Merge pull request #1536 from awilliamson/alexnet_lrn

Implemented LRN for AlexNet tutorial

tutorials/image/alexnet/alexnet_benchmark.py

@@ -74,10 +74,15 @@ def inference(images):
     parameters += [kernel, biases]
 
   # lrn1
-  # TODO(shlens, jiayq): Add a GPU version of local response normalization.
+  with tf.name_scope('lrn1') as scope:
+    lrn1 = tf.nn.local_response_normalization(conv1,
+                                              alpha=1e-4,
+                                              beta=0.75,
+                                              depth_radius=2,
+                                              bias=2.0)
 
   # pool1
-  pool1 = tf.nn.max_pool(conv1,
+  pool1 = tf.nn.max_pool(lrn1,
                          ksize=[1, 3, 3, 1],
                          strides=[1, 2, 2, 1],
                          padding='VALID',
@@ -96,8 +101,16 @@ def inference(images):
     parameters += [kernel, biases]
   print_activations(conv2)
 
+  # lrn2
+  with tf.name_scope('lrn2') as scope:
+    lrn2 = tf.nn.local_response_normalization(conv2,
+                                              alpha=1e-4,
+                                              beta=0.75,
+                                              depth_radius=2,
+                                              bias=2.0)
+
   # pool2
-  pool2 = tf.nn.max_pool(conv2,
+  pool2 = tf.nn.max_pool(lrn2,
                          ksize=[1, 3, 3, 1],
                          strides=[1, 2, 2, 1],
                          padding='VALID',