Add python script that can visualize models by producing an HTML page.

PiperOrigin-RevId: 181756421

1 files changed, 7 insertions, 1 deletions

diff --git a/tensorflow/contrib/lite/README.md b/tensorflow/contrib/lite/README.md
index 852284cbc7..55a524b207 100644
--- a/tensorflow/contrib/lite/README.md
+++ b/tensorflow/contrib/lite/README.md
@@ -188,7 +188,7 @@ bazel-bin/tensorflow/contrib/lite/toco/toco -- \
 Note, it is also possible to use the Tensorflow Optimizing Converter through protos either from Python or from the command line see the
 documentation [here](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/toco/python/toco_from_protos.py). A developer can then integrate the conversion step into their model design workflow to ensure that a model will be easily convertible to a mobile inference graph. For example,
 
-```
+```python
 import tensorflow as tf
 
 img = tf.placeholder(name="img", dtype=tf.float32, shape=(1, 64, 64, 3))
@@ -203,6 +203,12 @@ For detailed instructions on how to use the Tensorflow Optimizing Converter, ple
 
 You may refer to the [Ops compatibility guide](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/g3doc/tf_ops_compatibility.md) for troubleshooting help. If that doesn't help, please file an [issue](https://github.com/tensorflow/tensorflow/issues).
 
+If you would like to see a visual description of your TensorFlow Lite model after conversion, you can use tensorflow/contrib/lite/tools/visualize.py by running
+```sh
+bazel run tensorflow/contrib/lite/tools:visualize -- model.tflite model_viz.html
+```
+and then visualize the resulting HTML file in a browser.
+
 ## Step 3. Use the TensorFlow Lite model for inference in a mobile app
 
 After completion of Step 2 the developer should have a .lite model.