IMPORTANT: AutoGraph is beta software, and under active development. Expect rough edges and bugs, but if you try it, we appreciate early feedback! We'd also love contributions (please see our contributing guidelines and our style guide).
AutoGraph is a Python to TensorFlow compiler.
With AutoGraph, you can write Eager style code in a concise manner, and run it as a TensorFlow graph. AutoGraph uses source code transformation and partial evaluation to generate Python code that builds an equivalent TensorFlow subgraph. The result is code that behaves like ops and can be freely combined with other TensorFlow ops. Please see this file for which parts of the Python language we currently support.
For example, this Python function:
def f(x): if x < 0: x = -x return x
would be converted to this:
def graph_mode_f(x): with tf.name_scope('f'): def if_true(): with tf.name_scope('if_true'): x_1, = x, x_1 = tf.negative(x_1) return x_1, def if_false(): with tf.name_scope('if_false'): x_1, = x, return x_1, x = ag__.utils.run_cond(tf.greater(x, 0), if_true, if_false) return x
so you can use it like an op:
with tf.Graph().as_default(): x = tf.constant(-1.0) converted_f = autograph.to_graph(f) y = converted_f(x) with tf.Session() as sess: print(sess.run(y)) # Output: 1
Use AutoGraph in one of the following ways, described below:
To get started, install the latest nightly TensorFlow build:
pip install -U tf-nightly
Then import the autograph
module from tf.contrib
:
from tensorflow.python import autograph as ag
Articles:
Interactive notebooks:
Annotating a function or class with @convert
converts it in place:
@ag.convert() def f(x): if x < 0: x = -x return x
... so that it always outputs TensorFlow code:
with tf.Graph().as_default(): x = tf.constant(-1) y = f(x) with tf.Session() as sess: print(sess.run(y)) # Output: 1
The functional API allows you to convert an existing function, class or object after it was defined:
converted_f = ag.to_graph(f) print(converted_f(tf.constant(-1))) # Output: Tensor print(f(-1)) # Output: 1
You can use the functional API to inspect the generated code as well:
print(ag.to_code(f)) # Output: <Python and TensorFlow code>
If you’d like AutoGraph to convert a feature of Python or TF that we currently don’t handle, please let us know by filing a bug. We’ll make it as easy as possible to interact with us through there.