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The following commit(s) were added to refs/heads/master by this push:
new 075120e Fix infoGan Gluon tutorial errors. (#13416)
075120e is described below
commit 075120ebb892341bb39c5962e17abc5e8e7b9733
Author: Vishaal Kapoor <[email protected]>
AuthorDate: Tue Nov 27 03:03:18 2018 -0800
Fix infoGan Gluon tutorial errors. (#13416)
- Update notebook to avoid divide by 0 causing a warning.
- Add MXBoard dependency.
---
ci/docker/install/ubuntu_tutorials.sh | 4 ++--
docs/tutorials/gluon/info_gan.md | 8 ++++----
2 files changed, 6 insertions(+), 6 deletions(-)
diff --git a/ci/docker/install/ubuntu_tutorials.sh
b/ci/docker/install/ubuntu_tutorials.sh
index 9877475..404d4bb 100755
--- a/ci/docker/install/ubuntu_tutorials.sh
+++ b/ci/docker/install/ubuntu_tutorials.sh
@@ -23,5 +23,5 @@
set -ex
apt-get update || true
apt-get install graphviz python-opencv
-pip2 install jupyter matplotlib Pillow opencv-python scikit-learn graphviz tqdm
-pip3 install jupyter matplotlib Pillow opencv-python scikit-learn graphviz tqdm
+pip2 install jupyter matplotlib Pillow opencv-python scikit-learn graphviz
tqdm mxboard
+pip3 install jupyter matplotlib Pillow opencv-python scikit-learn graphviz
tqdm mxboard
diff --git a/docs/tutorials/gluon/info_gan.md b/docs/tutorials/gluon/info_gan.md
index c8f07c6..8b2668a 100644
--- a/docs/tutorials/gluon/info_gan.md
+++ b/docs/tutorials/gluon/info_gan.md
@@ -311,18 +311,18 @@ with SummaryWriter(logdir='./logs/') as sw:
# logging
if idx % 10 == 0:
-
+ count = idx + 1
logging.info('speed: {} samples/s'.format(batch_size /
(time.time() - starttime)))
logging.info('discriminator loss = %f, generator loss = %f at
iter %d epoch %d'
-
%(d_error_epoch.asscalar()/idx,g_error_epoch.asscalar()/idx, idx, epoch))
+
%(d_error_epoch.asscalar()/count,g_error_epoch.asscalar()/count, count, epoch))
g_input,_,_ = create_generator_input()
# create some fake image for logging in MXBoard
fake_image = generator(g_input)
- sw.add_scalar(tag='Loss_D',
value={'test':d_error_epoch.asscalar()/idx}, global_step=counter)
- sw.add_scalar(tag='Loss_G',
value={'test':d_error_epoch.asscalar()/idx}, global_step=counter)
+ sw.add_scalar(tag='Loss_D',
value={'test':d_error_epoch.asscalar()/count}, global_step=counter)
+ sw.add_scalar(tag='Loss_G',
value={'test':d_error_epoch.asscalar()/count}, global_step=counter)
sw.add_image(tag='data_image', image=((fake_image[0]+ 1.0) *
127.5).astype(np.uint8) , global_step=counter)
sw.flush()
