Skip to content

GitLab

Commit 35f6f9c9 authored by Neal Wu's avatar Neal Wu Committed by GitHub
Browse files

Merge pull request #1536 from awilliamson/alexnet_lrn 

Implemented LRN for AlexNet tutorial
parents ea2f4704 11733fca
Show whitespace changes
Inline Side-by-side
Showing with 16 additions and 3 deletions
tutorials/image/alexnet/alexnet_benchmark.py
View file @ 35f6f9c9
...@@ -74,10 +74,15 @@ def inference(images): ...@@ -74,10 +74,15 @@ def inference(images):
parameters += [kernel, biases] parameters += [kernel, biases]
# lrn1 # 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
pool1 = tf.nn.max_pool(conv1, pool1 = tf.nn.max_pool(lrn1,
ksize=[1, 3, 3, 1], ksize=[1, 3, 3, 1],
strides=[1, 2, 2, 1], strides=[1, 2, 2, 1],
padding='VALID', padding='VALID',
...@@ -96,8 +101,16 @@ def inference(images): ...@@ -96,8 +101,16 @@ def inference(images):
parameters += [kernel, biases] parameters += [kernel, biases]
print_activations(conv2) 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
pool2 = tf.nn.max_pool(conv2, pool2 = tf.nn.max_pool(lrn2,
ksize=[1, 3, 3, 1], ksize=[1, 3, 3, 1],
strides=[1, 2, 2, 1], strides=[1, 2, 2, 1],
padding='VALID', padding='VALID',
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment