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authorGravatar Dan Smilkov <dsmilkov@gmail.com>2016-04-25 07:59:06 -0800
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2016-04-25 09:02:01 -0700
commit379b2eec8edcb1ac575677549ba7c201764f56b5 (patch)
treef98efc7854c2a2ee80d371ca992cf9f603da57e9
parentd5a82c958219acc7d483c8776fe8d5850020993c (diff)
Fix broken links pointing to tensorflow.org/tensorboard/cifar.html
Change: 120711425
-rw-r--r--tensorflow/g3doc/how_tos/graph_viz/index.md6
-rw-r--r--tensorflow/tensorboard/README.md2
2 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/g3doc/how_tos/graph_viz/index.md b/tensorflow/g3doc/how_tos/graph_viz/index.md
index 471cddd406..ec1dc994ac 100644
--- a/tensorflow/g3doc/how_tos/graph_viz/index.md
+++ b/tensorflow/g3doc/how_tos/graph_viz/index.md
@@ -7,10 +7,10 @@ TensorFlow computation graphs are powerful but complicated. The graph visualizat
To see your own graph, run TensorBoard pointing it to the log directory of the job, click on the graph tab on the top pane and select the appropriate run using the menu at the upper left corner. For in depth information on how to run TensorBoard and make sure you are logging all the necessary information, see [TensorBoard: Visualizing Learning](../../how_tos/summaries_and_tensorboard/index.md).
-You can interact with an instance of TensorBoard looking at data from a
-[CIFAR-10](../../tutorials/deep_cnn/index.md) training session, including the
+You can interact with an instance of TensorBoard looking at data from an
+[MNIST](../../tutorials/mnist/beginners/index.md) training session, including the
graph visualization, by clicking
-[here](https://www.tensorflow.org/tensorboard/cifar.html#graphs).
+[here](https://www.tensorflow.org/tensorboard/index.html#graphs).
## Name scoping and nodes
diff --git a/tensorflow/tensorboard/README.md b/tensorflow/tensorboard/README.md
index 28c0d3ee6a..a88f5e4d02 100644
--- a/tensorflow/tensorboard/README.md
+++ b/tensorflow/tensorboard/README.md
@@ -5,7 +5,7 @@ TensorFlow runs and graphs. TensorBoard currently supports four visualizations:
scalars, images, histograms, and the graph.
You can play with an interactive demo TensorBoard at
-[tensorflow.org/tensorboard/cifar.html](https://www.tensorflow.org/tensorboard/cifar.html).
+[tensorflow.org/tensorboard/](https://www.tensorflow.org/tensorboard/).
This README gives an overview of key concepts in TensorBoard, as well as how to
interpret the visualizations TensorBoard provides. For an in-depth example of