101 lines
3.5 KiB
Python
101 lines
3.5 KiB
Python
# Copyright 2017 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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"""TensorBoard is a webapp for understanding TensorFlow runs and graphs."""
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import functools
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import threading
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import types
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def lazy_load(name):
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"""Decorator to define a function that lazily loads the module 'name'.
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This can be used to defer importing troublesome dependencies - e.g. ones that
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are large and infrequently used, or that cause a dependency cycle -
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until they are actually used.
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Args:
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name: the fully-qualified name of the module; typically the last segment
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of 'name' matches the name of the decorated function
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Returns:
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Decorator function that produces a lazy-loading module 'name' backed by the
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underlying decorated function.
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"""
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def wrapper(load_fn):
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# Wrap load_fn to call it exactly once and update __dict__ afterwards to
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# make future lookups efficient (only failed lookups call __getattr__).
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@_memoize
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def load_once(self):
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if load_once.loading:
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raise ImportError(
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"Circular import when resolving LazyModule %r" % name
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)
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load_once.loading = True
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try:
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module = load_fn()
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finally:
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load_once.loading = False
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self.__dict__.update(module.__dict__)
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load_once.loaded = True
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return module
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load_once.loading = False
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load_once.loaded = False
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# Define a module that proxies getattr() and dir() to the result of calling
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# load_once() the first time it's needed. The class is nested so we can close
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# over load_once() and avoid polluting the module's attrs with our own state.
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class LazyModule(types.ModuleType):
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def __getattr__(self, attr_name):
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return getattr(load_once(self), attr_name)
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def __dir__(self):
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return dir(load_once(self))
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def __repr__(self):
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if load_once.loaded:
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return "<%r via LazyModule (loaded)>" % load_once(self)
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return (
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"<module %r via LazyModule (not yet loaded)>"
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% self.__name__
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)
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return LazyModule(name)
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return wrapper
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def _memoize(f):
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"""Memoizing decorator for f, which must have exactly 1 hashable
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argument."""
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nothing = object() # Unique "no value" sentinel object.
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cache = {}
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# Use a reentrant lock so that if f references the resulting wrapper we die
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# with recursion depth exceeded instead of deadlocking.
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lock = threading.RLock()
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@functools.wraps(f)
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def wrapper(arg):
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if cache.get(arg, nothing) is nothing:
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with lock:
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if cache.get(arg, nothing) is nothing:
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cache[arg] = f(arg)
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return cache[arg]
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return wrapper
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