define functions for expert example

Author: Ryo Miyajima

mnist.py

@@ -29,6 +29,19 @@
 IMAGE_SIZE = 28
 IMAGE_PIXELS = IMAGE_SIZE * IMAGE_SIZE
 
+def weight_variable(shape):
+ initial = tf.truncated_normal(shape, stddev=0.1)
+ return tf.Variable(initial)
+
+def bias_variable(shape):
+ initial = tf.constant(0.1, shape=shape)
+ return tf.Variable(initial)
+
+def conv2d(x, W):
+ return tf.nn.conv2d(x, W, strides=[1,1,1,1], padding='SAME')
+
+def max_pool_2x2(x):
+ return tf.nn.max_pool(x, ksize=[1, 2, 2, 1], strides=[1,2,2,1], padding='SAME')
 
 def inference(images, hidden1_units, hidden2_units):
  """Build the MNIST model up to where it may be used for inference.