Skip to content

Update 02 - tf.layers.py #30

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jan 10, 2018
Merged

Update 02 - tf.layers.py #30

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions 07 - CNN/02 - tf.layers.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,11 +18,11 @@
# 활성화 함수 적용은 물론, 컨볼루션 신경망을 만들기 위한 나머지 수치들은 알아서 계산해줍니다.
# 특히 Weights 를 계산하는데 xavier_initializer 를 쓰고 있는 등,
# 크게 신경쓰지 않아도 일반적으로 효율적인 신경망을 만들어줍니다.
L1 = tf.layers.conv2d(X, 32, [3, 3])
L1 = tf.layers.conv2d(X, 32, [3, 3], activation=tf.nn.relu)
L1 = tf.layers.max_pooling2d(L1, [2, 2], [2, 2])
L1 = tf.layers.dropout(L1, 0.7, is_training)

L2 = tf.layers.conv2d(L1, 64, [3, 3])
L2 = tf.layers.conv2d(L1, 64, [3, 3], activation=tf.nn.relu)
L2 = tf.layers.max_pooling2d(L2, [2, 2], [2, 2])
L2 = tf.layers.dropout(L2, 0.7, is_training)

Expand Down