def _rename_compilable_function(self, node):
assert anno.hasanno(node.func, 'live_val')
assert anno.hasanno(node.func, 'fqn')
target_entity = anno.getanno(node.func, 'live_val')
target_fqn = anno.getanno(node.func, 'fqn')
if anno.hasanno(node, 'is_constructor'):
new_name = self.ctx.namer.compiled_class_name(
target_fqn, live_entity=target_entity)
do_rename = True
else:
if anno.hasanno(node.func, 'parent_type'):
owner_type = anno.getanno(node.func, 'parent_type')
else:
# Fallback - not reliable.
owner_type = inspect_utils.getmethodclass(target_entity)
new_name, do_rename = self.ctx.namer.compiled_function_name(
target_fqn, live_entity=target_entity, owner_type=owner_type)
if do_rename:
if target_entity is not None:
if tf_inspect.ismethod(target_entity):
# The renaming process will transform it into a regular function.
# TODO(mdan): Is this complete? How does it work with nested members?
node.args = [node.func.value] + node.args
node.func = templates.replace_as_expression(
'func_name', func_name=new_name)
return node
def test_getmethodclass_callables(self):
class TestCallable(object):
def __call__(self):
pass
c = TestCallable()
self.assertEqual(inspect_utils.getmethodclass(c), TestCallable)
def test_getmethodclass_callables(self):
class TestCallable(object):
def __call__(self):
pass
c = TestCallable()
self.assertEqual(inspect_utils.getmethodclass(c), TestCallable)
def test_getmethodclass_locals(self):
def local_function():
pass
class LocalClass(object):
def member_function(self):
pass
@decorator
def decorated_member(self):
pass
@function_decorator()
def fn_decorated_member(self):
pass
@wrapping_decorator()
def wrap_decorated_member(self):
pass
self.assertEqual(
inspect_utils.getmethodclass(local_function), None)
self.assertEqual(
inspect_utils.getmethodclass(LocalClass.member_function),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(LocalClass.decorated_member),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(LocalClass.fn_decorated_member),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(LocalClass.wrap_decorated_member),
LocalClass)
test_obj = LocalClass()
self.assertEqual(
inspect_utils.getmethodclass(test_obj.member_function),
test_obj)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.decorated_member),
test_obj)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.fn_decorated_member),
test_obj)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.wrap_decorated_member),
test_obj)
def test_getmethodclass_locals(self):
def local_function():
pass
class LocalClass(object):
def member_function(self):
pass
@decorator
def decorated_member(self):
pass
@function_decorator()
def fn_decorated_member(self):
pass
@wrapping_decorator()
def wrap_decorated_member(self):
pass
self.assertEqual(
inspect_utils.getmethodclass(local_function), None)
self.assertEqual(
inspect_utils.getmethodclass(LocalClass.member_function),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(LocalClass.decorated_member),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(LocalClass.fn_decorated_member),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(LocalClass.wrap_decorated_member),
LocalClass)
test_obj = LocalClass()
self.assertEqual(
inspect_utils.getmethodclass(test_obj.member_function),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.decorated_member),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.fn_decorated_member),
LocalClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.wrap_decorated_member),
LocalClass)
def test_getmethodclass_weakref_mechanism(self):
test_obj = TestClass()
def test_fn(self):
return self
bound_method = types.MethodType(
test_fn,
function.TfMethodTarget(weakref.ref(test_obj),
test_obj.member_function))
self.assertEqual(inspect_utils.getmethodclass(bound_method), TestClass)
def test_getmethodclass_weakref_mechanism(self):
test_obj = TestClass()
def test_fn(self):
return self
bound_method = types.MethodType(
test_fn,
function.TfMethodTarget(
weakref.ref(test_obj), test_obj.member_function))
self.assertEqual(inspect_utils.getmethodclass(bound_method), TestClass)
def test_getmethodclass_weakref_mechanism(self):
test_obj = TestClass()
class WeakrefWrapper(object):
def __init__(self):
self.ag_self_weakref__ = weakref.ref(test_obj)
def test_fn(self):
return self
bound_method = types.MethodType(test_fn, WeakrefWrapper())
self.assertEqual(inspect_utils.getmethodclass(bound_method), TestClass)
def test_getmethodclass_weakref_mechanism(self):
test_obj = TestClass()
class WeakrefWrapper(object):
def __init__(self):
self.ag_self_weakref__ = weakref.ref(test_obj)
def test_fn(self):
return self
bound_method = types.MethodType(test_fn, WeakrefWrapper())
self.assertEqual(inspect_utils.getmethodclass(bound_method), test_obj)
def converted_call(f, owner, options, *args, **kwargs):
"""Compiles a function call inline. For internal use only."""
if owner is not None:
if not isinstance(f, str):
raise ValueError(
'When owner is specified, the function name must be specified as'
' a string: {}'.format(f))
# Special case when the owner is a 'super' object. In that case lookups of
# dynamic attributes won't work. See
# inspect_utils.SuperWrapperForDynamicAttrs.
if isinstance(owner, super):
owner = inspect_utils.SuperWrapperForDynamicAttrs(owner)
f = getattr(owner, f)
# TODO(mdan): This needs cleanup.
# In particular, we may want to avoid renaming functions altogether.
if not options.force_conversion and conversion.is_whitelisted_for_graph(f):
return f(*args, **kwargs)
unknown_arg_value = object() # Sentinel for arguments of unknown value
if inspect_utils.isbuiltin(f):
return py_builtins.overload_of(f)(*args, **kwargs)
if tf_inspect.isfunction(f) or tf_inspect.ismethod(f):
# Regular functions
target_entity = f
arg_map_target = f
f_class = inspect_utils.getmethodclass(f)
if f_class is not None:
# If this is a method call, it may or may not include self.
#
# Example when self is included:
# converted_call(to_graph(foo.bar), foo)
#
# Example when self is not included:
# super(...).foo(args)
#
if owner is not None and (not args or args[0] is not owner):
effective_args = (owner,) + args
else:
effective_args = args
partial_types = (f_class,)
else:
effective_args = args
partial_types = ()
elif tf_inspect.isclass(f):
# Constructors
target_entity = f
arg_map_target = f.__init__
effective_args = args
partial_types = ()
elif hasattr(f, '__call__') and hasattr(f, '__class__'):
# Callable objects
target_entity = f.__call__
arg_map_target = f.__call__
effective_args = (f,) + args
partial_types = (f.__class__,)
else:
NotImplementedError('unknown callable type "%s"' % type(f))
arg_values = tf_inspect.getcallargs(arg_map_target, *args, **kwargs)
arg_types = {}
for name, arg in arg_values.items():
if arg is unknown_arg_value:
continue
arg_class = arg.__class__
arg_types[name] = (arg_class.__name__, arg_class)
# When called from within a decorator, this is the only indication that
# the function is a method - it appears that the decorator is applied
# before the method is bound.
if not partial_types:
if 'self' in arg_values:
if tf_inspect.isclass(arg_values['self'].__class__):
partial_types = (arg_values['self'].__class__,)
elif 'cls' in arg_values:
if tf_inspect.isclass(arg_values['cls']):
partial_types = (arg_values['cls'],)
converted_f = to_graph(
target_entity,
recursive=options.recursive,
verbose=options.verbose,
arg_values=arg_values,
arg_types=arg_types,
partial_types=partial_types,
strip_decorators=options.strip_decorators)
return converted_f(*effective_args, **kwargs)
def test_getmethodclass(self):
self.assertEqual(
inspect_utils.getmethodclass(free_function), None)
self.assertEqual(
inspect_utils.getmethodclass(free_factory()), None)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.member_function),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.fn_decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.wrap_decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.static_method),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.class_method),
TestClass)
test_obj = TestClass()
self.assertEqual(
inspect_utils.getmethodclass(test_obj.member_function),
test_obj)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.decorated_member),
test_obj)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.fn_decorated_member),
test_obj)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.wrap_decorated_member),
test_obj)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.static_method),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.class_method),
TestClass)
def test_getmethodclass_no_bool_conversion(self):
tensor = constant_op.constant([1])
self.assertEqual(inspect_utils.getmethodclass(tensor.get_shape),
type(tensor))
def is_whitelisted_for_graph(o):
"""Checks whether an entity is whitelisted for use in graph mode.
Examples of whitelisted entities include all members of the tensorflow
package.
Args:
o: A Python entity.
Returns:
Boolean
"""
# TODO(b/120224672): Fix this.
if isinstance(o, functools.partial):
# tf_inspect.getmodule(functools.partial(...)) otherwise returns None since
# functools.partial objects do not have a __module__ attribute.
m = functools
else:
m = tf_inspect.getmodule(o)
if hasattr(m, '__name__'):
# Builtins typically have unnamed modules.
for prefix, in config.DEFAULT_UNCOMPILED_MODULES:
if m.__name__.startswith(prefix):
logging.log(2, 'Whitelisted: %s: name starts with "%s"', o, prefix)
return True
# Temporary -- whitelist tensorboard modules.
# TODO(b/122731813): Remove.
if m.__name__ == 'tensorboard' or '.tensorboard' in m.__name__:
logging.log(2, 'Whitelisted: %s: name contains "tensorboard"', o)
return True
if hasattr(o, 'autograph_info__') or hasattr(o, '__ag_compiled'):
logging.log(2, 'Whitelisted: %s: already converted', o)
return True
if tf_inspect.isgeneratorfunction(o):
logging.warn(
'Entity {} appears to be a generator function. It will not be converted'
' by AutoGraph.'.format(o), 1)
logging.log(2, 'Whitelisted: %s: generator functions are not converted', o)
return True
if hasattr(o, '__call__'):
# Callable objects: whitelisted if their __call__ method is.
# The type check avoids infinite recursion around the __call__ method
# of function objects.
if (type(o) != type(o.__call__)) and is_whitelisted_for_graph(o.__call__): # pylint: disable=unidiomatic-typecheck
logging.log(2, 'Whitelisted: %s: object __call__ whitelisted', o)
return True
owner_class = None
if tf_inspect.ismethod(o):
# Methods of whitelisted classes are also whitelisted, even if they are
# bound via user subclasses.
#
# For example, suppose `tf.Foo` has a method called `bar`, and `baz` is
# defined as below. `tf.Foo` is whitelisted. Then `baz.bar` is also
# whitelisted.
#
# class Custom(tf.Foo):
# pass
#
# baz = Custom()
#
# For the example above, if `Custom` did overload `bar`, then it would no
# longer be whitelisted.
owner_class = inspect_utils.getmethodclass(o)
if owner_class is not None:
if issubclass(owner_class, unittest.TestCase):
logging.log(2, 'Whitelisted: %s: method of TestCase subclass', o)
return True
owner_class = inspect_utils.getdefiningclass(o, owner_class)
if is_whitelisted_for_graph(owner_class):
logging.log(2, 'Whitelisted: %s: owner is whitelisted %s', o,
owner_class)
return True
if inspect_utils.isnamedtuple(o):
# Due to the way they're constructed, namedtuple types cannot be converted
# because they don't expose source code. But we assume they are safe for
# graph mode since they are just containers.
if tf_inspect.isclass(o) and len(o.__bases__) > 1:
logging.warn(
'Entity {} looks like a namedtuple subclass. Its constructor will'
' not be converted by AutoGraph, but if it has any custom methods,'
' those will be.'.format(o), 1)
logging.log(2, 'Whitelisted: %s: named tuple', o)
return True
logging.log(2, 'Not whitelisted: %s: default rule', o)
return False
def converted_call(f, owner, options, *args, **kwargs):
"""Compiles a function call inline. For internal use only."""
logging.vlog(logging.DEBUG, 'Converted call: %s; owner: %s', f, owner)
if owner is not None:
if not isinstance(f, str):
raise ValueError(
'When owner is specified, the function name must be specified as'
' a string: {}'.format(f))
# Special case when the owner is a 'super' object. In that case lookups of
# dynamic attributes won't work. See
# inspect_utils.SuperWrapperForDynamicAttrs.
if isinstance(owner, super):
owner = inspect_utils.SuperWrapperForDynamicAttrs(owner)
f = getattr(owner, f)
if inspect_utils.isbuiltin(f):
return py_builtins.overload_of(f)(*args, **kwargs)
# TODO(mdan): This needs cleanup.
# In particular, we may want to avoid renaming functions altogether.
if not options.force_conversion and conversion.is_whitelisted_for_graph(f):
# Args typically include `self`, as required by the conversion process.
# When conversion is skipped, `self` is not necessary, because the
# original bound method is being executed. This code removes it.
if tf_inspect.ismethod(f) and args:
f_class = inspect_utils.getmethodclass(f)
if args[0] is f_class:
args = args[1:]
return f(*args, **kwargs)
# internal_convert_user_code is for example turned off when issuing a dynamic
# call conversion from generated code while in nonrecursive mode. In that
# case we evidently don't want to recurse, but we still have to convert
# things like builtins.
if not options.internal_convert_user_code:
return f(*args, **kwargs)
# Unwrap functools.partial objects
# TODO(mdan): Consider sharing unwrapping logic with tf_inspect.
while isinstance(f, functools.partial):
args = f.args + args
new_kwargs = {}
if f.keywords is not None:
new_kwargs.update(f.keywords)
new_kwargs.update(kwargs)
kwargs = new_kwargs
f = f.func
if tf_inspect.isfunction(f) or tf_inspect.ismethod(f):
# Regular functions
target_entity = f
arg_map_target = f
f_class = inspect_utils.getmethodclass(f)
# TODO(b/119246461): This may be more elegantly handled using __get__?
if f_class is not None:
# If this is a method call, it may or may not include self.
#
# Example when self is included:
# converted_call(to_graph(foo.bar), foo)
#
# Example when self is not included:
# super(...).foo(args)
#
if owner is not None and (not args or args[0] is not owner):
effective_args = (owner, ) + args
else:
# When the owner is not specified, use the result of
# inspect_utils.getmethodclass.
# TODO(b/119246461): Make sure an owner is always specified.
if not args or args[0] is not f_class:
effective_args = (f_class, ) + args
else:
effective_args = (f_class, ) + args[1:]
partial_types = (f_class, )
else:
effective_args = args
partial_types = ()
elif tf_inspect.isclass(f):
# Constructors
target_entity = f
arg_map_target = f.__init__
effective_args = args
partial_types = ()
elif hasattr(f, '__call__') and hasattr(f, '__class__'):
# Callable objects
target_entity = f.__call__
arg_map_target = f.__call__
effective_args = (f, ) + args
partial_types = (f.__class__, )
else:
NotImplementedError('unknown callable type "%s"' % type(f))
arg_values = tf_inspect.getcallargs(arg_map_target, *args, **kwargs)
arg_types = {}
for name, arg in arg_values.items():
arg_class = arg.__class__
arg_types[name] = (arg_class.__name__, arg_class)
# When called from within a decorator, this is the only indication that
# the function is a method - it appears that the decorator is applied
# before the method is bound.
if not partial_types:
if 'self' in arg_values:
if tf_inspect.isclass(arg_values['self'].__class__):
partial_types = (arg_values['self'].__class__, )
elif 'cls' in arg_values:
if tf_inspect.isclass(arg_values['cls']):
partial_types = (arg_values['cls'], )
converted_f = to_graph(
target_entity,
recursive=options.recursive,
arg_values=arg_values,
arg_types=arg_types,
experimental_optional_features=options.optional_features,
experimental_strip_decorators=options.strip_decorators,
experimental_verbose=options.verbose,
experimental_partial_types=partial_types)
result = converted_f(*effective_args, **kwargs)
# The converted function's closure is simply inserted into the function's
# module __dict__. Since modules are permanently cached, that results in
# leaking the entire closure.
# Normally, it's not safe to delete the module because that may release said
# closure as well. However, in the case of converted_call we are certain the
# function will not be executed again, so the closure should no longer be
# needed so long as the function doesn't return any executable code.
# TODO(mdan): Attach the closure properly, using cells.
if all(map(_is_not_callable, nest.flatten(result))):
del sys.modules[converted_f.__module__]
return result
def test_getmethodclass(self):
self.assertEqual(
inspect_utils.getmethodclass(free_function), None)
self.assertEqual(
inspect_utils.getmethodclass(free_factory()), None)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.member_function),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.fn_decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.wrap_decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.static_method),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(TestClass.class_method),
TestClass)
test_obj = TestClass()
self.assertEqual(
inspect_utils.getmethodclass(test_obj.member_function),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.fn_decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.wrap_decorated_member),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.static_method),
TestClass)
self.assertEqual(
inspect_utils.getmethodclass(test_obj.class_method),
TestClass)
def converted_call(f, recursive, verbose, force_conversion, arg_types, *args,
**kwargs):
"""Compiles a function call inline. For internal use only."""
# TODO(mdan): This needs cleanup.
# In particular, we may want to avoid renaming functions altogether.
if not force_conversion and conversion.is_whitelisted_for_graph(f):
return f(*args, **kwargs)
unknown_arg_value = object() # Sentinel for arguments of unknown value
if inspect_utils.isbuiltin(f):
return py_builtins.overload_of(f)(*args, **kwargs)
if tf_inspect.isfunction(f) or tf_inspect.ismethod(f):
# Regular functions
target_entity = f
arg_map_target = f
effective_args = args
f_class = inspect_utils.getmethodclass(f)
if f_class is not None:
partial_types = (f_class,)
else:
partial_types = ()
elif tf_inspect.isclass(f):
# Constructors
target_entity = f
arg_map_target = f.__init__
effective_args = args
partial_types = ()
elif hasattr(f, '__call__') and hasattr(f, '__class__'):
# Callable objects
target_entity = f.__call__
arg_map_target = f.__call__
effective_args = (f,) + args
partial_types = (f.__class__,)
else:
NotImplementedError('unknown callable type "%s"' % type(f))
arg_values = tf_inspect.getcallargs(arg_map_target, *args, **kwargs)
for name, arg in arg_values.items():
if arg is unknown_arg_value:
continue
arg_class = arg.__class__
# If arg_value_hints specifies any name, use that instead.
if name not in arg_types:
arg_types[name] = (arg_class.__name__, arg_class)
# When called from within a decorator, this is the only indication that
# the function is a method - it appears that the decorator is applied
# before the method is bound.
if not partial_types:
if 'self' in arg_values:
if tf_inspect.isclass(arg_values['self'].__class__):
partial_types = (arg_values['self'].__class__,)
elif 'cls' in arg_values:
if tf_inspect.isclass(arg_values['cls']):
partial_types = (arg_values['cls'],)
converted_f = to_graph(
target_entity,
recursive=recursive,
verbose=verbose,
arg_values=arg_values,
arg_types=arg_types,
partial_types=partial_types)
return converted_f(*effective_args, **kwargs)
def test_getmethodclass_no_bool_conversion(self):
tensor = constant_op.constant([1])
self.assertEqual(inspect_utils.getmethodclass(tensor.get_shape), tensor)
def is_whitelisted(o,
check_call_override=True,
allow_namedtuple_subclass=False):
"""Checks whether an entity is whitelisted for use in graph mode.
Examples of whitelisted entities include all members of the tensorflow
package.
Args:
o: A Python entity.
check_call_override: Reserved for internal use. When set to `False`, it
disables the rule according to which classes are whitelisted if their
__call__ method is whitelisted.
allow_namedtuple_subclass: Reserved for internal use. When `True`,
namedtuple subclasses are not whitelisted.
Returns:
Boolean
"""
# TODO(b/120224672): Fix this.
if isinstance(o, functools.partial):
# tf_inspect.getmodule(functools.partial(...)) otherwise returns None since
# functools.partial objects do not have a __module__ attribute.
m = functools
else:
m = tf_inspect.getmodule(o)
# Examples of callables that lack a __module__ property include builtins.
if hasattr(m, '__name__'):
for rule in config.CONVERSION_RULES:
action = rule.get_action(m)
if action == config.Action.CONVERT:
logging.log(2, 'Not whitelisted: %s: %s', o, rule)
return False
elif action == config.Action.DO_NOT_CONVERT:
logging.log(2, 'Whitelisted: %s: %s', o, rule)
return True
if tf_inspect.isgeneratorfunction(o):
logging.warn(
'Entity %s appears to be a generator function. It will not be converted'
' by AutoGraph.', o)
logging.log(2,
'Whitelisted: %s: generator functions are not converted',
o)
return True
if (check_call_override and not tf_inspect.isclass(o)
and hasattr(o, '__call__')):
# Callable objects: whitelisted if their __call__ method is.
# The type check avoids infinite recursion around the __call__ method
# of function objects.
if (type(o) != type(o.__call__)) and is_whitelisted(o.__call__): # pylint: disable=unidiomatic-typecheck
logging.log(2, 'Whitelisted: %s: object __call__ whitelisted', o)
return True
owner_class = None
if tf_inspect.ismethod(o):
# Methods of whitelisted classes are also whitelisted, even if they are
# bound via user subclasses.
#
# For example, suppose `tf.Foo` has a method called `bar`, and `baz` is
# defined as below. `tf.Foo` is whitelisted. Then `baz.bar` is also
# whitelisted.
#
# class Custom(tf.Foo):
# pass
#
# baz = Custom()
#
# For the example above, if `Custom` did overload `bar`, then it would no
# longer be whitelisted.
owner_class = inspect_utils.getmethodclass(o)
if owner_class is function.TfMethodTarget:
owner_class = o.__self__.target_class
if owner_class is not None:
if issubclass(owner_class, unittest.TestCase):
logging.log(2, 'Whitelisted: %s: method of TestCase subclass',
o)
return True
owner_class = inspect_utils.getdefiningclass(o, owner_class)
if is_whitelisted(owner_class,
check_call_override=False,
allow_namedtuple_subclass=True):
logging.log(2, 'Whitelisted: %s: owner is whitelisted %s', o,
owner_class)
return True
if inspect_utils.isnamedtuple(o):
# Due to the way they're constructed, namedtuple types cannot be converted
# because they don't expose source code. But we assume they are safe for
# graph mode since they are just containers.
if allow_namedtuple_subclass:
if not any(
inspect_utils.isnamedtuple(base) for base in o.__bases__):
logging.log(2, 'Whitelisted: %s: named tuple', o)
return True
else:
logging.log(2, 'Whitelisted: %s: named tuple or subclass', o)
return True
logging.log(2, 'Not whitelisted: %s: default rule', o)
return False
def converted_call(f, owner, options, *args, **kwargs):
"""Compiles a function call inline. For internal use only."""
if options.verbose >= converter.Verbosity.VERBOSE:
logging.info('Converted call: {}; owner: {}'.format(f, owner))
if owner is not None:
if not isinstance(f, str):
raise ValueError(
'When owner is specified, the function name must be specified as'
' a string: {}'.format(f))
# Special case when the owner is a 'super' object. In that case lookups of
# dynamic attributes won't work. See
# inspect_utils.SuperWrapperForDynamicAttrs.
if isinstance(owner, super):
owner = inspect_utils.SuperWrapperForDynamicAttrs(owner)
f = getattr(owner, f)
if inspect_utils.isbuiltin(f):
return py_builtins.overload_of(f)(*args, **kwargs)
# TODO(mdan): This needs cleanup.
# In particular, we may want to avoid renaming functions altogether.
if not options.force_conversion and conversion.is_whitelisted_for_graph(f):
# Args typically include `self`, as required by the conversion process.
# When conversion is skipped, `self` is not necessary, because the
# original bound method is being executed. This code removes it.
if tf_inspect.ismethod(f) and args:
f_class = inspect_utils.getmethodclass(f)
if args[0] is f_class:
args = args[1:]
return f(*args, **kwargs)
# internal_convert_user_code is for example turned off when issuing a dynamic
# call conversion from generated code while in nonrecursive mode. In that
# case we evidently don't want to recurse, but we still have to convert
# things like builtins.
if not options.internal_convert_user_code:
return f(*args, **kwargs)
# Unwrap functools.partial objects
# TODO(allenl, mdan): Consider sharing unwrapping logic with tf_inspect.
while isinstance(f, functools.partial):
args = f.args + args
new_kwargs = {}
if f.keywords is not None:
new_kwargs.update(f.keywords)
new_kwargs.update(kwargs)
kwargs = new_kwargs
f = f.func
if tf_inspect.isfunction(f) or tf_inspect.ismethod(f):
# Regular functions
target_entity = f
arg_map_target = f
f_class = inspect_utils.getmethodclass(f)
# TODO(b/119246461): This may be more elegantly handled using __get__?
if f_class is not None:
# If this is a method call, it may or may not include self.
#
# Example when self is included:
# converted_call(to_graph(foo.bar), foo)
#
# Example when self is not included:
# super(...).foo(args)
#
if owner is not None and (not args or args[0] is not owner):
effective_args = (owner,) + args
else:
# When the owner is not specified, use the result of
# inspect_utils.getmethodclass.
# TODO(b/119246461): Make sure an owner is always specified.
if not args or args[0] is not f_class:
effective_args = (f_class,) + args
else:
effective_args = (f_class,) + args[1:]
partial_types = (f_class,)
else:
effective_args = args
partial_types = ()
elif tf_inspect.isclass(f):
# Constructors
target_entity = f
arg_map_target = f.__init__
effective_args = args
partial_types = ()
elif hasattr(f, '__call__') and hasattr(f, '__class__'):
# Callable objects
target_entity = f.__call__
arg_map_target = f.__call__
effective_args = (f,) + args
partial_types = (f.__class__,)
else:
NotImplementedError('unknown callable type "%s"' % type(f))
arg_values = tf_inspect.getcallargs(arg_map_target, *args, **kwargs)
arg_types = {}
for name, arg in arg_values.items():
arg_class = arg.__class__
arg_types[name] = (arg_class.__name__, arg_class)
# When called from within a decorator, this is the only indication that
# the function is a method - it appears that the decorator is applied
# before the method is bound.
if not partial_types:
if 'self' in arg_values:
if tf_inspect.isclass(arg_values['self'].__class__):
partial_types = (arg_values['self'].__class__,)
elif 'cls' in arg_values:
if tf_inspect.isclass(arg_values['cls']):
partial_types = (arg_values['cls'],)
converted_f = to_graph(
target_entity,
recursive=options.recursive,
verbose=options.verbose,
arg_values=arg_values,
arg_types=arg_types,
partial_types=partial_types,
strip_decorators=options.strip_decorators,
optional_features=options.optional_features)
result = converted_f(*effective_args, **kwargs)
# The converted function's closure is simply inserted into the function's
# module __dict__. Since modules are permanently cached, that results in
# leaking the entire closure.
# Normally, it's not safe to delete the module because that may release said
# closure as well. However, in the case of converted_call we are certain the
# function will not be executed again, so the closure should no longer be
# needed so long as the function doesn't return any executable code.
# TODO(mdan): Attach the closure properly, using cells.
if all(map(_is_not_callable, nest.flatten(result))):
del sys.modules[converted_f.__module__]
return result
def is_whitelisted_for_graph(o):
"""Check whether an entity is whitelisted for use in graph mode.
Examples of whitelisted entities include all members of the tensorflow
package.
Args:
o: A Python entity.
Returns:
Boolean
"""
# TODO(b/120224672): Fix this.
if isinstance(o, functools.partial):
# tf_inspect.getmodule(functools.partial(...)) otherwise returns None since
# functools.partial objects do not have a __module__ attribute.
m = functools
else:
m = tf_inspect.getmodule(o)
if not hasattr(m, '__name__'):
# Note: typically it's builtins that fall in this category. Builtins will
# be handled by specific code that follows this screening layer.
logging.log(2, '%s is NOT whitelisted: unknown module name', o)
return False
for prefix, in config.DEFAULT_UNCOMPILED_MODULES:
if m.__name__.startswith(prefix):
logging.log(2, '%s is whitelisted: name starts with "%s"', o,
prefix)
return True
if hasattr(o, 'autograph_info__') or hasattr(o, '__ag_compiled'):
logging.log(2, '%s is whitelisted: already converted', o)
return True
if (not inspect_utils.isweakrefself(o) and not tf_inspect.isclass(o)
and hasattr(o, '__call__') and hasattr(o, '__class__')):
# Callable objects: whitelisted if their __call__ method is.
call_whitelisted = is_whitelisted_for_graph(o.__call__)
if call_whitelisted:
logging.log(2, '%s is whitelisted: object __call__ whitelisted', o)
return call_whitelisted
if tf_inspect.ismethod(o):
# Methods of whitelisted classes are also whitelisted, even if they are
# bound via user subclasses.
#
# For example, suppose `tf.Foo` has a method called `bar`, and `baz` is
# defined as below. `tf.Foo` is whitelisted. Then `baz.bar` is also
# whitelisted.
#
# class Custom(tf.Foo):
# pass
#
# baz = Custom()
#
# For the example above, if `Custom` did overload `bar`, then it would no
# longer be whitelisted.
owner_class = inspect_utils.getmethodclass(o)
if owner_class is not None:
owner_class = inspect_utils.getdefiningclass(o, owner_class)
if is_whitelisted_for_graph(owner_class):
logging.log(2, '%s is whitelisted: owner is whitelisted %s', o,
owner_class)
return True
if inspect_utils.isnamedtuple(o):
# Due to the way they're constructed, namedtuple types cannot be converted
# because they don't expose source code. But we assume they are safe for
# graph mode since they are just containers.
if tf_inspect.isclass(o) and len(o.__bases__) > 1:
logging.warn_first_n(
'Entity {} looks like a namedtuple subclass. If it has any custom'
' methods, they will not be converted by AutoGraph.'.format(o),
1)
logging.log(2, '%s is whitelisted: named tuple', o)
return True
logging.log(2, '%s is NOT whitelisted', o)
return False
def is_whitelisted_for_graph(o, check_call_override=True):
"""Checks whether an entity is whitelisted for use in graph mode.
Examples of whitelisted entities include all members of the tensorflow
package.
Args:
o: A Python entity.
check_call_override: Reserved for internal use. When set to `False`, it
disables the rule according to which classes are whitelisted if their
__call__ method is whitelisted.
Returns:
Boolean
"""
# TODO(b/120224672): Fix this.
if isinstance(o, functools.partial):
# tf_inspect.getmodule(functools.partial(...)) otherwise returns None since
# functools.partial objects do not have a __module__ attribute.
m = functools
else:
m = tf_inspect.getmodule(o)
if hasattr(m, '__name__'):
# Builtins typically have unnamed modules.
for prefix, in config.DEFAULT_UNCOMPILED_MODULES:
if m.__name__.startswith(prefix + '.') or m.__name__ == prefix:
logging.log(2, 'Whitelisted: %s: name starts with "%s"', o,
prefix)
return True
if hasattr(o, 'autograph_info__') or hasattr(o, '__ag_compiled'):
logging.log(2, 'Whitelisted: %s: already converted', o)
return True
if tf_inspect.isgeneratorfunction(o):
logging.warn(
'Entity {} appears to be a generator function. It will not be converted'
' by AutoGraph.'.format(o), 1)
logging.log(2,
'Whitelisted: %s: generator functions are not converted',
o)
return True
if check_call_override and hasattr(o, '__call__'):
# Callable objects: whitelisted if their __call__ method is.
# The type check avoids infinite recursion around the __call__ method
# of function objects.
if (type(o) != type(o.__call__)) and is_whitelisted_for_graph(
o.__call__): # pylint: disable=unidiomatic-typecheck
logging.log(2, 'Whitelisted: %s: object __call__ whitelisted', o)
return True
owner_class = None
if tf_inspect.ismethod(o):
# Methods of whitelisted classes are also whitelisted, even if they are
# bound via user subclasses.
#
# For example, suppose `tf.Foo` has a method called `bar`, and `baz` is
# defined as below. `tf.Foo` is whitelisted. Then `baz.bar` is also
# whitelisted.
#
# class Custom(tf.Foo):
# pass
#
# baz = Custom()
#
# For the example above, if `Custom` did overload `bar`, then it would no
# longer be whitelisted.
owner_class = inspect_utils.getmethodclass(o)
if owner_class is not None:
if issubclass(owner_class, unittest.TestCase):
logging.log(2, 'Whitelisted: %s: method of TestCase subclass',
o)
return True
owner_class = inspect_utils.getdefiningclass(o, owner_class)
is_call_override = (o.__name__ == '__call__')
if is_whitelisted_for_graph(
owner_class, check_call_override=not is_call_override):
logging.log(2, 'Whitelisted: %s: owner is whitelisted %s', o,
owner_class)
return True
if inspect_utils.isnamedtuple(o):
# Due to the way they're constructed, namedtuple types cannot be converted
# because they don't expose source code. But we assume they are safe for
# graph mode since they are just containers.
if tf_inspect.isclass(o) and len(o.__bases__) > 1:
logging.warn(
'Entity {} looks like a namedtuple subclass. Its constructor will'
' not be converted by AutoGraph, but if it has any custom methods,'
' those will be.'.format(o), 1)
logging.log(2, 'Whitelisted: %s: named tuple', o)
return True
logging.log(2, 'Not whitelisted: %s: default rule', o)
return False
def is_whitelisted_for_graph(o):
"""Check whether an entity is whitelisted for use in graph mode.
Examples of whitelisted entities include all members of the tensorflow
package.
Args:
o: A Python entity.
Returns:
Boolean
"""
# TODO(b/120224672): Fix this.
if isinstance(o, functools.partial):
# tf_inspect.getmodule(functools.partial(...)) otherwise returns None since
# functools.partial objects do not have a __module__ attribute.
m = functools
else:
m = tf_inspect.getmodule(o)
if not hasattr(m, '__name__'):
# Note: typically it's builtins that fall in this category. Builtins will
# be handled by specific code that follows this screening layer.
logging.log(2, '%s is NOT whitelisted: unknown module name', o)
return False
for prefix, in config.DEFAULT_UNCOMPILED_MODULES:
if m.__name__.startswith(prefix):
logging.log(2, '%s is whitelisted: name starts with "%s"', o, prefix)
return True
if hasattr(o, 'autograph_info__') or hasattr(o, '__ag_compiled'):
logging.log(2, '%s is whitelisted: already converted', o)
return True
if (not inspect_utils.isweakrefself(o) and not tf_inspect.isclass(o) and
hasattr(o, '__call__') and hasattr(o, '__class__')):
# Callable objects: whitelisted if their __call__ method is.
call_whitelisted = is_whitelisted_for_graph(o.__call__)
if call_whitelisted:
logging.log(2, '%s is whitelisted: object __call__ whitelisted', o)
return call_whitelisted
if tf_inspect.ismethod(o):
# Methods of whitelisted classes are also whitelisted, even if they are
# bound via user subclasses.
#
# For example, suppose `tf.Foo` has a method called `bar`, and `baz` is
# defined as below. `tf.Foo` is whitelisted. Then `baz.bar` is also
# whitelisted.
#
# class Custom(tf.Foo):
# pass
#
# baz = Custom()
#
# For the example above, if `Custom` did overload `bar`, then it would no
# longer be whitelisted.
owner_class = inspect_utils.getmethodclass(o)
if owner_class is not None:
owner_class = inspect_utils.getdefiningclass(o, owner_class)
if is_whitelisted_for_graph(owner_class):
logging.log(2, '%s is whitelisted: owner is whitelisted %s', o,
owner_class)
return True
if inspect_utils.isnamedtuple(o):
# Due to the way they're constructed, namedtuple types cannot be converted
# because they don't expose source code. But we assume they are safe for
# graph mode since they are just containers.
if tf_inspect.isclass(o) and len(o.__bases__) > 1:
logging.warn_first_n(
'Entity {} looks like a namedtuple subclass. If it has any custom'
' methods, they will not be converted by AutoGraph.'.format(o), 1)
logging.log(2, '%s is whitelisted: named tuple', o)
return True
logging.log(2, '%s is NOT whitelisted', o)
return False
def converted_call(f, options, *args, **kwargs):
"""Compiles a function call inline. For internal use only."""
# TODO(mdan): This needs cleanup.
# In particular, we may want to avoid renaming functions altogether.
if not options.force_conversion and conversion.is_whitelisted_for_graph(f):
return f(*args, **kwargs)
unknown_arg_value = object() # Sentinel for arguments of unknown value
if inspect_utils.isbuiltin(f):
return py_builtins.overload_of(f)(*args, **kwargs)
if tf_inspect.isfunction(f) or tf_inspect.ismethod(f):
# Regular functions
target_entity = f
arg_map_target = f
effective_args = args
f_class = inspect_utils.getmethodclass(f)
if f_class is not None:
partial_types = (f_class, )
else:
partial_types = ()
elif tf_inspect.isclass(f):
# Constructors
target_entity = f
arg_map_target = f.__init__
effective_args = args
partial_types = ()
elif hasattr(f, '__call__') and hasattr(f, '__class__'):
# Callable objects
target_entity = f.__call__
arg_map_target = f.__call__
effective_args = (f, ) + args
partial_types = (f.__class__, )
else:
NotImplementedError('unknown callable type "%s"' % type(f))
arg_values = tf_inspect.getcallargs(arg_map_target, *args, **kwargs)
for name, arg in arg_values.items():
if arg is unknown_arg_value:
continue
arg_class = arg.__class__
# If arg_value_hints specifies any name, use that instead.
if name not in options.arg_types:
options.arg_types[name] = (arg_class.__name__, arg_class)
# When called from within a decorator, this is the only indication that
# the function is a method - it appears that the decorator is applied
# before the method is bound.
if not partial_types:
if 'self' in arg_values:
if tf_inspect.isclass(arg_values['self'].__class__):
partial_types = (arg_values['self'].__class__, )
elif 'cls' in arg_values:
if tf_inspect.isclass(arg_values['cls']):
partial_types = (arg_values['cls'], )
converted_f = to_graph(target_entity,
recursive=options.recursive,
verbose=options.verbose,
arg_values=arg_values,
arg_types=options.arg_types,
partial_types=partial_types,
strip_decorators=options.strip_decorators)
return converted_f(*effective_args, **kwargs)
def converted_call(f, owner, options, *args, **kwargs):
"""Compiles a function call inline. For internal use only."""
if options.verbose:
logging.info('Converted call: {}; owner: {}'.format(f, owner))
if owner is not None:
if not isinstance(f, str):
raise ValueError(
'When owner is specified, the function name must be specified as'
' a string: {}'.format(f))
# Special case when the owner is a 'super' object. In that case lookups of
# dynamic attributes won't work. See
# inspect_utils.SuperWrapperForDynamicAttrs.
if isinstance(owner, super):
owner = inspect_utils.SuperWrapperForDynamicAttrs(owner)
f = getattr(owner, f)
# TODO(mdan): This needs cleanup.
# In particular, we may want to avoid renaming functions altogether.
if not options.force_conversion and conversion.is_whitelisted_for_graph(f):
return f(*args, **kwargs)
if inspect_utils.isbuiltin(f):
return py_builtins.overload_of(f)(*args, **kwargs)
# internal_convert_user_code is for example turned off when issuing a dynamic
# call conversion from generated code while in nonrecursive mode. In that
# case we evidently don't want to recurse, but we still have to convert
# things like builtins.
if not options.internal_convert_user_code:
return f(*args, **kwargs)
if tf_inspect.isfunction(f) or tf_inspect.ismethod(f):
# Regular functions
target_entity = f
arg_map_target = f
f_class = inspect_utils.getmethodclass(f)
if f_class is not None:
# If this is a method call, it may or may not include self.
#
# Example when self is included:
# converted_call(to_graph(foo.bar), foo)
#
# Example when self is not included:
# super(...).foo(args)
#
if owner is not None and (not args or args[0] is not owner):
effective_args = (owner, ) + args
else:
effective_args = args
partial_types = (f_class, )
else:
effective_args = args
partial_types = ()
elif tf_inspect.isclass(f):
# Constructors
target_entity = f
arg_map_target = f.__init__
effective_args = args
partial_types = ()
elif hasattr(f, '__call__') and hasattr(f, '__class__'):
# Callable objects
target_entity = f.__call__
arg_map_target = f.__call__
effective_args = (f, ) + args
partial_types = (f.__class__, )
else:
NotImplementedError('unknown callable type "%s"' % type(f))
arg_values = tf_inspect.getcallargs(arg_map_target, *args, **kwargs)
arg_types = {}
for name, arg in arg_values.items():
arg_class = arg.__class__
arg_types[name] = (arg_class.__name__, arg_class)
# When called from within a decorator, this is the only indication that
# the function is a method - it appears that the decorator is applied
# before the method is bound.
if not partial_types:
if 'self' in arg_values:
if tf_inspect.isclass(arg_values['self'].__class__):
partial_types = (arg_values['self'].__class__, )
elif 'cls' in arg_values:
if tf_inspect.isclass(arg_values['cls']):
partial_types = (arg_values['cls'], )
converted_f = to_graph(target_entity,
recursive=options.recursive,
verbose=options.verbose,
arg_values=arg_values,
arg_types=arg_types,
partial_types=partial_types,
strip_decorators=options.strip_decorators,
optional_features=options.optional_features)
result = converted_f(*effective_args, **kwargs)
# When converting a function, we write a tmp file and import it as a module.
# This leaks the module's closure. Once we've executed the converted_f module
# and there is no more code left to be executed, we can clean up the module.
# TODO(mdan): Look into workarounds that don't suffer from refcount leaks.
# Possibly attach the closure as a regular closure cell, instead of relying on
# module globals.
# If there are callables in the result, they will fail to find their closure
# when called, so only delete module if all returned types are not callable.
flat_results = nest.flatten(result)
if all(map(_is_not_callable, flat_results)):
del sys.modules[converted_f.__module__]
return result