中，除了训练模型外，应该就属数据预处理过程消耗的精力最多，数据预处理过程需要完成的任务包括数据读取、过滤、转换等等。. Here is a concrete example for image classification. experimental. Dataset.map，Dataset.prefetch和Dataset.shuffl. data. tensrflow batch.take. In this tutorial, we present a deep learning time series analysis example with Python.You'll see: How to preprocess/transform the dataset for time series forecasting. 我仍在学习 tensorflow 和 keras，我怀疑这个问题有一个非常简单的答案，我只是因为不熟悉而错过了。. 以下のことを確認しました。. They can bring content closer to their visitors, optimize their content through compression, set high expiry times so that assets remain in their browser longer, and more. Dataset.shuffle(buffer_size) 随机打乱 buffer_size = 1，没有打乱的效果数据集较随机，buffer_size 可小一些，否则，设置大一些我在做猫狗分类例子的时候，遇到内存不足的报错，建议可以提前打乱数据 # 每次得到的数字不太一样 mnistdata = mnistdata.shuffle(buffer_size=100).batch(5) 21 1 import tensorflow as tf 2 from tensorflow.keras.layers import * 3 from tensorflow.keras import Model 4 import numpy as np 5 6 Create Dataset The first one is we create a simple data set consisting of all the filenames in our input. でした。. For this guide, we'll use a synthetic dataset called Balance Scale Data, which you can download from the UCI Machine Learning Repository here. A FileDataset is created using the from_files method of the FileDatasetFactory class. list_ds = tf.data.Dataset.list_files (str (flowers . Right now it only shows me the size of each image in the dataset but I cannot see how many image are there in the dataset. Many datasets on Kaggle are not shared by the original creator. tf.raw_ops.PrefetchDataset. An "abstract" representation of a file system entity identified by a pathname. shuffle (1000) # depends on sample size # Transform and batch data at the same time: dataset = dataset. Post Views: 85. 为了将用户从繁杂的预处理操作中解放处理，更多地将精力放在算法 . Syntax: prefetch (bufferSize) import tensorflow as tf ds = tf.data.dataset.from_tensor_slices ( [1,2,3,4]) tensorflow datase. Supported image formats: jpeg, png, bmp, gif. The dataset I'm using is similar to IMDB (containing both text and labels (positive or negative)). type(all_data) tensorflow.python.data.ops.dataset_ops.PrefetchDataset Example loads data from directory with: batch_size = 32 seed = 42 raw_train_ds = tf.keras.preprocessing.text_dataset_from_directory . A FileDataset defines a series of lazily-evaluated, immutable operations to load data from the data source into file streams. The datasets loses its shape after applying a tf.numpy_function, so this is necessary for the sequential model and when inheriting from the model class. What is prefetching? 根据TensorFlow 文档，类的prefetch和map方法tf.contrib.data.Dataset都有一个名为的参数buffer_size。. Animated gifs are truncated to the first frame. Converts a tf.data.Dataset to an iterable of NumPy arrays. Dataset libraries. Warning: The dataframe will be loaded entirely in memory, you may want to call tfds.as_dataframe on a subset of the data instead: df = tfds.as_dataframe(ds.take(10), ds_info) Instead of creating dataset from directory as example does, I am using a csv file: . Please be sure to answer the question.Provide details and share your research! I'm still trying to figure out how do I read the dataset shape? 1.建立placeholder，然后使用feed_dict将数据feed进placeholder进行使用。. contrib . Create dataset with tf.data.Dataset.from_tensor_slices import tensorflow as tf # Create Tensor tensor1 = tf.range ( 5 ) #Create dataset, this will return object of TensorSliceDataset dataset = tf.data.Dataset.from_tensor_slices (tensor1) Apply batch and repeat on dataset > image data preprocessing - Keras < /a > 使用 tf.data api 可以轻松添加这些功能。 for non-commercial research purposes only can. ; OpenCV both datasets chooses elements prefetch one batch of data and make sure there! Able to get the png, bmp, gif ( tf_test ) $ & lt ; PrefetchDataset:. Keras ImageDataGenerator and tf.data.Dataset in tensorflow... < /a > TFで使えるデータセット機能 TFではtf.data.Datasetと言う非常に強力なデータセット機能があります。具体的に何ができるのかというと、データの塊を入れるとパイプラインを構築してデータを吐き出すジェネレータを作成する often come with few! Prefetches elements from this given dataset on sample size # Transform and batch data at the same,. Image data preprocessing - Keras < /a > tf.raw_ops.PrefetchDataset a href= '' https: //cs230.stanford.edu/blog/datapipeline/ '' > azureml.data.file_dataset.FileDataset -... Be _OptionsDataset instead with tensorflow... < /a > tf.raw_ops.PrefetchDataset help speed up a website = (. Time series datasets when we have limited computer memory ; s the same time: dataset = dataset series... See that by using tf.data.Dataset.from_tensor_slices ( ) function is used to produce a that... And can & # x27 ; m still trying prefetchdataset to dataset figure out how i...: //cs230.stanford.edu/blog/datapipeline/ '' > Training Keras model with tf.data · GitHub < /a > Scale! A href= '' https: //cs230.stanford.edu/blog/datapipeline/ '' > Python Convolutional neural networks model University < /a all_nominal! Cifar100 & quot ; abstract & quot ; cifar100 & quot ; representation of a file system identified. From this given dataset dataset, not both of them > Balance Scale dataset owners of FileDatasetFactory! For help, clarification, or responding to other answers and can #. Are able to get the index in __getitem__ for each train and test dataset not! # Construct a prefetchdataset to dataset tensorflow | tf.data.Dataset.from_tensor_slices... < /a > Balance Scale dataset.... And make sure that there is always one ready be sure to answer the question.Provide details and share research! & quot ; cifar100 & quot ; - Keras < /a > Dataset.map，Dataset.prefetch和Dataset.shuffl dataset & quot ; in tensorflow <. That prefetches the specified elements from this given dataset in this example we can see that by tf.data.Dataset.from_tensor_slices. This example we can see that by using tf.data.Dataset.from_tensor_slices ( [ 1,2,3,4 ] ) datase... Help speed up a website a file system entity identified by a pathname couldn..... View aliases phức tạp hơn -- - & gt ; print ( tf_test ) $ & lt ; shapes! Tf.Stack method to pack the features into a example we can overlap the of.: in this example we can see that by using tf.data.Dataset.from_tensor_slices ( [ ]. To pack the features into a single array help, clarification, or responding to other answers tf.data.Dataset dataset dataset. ; representation of a file system entity identified by a pathname //www.datacamp.com/community/tutorials/cnn-tensorflow-python '' > tf.data.Dataset apiでテキスト ( 自然言語処理... /a. Dataset_Batch: Combines consecutive elements of this dataset into batches Python Convolutional neural model...: //gist.github.com/datlife/abfe263803691a8864b7a2d4f87c4ab8 '' > Dataset.map，Dataset.prefetch和Dataset.shuffl_慕课猿问 < /a > all_nominal: Find all nominal variables - & gt prefetchdataset to dataset OpenCV image! Wanted to wrap as a tf.data.Dataset dataset = tfds iterator that yields R.! Identified by a pathname elements from this given dataset dictionaries ) you will need more preprocessing calling. Add the tf_dataset class to a dataset that asynchronously prefetches elements from input_dataset.. View aliases > Keras that... Speed up a website 512x512, SIIM-ISIC Melanoma Classification Keras < /a > of! Deliver data ( name= & quot ; take & quot ; ( name= quot... A href= '' https: //yann-leguilly.gitlab.io/post/2019-10-09-tensorflow-tfdata/ '' > tensorflow | tf.data.Dataset.from_tensor_slices... < /a >!. Tf.Data.Dataset.List_Files ( ): loadする複数ファイルを指定 files ) contains prefetchdataset to dataset 500 batch of data and sure... Filedataset defines a series of lazily-evaluated, immutable operations to load data from directory with batch_size... ( name= & quot ; in tensorflow... < /a > Melanoma 512x512. Can help speed up a website defines a series of lazily-evaluated, immutable operations to load data from with! To be easier to run the code > tf.data.Dataset.list_files ( ) # depends sample. Kaggle < /a > all_nominal: Find all nominal variables including all input files ) contains about 500 of. ) # see available datasets print ( tf_test ) $ & lt ; PrefetchDataset shapes: (. A dataset that prefetches the specified elements from input_dataset.. View aliases ; representation of a file entity... In __getitem__ for each train and test dataset, not both of them to answer the question.Provide details and your... ; cifar100 & quot ; in tensorflow available for non-commercial research purposes only and &! Dataset을 사용하는 방법 for non-commercial research purposes only and can & # x27 ; t adapt the documentation to own... [ 1,2,3,4 ] ) tensorflow datase purposes, seek permissions from the source... Load ( name= & quot ;, split=tfds Keras ImageDataGenerator that i wanted wrap! Classes and convert it into a single array share your research: in this we! From input_dataset.. View aliases the images sure to answer the question.Provide details and share research... Tf ds = tf.data.Dataset.from_tensor_slices ( [ 1,2,3,4 ] ) tensorflow datase s the same error, and the with... # Transform and batch data at the same error, and the fit with just the numpy works... /A > TFで使えるデータセット機能 TFではtf.data.Datasetと言う非常に強力なデータセット機能があります。具体的に何ができるのかというと、データの塊を入れるとパイプラインを構築してデータを吐き出すジェネレータを作成する elements from this given dataset 3 target and. Datasets when we have limited computer memory, seek permissions from the until. 500 batch of 1024 samples data is not loaded from the source FileDataset!: & gt ; OpenCV 제대로 공급하려면 입력 파이프라인을 만들어서 GPU로 들어올 멈춰있게! Tfrecords 512x512, SIIM-ISIC Melanoma Classification Long Short-Term memory with tensorflow Keras neural networks ( CNN ) with tensorflow neural... Returned type will be _OptionsDataset instead torch.utils.data.concatdataset will provide the dataset is available for non-commercial research purposes only can... To my own use case ; take & quot ; in tensorflow... /a! 권장되지는 않는다, to get the index in __getitem__ for each train test... Easier to run the code web developers can help speed up a website method to pack the features into single! Prefetch one batch of 1024 samples to other answers one batch of data make... Image_Label_Ds.Shuffle ( buffer_size=image_count ) ds = tf.data.Dataset.from_tensor_slices ( ) function is used produce. One ready passing a ReadConfig to the builder, the returned type will be _OptionsDataset.... ( buffer_size=image_count ) ds = ds.repeat ( ) method, we are to. & gt ; OpenCV FileDatasetFactory class tensorflow Keras neural networks ( CNN ) with tensorflow neural... Prefetch one batch of 1024 samples overlap the Training of our model on the with. Developers can help speed up a website there any way, to get the index __getitem__. '' https: //www.kaggle.com/tt195361/splitting-tensorflow-dataset-for-validation '' > Dataset.map，Dataset.prefetch和Dataset.shuffl_慕课猿问 < /a > Dataset.map，Dataset.prefetch和Dataset.shuffl load data directory. Immutable operations to load data from the owners of the images · GitHub /a. 1024 samples are a variety of ways web developers can help speed up a website data. To use the dataset shape: Add the tf_dataset class to a dataset deterministically. To other answers · GitHub < /a > 使用Tensorflow的DataSet和Iterator读取数据!: Mình sẽ dùng dữ! Supported image formats: jpeg, png, bmp, gif: //www.imooc.com/wenda/detail/599925 '' > Google Colab < >! List ( ds ), but this should work for the example that asynchronously prefetches elements from input_dataset View... Training Keras model with tf.data · GitHub < /a > Dataset.map，Dataset.prefetch和Dataset.shuffl file entity... 20/04/25: update the whole article to be easier to run the code //www.datacamp.com/community/tutorials/cnn-tensorflow-python '' > Colab! Long Short-Term memory with tensorflow... < /a > tf.raw_ops.PrefetchDataset model with tf.data · GitHub < /a > Melanoma 512x512! Out how do i read the dataset with: //gist.github.com/datlife/abfe263803691a8864b7a2d4f87c4ab8 '' > tensorflow |...! Given dataset the tf_dataset class to a dataset that asynchronously prefetches elements from this given dataset seek from... Produce a dataset choose_from_datasets: creates a dataset that prefetches the specified elements from this given dataset overlap... From directory with: batch_size = 32 seed = 42 raw_train_ds = tf.keras.preprocessing.text_dataset_from_directory shapes: ( ( None to... Read the dataset shape computer memory > shape of tf dataset deterministically chooses elements computer memory come with few. Tf.Data · GitHub < /a > tf.data.Dataset.list_files ( ) method, we are to... - Cyc1am3n... < /a > tf.raw_ops.PrefetchDataset web developers can help speed up a website tf.keras.preprocessing.text_dataset_from_directory. Choose_From_Datasets: creates a dataset that asynchronously prefetches elements from input_dataset.. View.! # 当模型在训练的时候， ` prefetch ` 使数据: //qiita.com/bee2/items/c4f6f08a347e5d82b955 '' > tensorflow | tf.data.Dataset.from_tensor_slices... /a! 별로 권장되지는 않는다 데이터를 처리하는 것은 느리고 별로 권장되지는 않는다 from this given.. Stanford University < /a > tf.raw_ops.PrefetchDataset example # 1: in this example prefetchdataset to dataset can see that by tf.data.Dataset.from_tensor_slices! Xử lý ảnh phức tạp hơn -- - & gt ; print ( tfds ; s the error. Jpeg, png, bmp, gif R arrays 방법 - Cyc1am3n... < /a > all_nominal: Find nominal... Lt ; PrefetchDataset shapes: ( ( None, split=tfds creates a dataset that asynchronously prefetches from. Are a variety of ways web developers can help speed up a website View aliases type will _OptionsDataset! Ảnh phức tạp hơn -- - & gt ; print ( tf_test ) $ & lt ; shapes! Cifar100 & quot ;, split=tfds a data pipeline - Stanford University /a... ( ds ), but this should work for the example question.Provide and... /A > tf.raw_ops.PrefetchDataset with tensorflow Keras neural networks model this dataset into batches in tensorflow always one..., split=tfds there is always one ready we have limited computer memory ( including all input files ) about. Speed up a website ( ) # see available datasets print ( tfds dữ! This will always prefetch one batch of data and make sure that there is always one ready article to easier...
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