Warning: Please use alternatives such as official/mnist/dataset.py from tensorflow/models

Question

I'm doing a simple tutorial using Tensorflow, I have just installed so it should be updated, first I load the mnist data using the following code:

import numpy as np import os from tensorflow.examples.tutorials.mnist import input_data os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'  mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) train_data = mnist.train.images  # Returns np.array train_labels = np.asarray(mnist.train.labels, dtype=np.int32) eval_data = mnist.test.images  # Returns np.array eval_labels = np.asarray(mnist.test.labels, dtype=np.int32) 

But when I run it I get the following warning:

WARNING:tensorflow:From C:\Users\user\PycharmProjects\TensorFlowRNN\venv\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version. Instructions for updating: Use the retry module or similar alternatives. WARNING:tensorflow:From C:/Users/user/PycharmProjects/TensorFlowRNN/sample.py:5: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use alternatives such as official/mnist/dataset.py from tensorflow/models. WARNING:tensorflow:From C:\Users\user\PycharmProjects\TensorFlowRNN\venv\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:260: maybe_download (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version. Instructions for updating: Please write your own downloading logic. WARNING:tensorflow:From C:\Users\user\PycharmProjects\TensorFlowRNN\venv\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:262: extract_images (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use tf.data to implement this functionality. Extracting MNIST_data/train-images-idx3-ubyte.gz WARNING:tensorflow:From C:\Users\user\PycharmProjects\TensorFlowRNN\venv\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use tf.data to implement this functionality. Extracting MNIST_data/train-labels-idx1-ubyte.gz WARNING:tensorflow:From C:\Users\user\PycharmProjects\TensorFlowRNN\venv\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:110: dense_to_one_hot (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use tf.one_hot on tensors. Extracting MNIST_data/t10k-images-idx3-ubyte.gz Extracting MNIST_data/t10k-labels-idx1-ubyte.gz WARNING:tensorflow:From C:\Users\user\PycharmProjects\TensorFlowRNN\venv\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:290: DataSet.__init__ (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use alternatives such as official/mnist/dataset.py from tensorflow/models. 

I have used the line os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' which should avoid getting warnings and tried other alternatives to obtain mnist, however always appear the same warnings, can someone help me figure out is this happening?

PD: I am using Python 3.6 in windows 10, in case it helps.

Answer 1

tensorflow.examples.tutorials is now deprecated and it is recommended to use tensorflow.keras.datasets as follows:

import tensorflow as tf mnist = tf.keras.datasets.mnist (X_train, y_train), (X_test, y_test) = mnist.load_data() 

https://www.tensorflow.org/api_docs/python/tf/keras/datasets/mnist/load_data

Answer 2

You can use tf.logging module like this:

import numpy as np  import tensorflow as tf old_v = tf.logging.get_verbosity() tf.logging.set_verbosity(tf.logging.ERROR)  from tensorflow.examples.tutorials.mnist import input_data  mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) train_data = mnist.train.images  # Returns np.array train_labels = np.asarray(mnist.train.labels, dtype=np.int32) eval_data = mnist.test.images  # Returns np.array eval_labels = np.asarray(mnist.test.labels, dtype=np.int32)  tf.logging.set_verbosity(old_v)