AutoGraph reference

Index

Generated code

For each converted function, AutoGraph creates a new function. The loading mechanism is an implementation detail and may change, but the generated function is generally a regular Python function. This function is typically executed internally by @tf.function to construct a TensorFlow graph.

Transformations made to the generated code

The generated code is a transformation of the input code. The transformations are listed below. Any other elements are left unchanged.

Summary of transformations:

• function calls are replaced with a wrapper:
  • foo(args) -> ag__.converted_call(foo, args)
• if, while and for statements are replaced with function calls:
  • if -> ag__.if_stmt
  • while -> ag__.while_stmt
  • for -> ag__.for_stmt
• break, return, and continue statements are replaced with equivalent if statements.
• and, or and not operators are replaced with function calls:
  • and -> ag__.and_
  • or -> ag__.or_
  • not -> ag__.not_

The functions replacing control flow statements are very similar in form with the corresponding control flow ops in TensorFlow.

AutoGraph generates normal Python code

You can interact normally with the generated code. For example, you can use the inspect.getsourcefile and inspect.getsource:

def f(a):
  ...

converted_f = tf.autograph.to_graph(f)
print(inspect.getsourcefile(converted_f))

/tmp/tmpm562wlj7.py

When using @tf.function, you can repeat the same steps using the function's python_function attribute:

@tf.function
def f(a):
  ...

converted_f = tf.autograph.to_graph(f.python_function)
print(inspect.getsourcefile(converted_f))

/tmp/tmpm562wlj7.py

tf.autograph.to_code(f) is a shortcut to obtain the generated code, and it's equivalent with calling inspect.getsource(tf.autograph.to_graph(f)).

Recording diagnostic information: tf.autograph.set_verbosity

AutoGraph can log additional debug information. This is mostly used for filing bugs, but can also be used to get an indication of whether a function is converted successfully or not.

You can enable logging by calling tf.autograph.set_verbosity(level). The level argument varies from 0 to 10:

• 0 - no logging
• 3 - includes the generated code
• 4 and above - extremely verbose logging

Caution: The information being logged includes source code as well as data. Before sharing AutoGraph logs, make sure they don't contain any sensitive information.

Alternatively, you can control the verbosity level using the environment variable AUTOGRAPH_VERBOSITY.