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run_autograph.py
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run_autograph.py
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"""
A little fun project that demonstrates how to use tfdbg and TensorBoard Debugger
Plugin with autograph.
For more about autograph, see:
https://medium.com/tensorflow/autograph-converts-python-into-tensorflow-graphs-b2a871f87ec7
For more about TensorBoard Debugger Plugin, see:
https://github.com/tensorflow/tensorboard/tree/master/tensorboard/plugins/debugger/README.md
Requires: TensorFlow 1.9.0+
To use the TensorBoard Debugger Plugin:
1. # First start the TensorBoard binary with the --debugger_port flag, e.g.,
```sh
tensorboard --logdir /tmp/logdir --debugger_port 6064
```
2. Then run this script:
```sh
python run_autograph.py
```
"""
import tensorflow as tf
from tensorflow.contrib import autograph
from tensorflow.python import debug as tf_debug
@autograph.convert()
def collatz(a):
counter = 0
while a != 1:
if a % 2 == 0:
a = a // 2
else:
a = 3 * a + 1
counter += 1
return counter
with tf.Graph().as_default():
a_tensor = tf.constant(1337)
counter_tensor = collatz(a_tensor)
sess = tf.Session()
# Modify me for different debugging modes: 'tensorboard' | 'cli'
debugging_mode = 'tensorboard'
if debugging_mode == 'tensorboard':
sess = tf_debug.TensorBoardDebugWrapperSession(sess, 'localhost:6064')
elif debugging_mode == 'cli':
sess = tf_debug.LocalCLIDebugWrapperSession(sess)
print(sess.run(counter_tensor))