In [4]:

    

import matplotlib.pyplot as plt
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
import sys,os;
%matplotlib inline
sys.path.append("../");
from tf_data import *


    

In [5]:

    

train_dir = '../data/MNIST/';
mnist = input_data.read_data_sets(train_dir, one_hot=True);
noisy_mnist = MNISTData.NoisyLabels(train_dir, percent=0.50);


    

    




Extracting ../data/MNIST/train-images-idx3-ubyte.gz
Extracting ../data/MNIST/train-labels-idx1-ubyte.gz
Extracting ../data/MNIST/t10k-images-idx3-ubyte.gz
Extracting ../data/MNIST/t10k-labels-idx1-ubyte.gz
Extracting ../data/MNIST/train-images-idx3-ubyte.gz
Extracting ../data/MNIST/train-labels-idx1-ubyte.gz
Extracting ../data/MNIST/t10k-images-idx3-ubyte.gz
Extracting ../data/MNIST/t10k-labels-idx1-ubyte.gz

In [6]:

    

[m_x,m_y] = mnist.train.next_batch(batch_size=1000);
[n_x,n_y] = noisy_mnist.train.next_batch(batch_size=1000);
np.sum(1-np.alltrue(np.equal(m_y,n_y),axis=1)) #Result should be around 500


    

    
Out[6]:





491

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