utils.py

import tensorflow as tf
import os
import gzip
import numpy as np
def leaky_relu(x, alpha=.2):
  return tf.nn.relu(x) - alpha * tf.nn.relu(-x)



def load_mnist(path, kind='train'):


    """Load MNIST data from `path`"""
    labels_path = os.path.join(path,
                               '%s-labels-idx1-ubyte.gz'
                               % kind)
    images_path = os.path.join(path,
                               '%s-images-idx3-ubyte.gz'
                               % kind)

    with gzip.open(labels_path, 'rb') as lbpath:
        labels = np.frombuffer(lbpath.read(), dtype=np.uint8,
                               offset=8)

    with gzip.open(images_path, 'rb') as imgpath:
        images = np.frombuffer(imgpath.read(), dtype=np.uint8,
                               offset=16).reshape(len(labels), 784)

    return images, labels

def inverse_transform(images):
    return (images+1.)/2.