mnist_loader.py

# -*- coding: utf-8 -*-
"""
Created on Sat Jul 13 20:40:18 2019

@author: barry
"""

####libraries
# standard library

import pickle
import gzip

#Third-party libraries
import numpy as np

def load_data():
    """return the MNIST data as a tuple containing the training data
    """
    f = gzip.open('./data/mnist.pkl.gz','rb');
    training_data, validation_data, test_data = pickle.load(f,encoding='bytes')
    f.close()
    
    return(training_data, validation_data, test_data)
    
def load_data_wrapper():
    tr_d, va_d, te_d = load_data()
    training_inputs = [np.reshape(x,(784, 1)) for x in tr_d[0]]
    training_results = [vectorized_result(y) for y in tr_d[1]]
    training_data = zip(training_inputs, training_results)
    validation_inputs = [np.reshape(x, (784, 1)) for x in va_d[0]]
    validation_data = zip(validation_inputs, va_d[1])
    test_inputs = [np.reshape(x,(784,1)) for x in te_d[0]]
    test_data = zip(test_inputs, te_d[1])
    return(training_data, validation_data, test_data)
    
def vectorized_result(j):
    e = np.zeros((10,1))
    e[j] = 1.0
    return e