133 lines
4.2 KiB
Python
133 lines
4.2 KiB
Python
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Utility to retrieve function args."""
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import functools
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from tensorflow.core.protobuf import config_pb2
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from tensorflow.python.util import tf_decorator
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from tensorflow.python.util import tf_inspect
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def _is_bound_method(fn):
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_, fn = tf_decorator.unwrap(fn)
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return tf_inspect.ismethod(fn) and (fn.__self__ is not None)
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def _is_callable_object(obj):
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return hasattr(obj, '__call__') and tf_inspect.ismethod(obj.__call__)
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def fn_args(fn):
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"""Get argument names for function-like object.
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Args:
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fn: Function, or function-like object (e.g., result of `functools.partial`).
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Returns:
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`tuple` of string argument names.
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Raises:
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ValueError: if partial function has positionally bound arguments
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"""
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if isinstance(fn, functools.partial):
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args = fn_args(fn.func)
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args = [a for a in args[len(fn.args):] if a not in (fn.keywords or [])]
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else:
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if _is_callable_object(fn):
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fn = fn.__call__
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args = tf_inspect.getfullargspec(fn).args
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if _is_bound_method(fn) and args:
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# If it's a bound method, it may or may not have a self/cls first
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# argument; for example, self could be captured in *args.
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# If it does have a positional argument, it is self/cls.
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args.pop(0)
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return tuple(args)
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def has_kwargs(fn):
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"""Returns whether the passed callable has **kwargs in its signature.
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Args:
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fn: Function, or function-like object (e.g., result of `functools.partial`).
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Returns:
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`bool`: if `fn` has **kwargs in its signature.
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Raises:
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`TypeError`: If fn is not a Function, or function-like object.
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"""
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if isinstance(fn, functools.partial):
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fn = fn.func
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elif _is_callable_object(fn):
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fn = fn.__call__
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elif not callable(fn):
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raise TypeError(
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'Argument `fn` should be a callable. '
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f'Received: fn={fn} (of type {type(fn)})')
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return tf_inspect.getfullargspec(fn).varkw is not None
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def get_func_name(func):
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"""Returns name of passed callable."""
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_, func = tf_decorator.unwrap(func)
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if callable(func):
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if tf_inspect.isfunction(func):
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return func.__name__
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elif tf_inspect.ismethod(func):
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return '%s.%s' % (
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func.__self__.__class__.__name__,
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func.__func__.__name__,
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)
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else: # Probably a class instance with __call__
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return str(type(func))
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else:
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raise ValueError(
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'Argument `func` must be a callable. '
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f'Received func={func} (of type {type(func)})')
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def get_func_code(func):
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"""Returns func_code of passed callable, or None if not available."""
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_, func = tf_decorator.unwrap(func)
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if callable(func):
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if tf_inspect.isfunction(func) or tf_inspect.ismethod(func):
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return func.__code__
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# Since the object is not a function or method, but is a callable, we will
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# try to access the __call__method as a function. This works with callable
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# classes but fails with functool.partial objects despite their __call__
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# attribute.
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try:
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return func.__call__.__code__
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except AttributeError:
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return None
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else:
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raise ValueError(
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'Argument `func` must be a callable. '
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f'Received func={func} (of type {type(func)})')
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_rewriter_config_optimizer_disabled = None
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def get_disabled_rewriter_config():
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global _rewriter_config_optimizer_disabled
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if _rewriter_config_optimizer_disabled is None:
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config = config_pb2.ConfigProto()
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rewriter_config = config.graph_options.rewrite_options
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rewriter_config.disable_meta_optimizer = True
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_rewriter_config_optimizer_disabled = config.SerializeToString()
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return _rewriter_config_optimizer_disabled
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