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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/26666 Changes: - Introduce a `ConcreteModuleType` concept. This acts both as the key into the type cache, and as the source of truth for `ModuleValue::attr` queries. It needs to do both jobs because that's how we ensure correctness (if the types are different, it's because `ModuleValue::attr` would return different things). - Now `recursive_script` will first construct a `ConcreteModuleType` and search for a pre-existing type before starting compilation. - All previous paths to creating a `ScriptModule` (including inheriting from `ScriptModule`) are now rewritten to go through `create_script_module`, so that we have only a single place where construction happens. Behavioral changes: - Big change to `torch.jit.ScriptModule` inheritance: all attributes are now recursively scripted if possible, matching recursive scripting semantics. This makes it hard to keep something from being scripted (for example, a Python submodule). Possibly we'll need an `ignore()` type thing for attributes. In particular, this adds `self.training` to *every* ScriptModule, since it's present on every `nn.Module`. - I believe this change to be transparent to existing users of the inheritance API, since if you had an attribute that is unscriptable that you never used, there is no error. In some cases, we will create new attributes (even if they are unused), which will increase serialized model size from before. Test Plan: Imported from OSS Differential Revision: D17551196 Pulled By: suo fbshipit-source-id: b476d1c9feb3ddfd63406d90989aaf9dfe890591
172 lines
4.6 KiB
Python
172 lines
4.6 KiB
Python
# Copyright (c) 2010-2017 Benjamin Peterson
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in all
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# copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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import itertools
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import sys
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import builtins
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import types
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import inspect
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PY2 = sys.version_info[0] == 2
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PY3 = sys.version_info[0] == 3
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PY37 = sys.version_info[0] == 3 and sys.version_info[1] == 7
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if PY2:
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inf = float('inf')
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nan = float('nan')
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else:
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import math
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inf = math.inf
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nan = math.nan
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if PY2:
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string_classes = basestring
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else:
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string_classes = (str, bytes)
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if PY2:
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int_classes = (int, long)
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else:
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int_classes = int
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if PY2:
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FileNotFoundError = IOError
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else:
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FileNotFoundError = builtins.FileNotFoundError
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if PY2:
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import Queue as queue # noqa: F401
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else:
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import queue # noqa: F401
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def with_metaclass(meta, *bases):
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"""Create a base class with a metaclass."""
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# This requires a bit of explanation: the basic idea is to make a dummy
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# metaclass for one level of class instantiation that replaces itself with
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# the actual metaclass.
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class metaclass(meta):
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def __new__(cls, name, this_bases, d):
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return meta(name, bases, d)
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return type.__new__(metaclass, 'temporary_class', (), {})
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# A portable way of referring to the generator version of map
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# in both Python 2 and Python 3.
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if hasattr(itertools, 'imap'):
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imap = itertools.imap # type: ignore
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else:
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imap = map # type: ignore
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if PY3:
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import builtins
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# See https://github.com/PyCQA/flake8-bugbear/issues/64
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exec_ = getattr(builtins, "exec") # noqa: B009
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else:
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def exec_(_code_, _globs_=None, _locs_=None):
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"""Execute code in a namespace."""
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if _globs_ is None:
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frame = sys._getframe(1)
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_globs_ = frame.f_globals
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if _locs_ is None:
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_locs_ = frame.f_locals
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del frame
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elif _locs_ is None:
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_locs_ = _globs_
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exec("""exec _code_ in _globs_, _locs_""")
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if sys.version_info[:2] == (3, 2):
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exec_("""def raise_from(value, from_value):
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try:
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if from_value is None:
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raise value
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raise value from from_value
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finally:
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value = None
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""")
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elif sys.version_info[:2] > (3, 2):
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exec_("""def raise_from(value, from_value):
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try:
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raise value from from_value
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finally:
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value = None
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""")
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else:
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def raise_from(value, from_value):
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raise value
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if PY2:
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import collections
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container_abcs = collections
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elif PY3:
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import collections.abc
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container_abcs = collections.abc
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# Gets a function from the name of a method on a type
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if PY2:
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def get_function_from_type(cls, name):
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method = getattr(cls, name, None)
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return getattr(method, "__func__", None)
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elif PY3:
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def get_function_from_type(cls, name):
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return getattr(cls, name, None)
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if PY2:
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import __builtin__ as builtins
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elif PY3:
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import builtins
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if PY2:
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import StringIO
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StringIO = StringIO.StringIO
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elif PY3:
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import io
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StringIO = io.StringIO
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# The codes below is not copied from the six package, so the copyright
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# declaration at the beginning does not apply.
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#
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# Copyright(c) PyTorch contributors
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#
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def istuple(obj):
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# Usually instances of PyStructSequence is also an instance of tuple
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# but in some py2 environment it is not, so we have to manually check
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# the name of the type to determine if it is a namedtupled returned
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# by a pytorch operator.
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t = type(obj)
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return isinstance(obj, tuple) or t.__module__ == 'torch.return_types'
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def bind_method(fn, obj, obj_type):
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if PY2:
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if inspect.ismethod(fn):
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fn = fn.__func__
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return types.MethodType(fn, obj, obj_type)
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else:
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return types.MethodType(fn, obj)
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