Cherry pick #129244 #129251 #129509 #129574
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Since we use [`DEFAULT_PROTOCOL=2`](https://github.com/pytorch/pytorch/blob/main/torch/serialization.py#L62), some functions/classes that were renamed from python 2-->3 will be pickled with their python2 name. This PR ensures that when a mod `GLOBAL <python2_mod>.<python2_name> ` is encountered, [following the strategy used by pickle](https://github.com/python/cpython/blob/main/Lib/pickle.py#L1590C13-L1593C63) it is properly mapped to `<python3_mod>.<python3_name>`. This fix ensures that `add_safe_globals` works properly for such functions/classes (i.e. users will allowlist the python3 func and the weights_only unpickler will do the appropriate translation when checking whether a class was allowlisted). An example is as follows: `__builtin__` was named to `builtins`, see the [release notes for Python 3.0](https://docs.python.org/3/whatsnew/3.0.html) > Renamed module `__builtin__` to [`builtins`](https://docs.python.org/3/library/builtins.html#module-builtins) (removing the underscores, adding an ‘s’). The __builtins__ variable found in most global namespaces is unchanged. To modify a builtin, you should use [builtins](https://docs.python.org/3/library/builtins.html#module-builtins), not `__builtins__`! However, since we use [`DEFAULT_PROTOCOL=2`](https://github.com/pytorch/pytorch/blob/main/torch/serialization.py#L62), builtins will be pickled with their module string as `__builtin__`. ```python >>> import pickle >>> import pickletools >>> print.__module__ 'builtins' >>> with open('print.pkl', 'wb') as f: >>> pickle.dump(print, f, protocol=2) # 2 because this is the default protocol used by pytorch >>> with open('print.pkl', 'rb') as f: >>> pickletools.dis(f) 0: \x80 PROTO 2 2: c GLOBAL '__builtin__ print' # pickle saves the module string as __builtin__ !!! :( 21: q BINPUT 0 23: . STOP ``` Pull Request resolved: pytorch#129244 Approved by: https://github.com/albanD
…n.add_safe_globals (pytorch#129251) Previously, allowlisting functions/classes via `torch.serialization.add_safe_globals(obj)` for the `weights_only` Unpickler had the following effect: - For a [`GLOBAL`](https://github.com/python/cpython/blob/3.12/Lib/pickletools.py#L1926-L1939) instruction, `GLOBAL obj.__module__ obj.__name__` would be allowed and translated back to obj to be pushed back to the stack. - For a [`REDUCE`](https://github.com/python/cpython/blob/3.12/Lib/pickletools.py#L1926-L1982) instruction where we expect the stack to contain `func` and `args`, `func` is allowed if it was added via `add_safe_globals` However, it did not have an effect on `BUILD` and `NEWOBJ` instructions Some classes may be rebuilt via [`NEWOBJ`](https://github.com/python/cpython/blob/3.12/Lib/pickletools.py#L2091-L2104) instruction, which indicates that their constructor should be used to rebuild the class. Further, a [`BUILD`](https://github.com/python/cpython/blob/3.12/Lib/pickletools.py#L1984-L2007) instruction might be used if an object's `__reduce__`/`__reduce_ex__` returns a non-None value for `state`. Which indicates a `__setstate__` or `__dict__.update`. **This PR makes sure that adding objects to the allowlist will also allow `NEWOBJ` and `BUILD` instructions for them.** In particular, the update for `NEWOBJ` should unblock allowlisting of [`ScaledMMConfig`](https://github.com/pytorch-labs/float8_experimental/blob/d4ade877dff327ea7f51e91f7cc218ae956e8cfd/float8_experimental/float8_tensor.py#L26-L30) in float8_experimental @drisspg Pull Request resolved: pytorch#129251 Approved by: https://github.com/albanD ghstack dependencies: pytorch#129244
ghstack-source-id: 7d6ee40 Pull Request resolved: pytorch#129509
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/129574
Note: Links to docs will display an error until the docs builds have been completed. ❌ 3 New FailuresAs of commit 2091793 with merge base b66e3f0 (
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atalman
approved these changes
Jun 27, 2024
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Cherry pick #129244 #129251 #129509
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