# Copyright 2018 The TensorFlow Authors. All Rights Reserved.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

# ==============================================================================

"""Utility to retrieve function args."""

import functools

from tensorflow.core.protobuf import config_pb2

from tensorflow.python.util import tf_decorator

from tensorflow.python.util import tf_inspect

def _is_bound_method(fn):

_, fn = tf_decorator.unwrap(fn)

return tf_inspect.ismethod(fn) and (fn.__self__ is not None)

def _is_callable_object(obj):

return hasattr(obj, '__call__') and tf_inspect.ismethod(obj.__call__)

def fn_args(fn):

"""Get argument names for function-like object.

Args:

fn: Function, or function-like object (e.g., result of `functools.partial`).

Returns:

`tuple` of string argument names.

Raises:

ValueError: if partial function has positionally bound arguments

"""

if isinstance(fn, functools.partial):

args = fn_args(fn.func)

args = [a for a in args[len(fn.args):] if a not in (fn.keywords or [])]

else:

if _is_callable_object(fn):

fn = fn.__call__

args = tf_inspect.getfullargspec(fn).args

if _is_bound_method(fn) and args:

# If it's a bound method, it may or may not have a self/cls first

# argument; for example, self could be captured in *args.

# If it does have a positional argument, it is self/cls.

args.pop(0)

return tuple(args)

def has_kwargs(fn):

"""Returns whether the passed callable has **kwargs in its signature.

Args:

fn: Function, or function-like object (e.g., result of `functools.partial`).

Returns:

`bool`: if `fn` has **kwargs in its signature.

Raises:

`TypeError`: If fn is not a Function, or function-like object.

"""

if isinstance(fn, functools.partial):

fn = fn.func

elif _is_callable_object(fn):

fn = fn.__call__

elif not callable(fn):

raise TypeError(

'Argument `fn` should be a callable. '

f'Received: fn={fn} (of type {type(fn)})')

return tf_inspect.getfullargspec(fn).varkw is not None

def get_func_name(func):

"""Returns name of passed callable."""

_, func = tf_decorator.unwrap(func)

if callable(func):

if tf_inspect.isfunction(func):

return func.__name__

elif tf_inspect.ismethod(func):

return '%s.%s' % (

func.__self__.__class__.__name__,

func.__func__.__name__,

)

else: # Probably a class instance with __call__

return str(type(func))

else:

raise ValueError(

'Argument `func` must be a callable. '

f'Received func={func} (of type {type(func)})')

def get_func_code(func):

"""Returns func_code of passed callable, or None if not available."""

_, func = tf_decorator.unwrap(func)

if callable(func):

if tf_inspect.isfunction(func) or tf_inspect.ismethod(func):

return func.__code__

# Since the object is not a function or method, but is a callable, we will

# try to access the __call__method as a function. This works with callable

# classes but fails with functool.partial objects despite their __call__

# attribute.

try:

return func.__call__.__code__

except AttributeError:

return None

else:

raise ValueError(

'Argument `func` must be a callable. '

f'Received func={func} (of type {type(func)})')

_rewriter_config_optimizer_disabled = None

def get_disabled_rewriter_config():

global _rewriter_config_optimizer_disabled

if _rewriter_config_optimizer_disabled is None:

config = config_pb2.ConfigProto()

rewriter_config = config.graph_options.rewrite_options

rewriter_config.disable_meta_optimizer = True

_rewriter_config_optimizer_disabled = config.SerializeToString()

return _rewriter_config_optimizer_disabled