警告:请使用tensorflow / models中的官方/ mnist / dataset.py等替代方法

时间:2018-04-18 14:04:25

标签: python python-3.x tensorflow

我正在使用Tensorflow做一个简单的教程,我刚刚安装了它应该更新,首先我使用以下代码加载mnist数据:

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)

但是当我运行它时,我收到以下警告:

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.

我使用了行os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3',它应该避免收到警告并尝试其他替代方法来获取mnist,但是总是会出现相同的警告,有人可以帮我弄清楚这是不是会发生?

PD:我在Windows 10中使用Python 3.6,以防它有用。

2 个答案:

答案 0 :(得分:13)

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)

答案 1 :(得分:9)

tensorflow.examples.tutorials现在已被弃用,建议按以下方式使用tensorflow.keras.datasets

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