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Source code for torch.package.package_importer

# mypy: allow-untyped-defs
import builtins
import importlib
import importlib.machinery
import inspect
import io
import linecache
import os
import sys
import types
from contextlib import contextmanager
from typing import (
    Any,
    BinaryIO,
    Callable,
    cast,
    Dict,
    Iterable,
    List,
    Optional,
    TYPE_CHECKING,
    Union,
)
from weakref import WeakValueDictionary

import torch
from torch.serialization import _get_restore_location, _maybe_decode_ascii

from ._directory_reader import DirectoryReader
from ._importlib import (
    _calc___package__,
    _normalize_line_endings,
    _normalize_path,
    _resolve_name,
    _sanity_check,
)
from ._mangling import demangle, PackageMangler
from ._package_unpickler import PackageUnpickler
from .file_structure_representation import _create_directory_from_file_list, Directory
from .importer import Importer


if TYPE_CHECKING:
    from .glob_group import GlobPattern

__all__ = ["PackageImporter"]


# This is a list of imports that are implicitly allowed even if they haven't
# been marked as extern. This is to work around the fact that Torch implicitly
# depends on numpy and package can't track it.
# https://github.com/pytorch/MultiPy/issues/46
IMPLICIT_IMPORT_ALLOWLIST: Iterable[str] = [
    "numpy",
    "numpy.core",
    "numpy.core._multiarray_umath",
    # FX GraphModule might depend on builtins module and users usually
    # don't extern builtins. Here we import it here by default.
    "builtins",
]


# Compatibility name mapping to facilitate upgrade of external modules.
# The primary motivation is to enable Numpy upgrade that many modules
# depend on. The latest release of Numpy removed `numpy.str` and
# `numpy.bool` breaking unpickling for many modules.
EXTERN_IMPORT_COMPAT_NAME_MAPPING: Dict[str, Dict[str, Any]] = {
    "numpy": {
        "str": str,
        "bool": bool,
    },
}


[docs]class PackageImporter(Importer): """Importers allow you to load code written to packages by :class:`PackageExporter`. Code is loaded in a hermetic way, using files from the package rather than the normal python import system. This allows for the packaging of PyTorch model code and data so that it can be run on a server or used in the future for transfer learning. The importer for packages ensures that code in the module can only be loaded from within the package, except for modules explicitly listed as external during export. The file ``extern_modules`` in the zip archive lists all the modules that a package externally depends on. This prevents "implicit" dependencies where the package runs locally because it is importing a locally-installed package, but then fails when the package is copied to another machine. """ """The dictionary of already loaded modules from this package, equivalent to ``sys.modules`` but local to this importer. """ modules: Dict[str, types.ModuleType]
[docs] def __init__( self, file_or_buffer: Union[str, torch._C.PyTorchFileReader, os.PathLike, BinaryIO], module_allowed: Callable[[str], bool] = lambda module_name: True, ): """Open ``file_or_buffer`` for importing. This checks that the imported package only requires modules allowed by ``module_allowed`` Args: file_or_buffer: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`), a string, or an ``os.PathLike`` object containing a filename. module_allowed (Callable[[str], bool], optional): A method to determine if a externally provided module should be allowed. Can be used to ensure packages loaded do not depend on modules that the server does not support. Defaults to allowing anything. Raises: ImportError: If the package will use a disallowed module. """ torch._C._log_api_usage_once("torch.package.PackageImporter") self.zip_reader: Any if isinstance(file_or_buffer, torch._C.PyTorchFileReader): self.filename = "<pytorch_file_reader>" self.zip_reader = file_or_buffer elif isinstance(file_or_buffer, (os.PathLike, str)): self.filename = os.fspath(file_or_buffer) if not os.path.isdir(self.filename): self.zip_reader = torch._C.PyTorchFileReader(self.filename) else: self.zip_reader = DirectoryReader(self.filename) else: self.filename = "<binary>" self.zip_reader = torch._C.PyTorchFileReader(file_or_buffer) torch._C._log_api_usage_metadata( "torch.package.PackageImporter.metadata", { "serialization_id": self.zip_reader.serialization_id(), "file_name": self.filename, }, ) self.root = _PackageNode(None) self.modules = {} self.extern_modules = self._read_extern() for extern_module in self.extern_modules: if not module_allowed(extern_module): raise ImportError( f"package '{file_or_buffer}' needs the external module '{extern_module}' " f"but that module has been disallowed" ) self._add_extern(extern_module) for fname in self.zip_reader.get_all_records(): self._add_file(fname) self.patched_builtins = builtins.__dict__.copy() self.patched_builtins["__import__"] = self.__import__ # Allow packaged modules to reference their PackageImporter self.modules["torch_package_importer"] = self # type: ignore[assignment] self._mangler = PackageMangler() # used for reduce deserializaiton self.storage_context: Any = None self.last_map_location = None # used for torch.serialization._load self.Unpickler = lambda *args, **kwargs: PackageUnpickler(self, *args, **kwargs)
[docs] def import_module(self, name: str, package=None): """Load a module from the package if it hasn't already been loaded, and then return the module. Modules are loaded locally to the importer and will appear in ``self.modules`` rather than ``sys.modules``. Args: name (str): Fully qualified name of the module to load. package ([type], optional): Unused, but present to match the signature of importlib.import_module. Defaults to ``None``. Returns: types.ModuleType: The (possibly already) loaded module. """ # We should always be able to support importing modules from this package. # This is to support something like: # obj = importer.load_pickle(...) # importer.import_module(obj.__module__) <- this string will be mangled # # Note that _mangler.demangle will not demangle any module names # produced by a different PackageImporter instance. name = self._mangler.demangle(name) return self._gcd_import(name)
[docs] def load_binary(self, package: str, resource: str) -> bytes: """Load raw bytes. Args: package (str): The name of module package (e.g. ``"my_package.my_subpackage"``). resource (str): The unique name for the resource. Returns: bytes: The loaded data. """ path = self._zipfile_path(package, resource) return self.zip_reader.get_record(path)
[docs] def load_text( self, package: str, resource: str, encoding: str = "utf-8", errors: str = "strict", ) -> str: """Load a string. Args: package (str): The name of module package (e.g. ``"my_package.my_subpackage"``). resource (str): The unique name for the resource. encoding (str, optional): Passed to ``decode``. Defaults to ``'utf-8'``. errors (str, optional): Passed to ``decode``. Defaults to ``'strict'``. Returns: str: The loaded text. """ data = self.load_binary(package, resource) return data.decode(encoding, errors)
[docs] def load_pickle(self, package: str, resource: str, map_location=None) -> Any: """Unpickles the resource from the package, loading any modules that are needed to construct the objects using :meth:`import_module`. Args: package (str): The name of module package (e.g. ``"my_package.my_subpackage"``). resource (str): The unique name for the resource. map_location: Passed to `torch.load` to determine how tensors are mapped to devices. Defaults to ``None``. Returns: Any: The unpickled object. """ pickle_file = self._zipfile_path(package, resource) restore_location = _get_restore_location(map_location) loaded_storages = {} loaded_reduces = {} storage_context = torch._C.DeserializationStorageContext() def load_tensor(dtype, size, key, location, restore_location): name = f"{key}.storage" if storage_context.has_storage(name): storage = storage_context.get_storage(name, dtype)._typed_storage() else: tensor = self.zip_reader.get_storage_from_record( ".data/" + name, size, dtype ) if isinstance(self.zip_reader, torch._C.PyTorchFileReader): storage_context.add_storage(name, tensor) storage = tensor._typed_storage() loaded_storages[key] = restore_location(storage, location) def persistent_load(saved_id): assert isinstance(saved_id, tuple) typename = _maybe_decode_ascii(saved_id[0]) data = saved_id[1:] if typename == "storage": storage_type, key, location, size = data dtype = storage_type.dtype if key not in loaded_storages: load_tensor( dtype, size, key, _maybe_decode_ascii(location), restore_location, ) storage = loaded_storages[key] # TODO: Once we decide to break serialization FC, we can # stop wrapping with TypedStorage return torch.storage.TypedStorage( wrap_storage=storage._untyped_storage, dtype=dtype, _internal=True ) elif typename == "reduce_package": # to fix BC breaking change, objects on this load path # will be loaded multiple times erroneously if len(data) == 2: func, args = data return func(self, *args) reduce_id, func, args = data if reduce_id not in loaded_reduces: loaded_reduces[reduce_id] = func(self, *args) return loaded_reduces[reduce_id] else: f"Unknown typename for persistent_load, expected 'storage' or 'reduce_package' but got '{typename}'" # Load the data (which may in turn use `persistent_load` to load tensors) data_file = io.BytesIO(self.zip_reader.get_record(pickle_file)) unpickler = self.Unpickler(data_file) unpickler.persistent_load = persistent_load # type: ignore[assignment] @contextmanager def set_deserialization_context(): # to let reduce_package access deserializaiton context self.storage_context = storage_context self.last_map_location = map_location try: yield finally: self.storage_context = None self.last_map_location = None with set_deserialization_context(): result = unpickler.load() # TODO from zdevito: # This stateful weird function will need to be removed in our efforts # to unify the format. It has a race condition if multiple python # threads try to read independent files torch._utils._validate_loaded_sparse_tensors() return result
[docs] def id(self): """ Returns internal identifier that torch.package uses to distinguish :class:`PackageImporter` instances. Looks like:: <torch_package_0> """ return self._mangler.parent_name()
[docs] def file_structure( self, *, include: "GlobPattern" = "**", exclude: "GlobPattern" = () ) -> Directory: """Returns a file structure representation of package's zipfile. Args: include (Union[List[str], str]): An optional string e.g. ``"my_package.my_subpackage"``, or optional list of strings for the names of the files to be included in the zipfile representation. This can also be a glob-style pattern, as described in :meth:`PackageExporter.mock` exclude (Union[List[str], str]): An optional pattern that excludes files whose name match the pattern. Returns: :class:`Directory` """ return _create_directory_from_file_list( self.filename, self.zip_reader.get_all_records(), include, exclude )
[docs] def python_version(self): """Returns the version of python that was used to create this package. Note: this function is experimental and not Forward Compatible. The plan is to move this into a lock file later on. Returns: :class:`Optional[str]` a python version e.g. 3.8.9 or None if no version was stored with this package """ python_version_path = ".data/python_version" return ( self.zip_reader.get_record(python_version_path).decode("utf-8").strip() if self.zip_reader.has_record(python_version_path) else None )
def _read_extern(self): return ( self.zip_reader.get_record(".data/extern_modules") .decode("utf-8") .splitlines(keepends=False) ) def _make_module( self, name: str, filename: Optional[str], is_package: bool, parent: str ): mangled_filename = self._mangler.mangle(filename) if filename else None spec = importlib.machinery.ModuleSpec( name, self, # type: ignore[arg-type] origin="<package_importer>", is_package=is_package, ) module = importlib.util.module_from_spec(spec) self.modules[name] = module module.__name__ = self._mangler.mangle(name) ns = module.__dict__ ns["__spec__"] = spec ns["__loader__"] = self ns["__file__"] = mangled_filename ns["__cached__"] = None ns["__builtins__"] = self.patched_builtins ns["__torch_package__"] = True # Add this module to our private global registry. It should be unique due to mangling. assert module.__name__ not in _package_imported_modules _package_imported_modules[module.__name__] = module # pre-emptively install on the parent to prevent IMPORT_FROM from trying to # access sys.modules self._install_on_parent(parent, name, module) if filename is not None: assert mangled_filename is not None # pre-emptively install the source in `linecache` so that stack traces, # `inspect`, etc. work. assert filename not in linecache.cache # type: ignore[attr-defined] linecache.lazycache(mangled_filename, ns) code = self._compile_source(filename, mangled_filename) exec(code, ns) return module def _load_module(self, name: str, parent: str): cur: _PathNode = self.root for atom in name.split("."): if not isinstance(cur, _PackageNode) or atom not in cur.children: if name in IMPLICIT_IMPORT_ALLOWLIST: module = self.modules[name] = importlib.import_module(name) return module raise ModuleNotFoundError( f'No module named "{name}" in self-contained archive "{self.filename}"' f" and the module is also not in the list of allowed external modules: {self.extern_modules}", name=name, ) cur = cur.children[atom] if isinstance(cur, _ExternNode): module = self.modules[name] = importlib.import_module(name) if compat_mapping := EXTERN_IMPORT_COMPAT_NAME_MAPPING.get(name): for old_name, new_name in compat_mapping.items(): module.__dict__.setdefault(old_name, new_name) return module return self._make_module(name, cur.source_file, isinstance(cur, _PackageNode), parent) # type: ignore[attr-defined] def _compile_source(self, fullpath: str, mangled_filename: str): source = self.zip_reader.get_record(fullpath) source = _normalize_line_endings(source) return compile(source, mangled_filename, "exec", dont_inherit=True) # note: named `get_source` so that linecache can find the source # when this is the __loader__ of a module. def get_source(self, module_name) -> str: # linecache calls `get_source` with the `module.__name__` as the argument, so we must demangle it here. module = self.import_module(demangle(module_name)) return self.zip_reader.get_record(demangle(module.__file__)).decode("utf-8") # note: named `get_resource_reader` so that importlib.resources can find it. # This is otherwise considered an internal method. def get_resource_reader(self, fullname): try: package = self._get_package(fullname) except ImportError: return None if package.__loader__ is not self: return None return _PackageResourceReader(self, fullname) def _install_on_parent(self, parent: str, name: str, module: types.ModuleType): if not parent: return # Set the module as an attribute on its parent. parent_module = self.modules[parent] if parent_module.__loader__ is self: setattr(parent_module, name.rpartition(".")[2], module) # note: copied from cpython's import code, with call to create module replaced with _make_module def _do_find_and_load(self, name): parent = name.rpartition(".")[0] module_name_no_parent = name.rpartition(".")[-1] if parent: if parent not in self.modules: self._gcd_import(parent) # Crazy side-effects! if name in self.modules: return self.modules[name] parent_module = self.modules[parent] try: parent_module.__path__ # type: ignore[attr-defined] except AttributeError: # when we attempt to import a package only containing pybinded files, # the parent directory isn't always a package as defined by python, # so we search if the package is actually there or not before calling the error. if isinstance( parent_module.__loader__, importlib.machinery.ExtensionFileLoader, ): if name not in self.extern_modules: msg = ( _ERR_MSG + "; {!r} is a c extension module which was not externed. C extension modules \ need to be externed by the PackageExporter in order to be used as we do not support interning them.}." ).format(name, name) raise ModuleNotFoundError(msg, name=name) from None if not isinstance( parent_module.__dict__.get(module_name_no_parent), types.ModuleType, ): msg = ( _ERR_MSG + "; {!r} is a c extension package which does not contain {!r}." ).format(name, parent, name) raise ModuleNotFoundError(msg, name=name) from None else: msg = (_ERR_MSG + "; {!r} is not a package").format(name, parent) raise ModuleNotFoundError(msg, name=name) from None module = self._load_module(name, parent) self._install_on_parent(parent, name, module) return module # note: copied from cpython's import code def _find_and_load(self, name): module = self.modules.get(name, _NEEDS_LOADING) if module is _NEEDS_LOADING: return self._do_find_and_load(name) if module is None: message = f"import of {name} halted; None in sys.modules" raise ModuleNotFoundError(message, name=name) # To handle https://github.com/pytorch/pytorch/issues/57490, where std's # creation of fake submodules via the hacking of sys.modules is not import # friendly if name == "os": self.modules["os.path"] = cast(Any, module).path elif name == "typing": if sys.version_info < (3, 13): self.modules["typing.io"] = cast(Any, module).io self.modules["typing.re"] = cast(Any, module).re return module def _gcd_import(self, name, package=None, level=0): """Import and return the module based on its name, the package the call is being made from, and the level adjustment. This function represents the greatest common denominator of functionality between import_module and __import__. This includes setting __package__ if the loader did not. """ _sanity_check(name, package, level) if level > 0: name = _resolve_name(name, package, level) return self._find_and_load(name) # note: copied from cpython's import code def _handle_fromlist(self, module, fromlist, *, recursive=False): """Figure out what __import__ should return. The import_ parameter is a callable which takes the name of module to import. It is required to decouple the function from assuming importlib's import implementation is desired. """ module_name = demangle(module.__name__) # The hell that is fromlist ... # If a package was imported, try to import stuff from fromlist. if hasattr(module, "__path__"): for x in fromlist: if not isinstance(x, str): if recursive: where = module_name + ".__all__" else: where = "``from list''" raise TypeError( f"Item in {where} must be str, " f"not {type(x).__name__}" ) elif x == "*": if not recursive and hasattr(module, "__all__"): self._handle_fromlist(module, module.__all__, recursive=True) elif not hasattr(module, x): from_name = f"{module_name}.{x}" try: self._gcd_import(from_name) except ModuleNotFoundError as exc: # Backwards-compatibility dictates we ignore failed # imports triggered by fromlist for modules that don't # exist. if ( exc.name == from_name and self.modules.get(from_name, _NEEDS_LOADING) is not None ): continue raise return module def __import__(self, name, globals=None, locals=None, fromlist=(), level=0): if level == 0: module = self._gcd_import(name) else: globals_ = globals if globals is not None else {} package = _calc___package__(globals_) module = self._gcd_import(name, package, level) if not fromlist: # Return up to the first dot in 'name'. This is complicated by the fact # that 'name' may be relative. if level == 0: return self._gcd_import(name.partition(".")[0]) elif not name: return module else: # Figure out where to slice the module's name up to the first dot # in 'name'. cut_off = len(name) - len(name.partition(".")[0]) # Slice end needs to be positive to alleviate need to special-case # when ``'.' not in name``. module_name = demangle(module.__name__) return self.modules[module_name[: len(module_name) - cut_off]] else: return self._handle_fromlist(module, fromlist) def _get_package(self, package): """Take a package name or module object and return the module. If a name, the module is imported. If the passed or imported module object is not a package, raise an exception. """ if hasattr(package, "__spec__"): if package.__spec__.submodule_search_locations is None: raise TypeError(f"{package.__spec__.name!r} is not a package") else: return package else: module = self.import_module(package) if module.__spec__.submodule_search_locations is None: raise TypeError(f"{package!r} is not a package") else: return module def _zipfile_path(self, package, resource=None): package = self._get_package(package) assert package.__loader__ is self name = demangle(package.__name__) if resource is not None: resource = _normalize_path(resource) return f"{name.replace('.', '/')}/{resource}" else: return f"{name.replace('.', '/')}" def _get_or_create_package( self, atoms: List[str] ) -> "Union[_PackageNode, _ExternNode]": cur = self.root for i, atom in enumerate(atoms): node = cur.children.get(atom, None) if node is None: node = cur.children[atom] = _PackageNode(None) if isinstance(node, _ExternNode): return node if isinstance(node, _ModuleNode): name = ".".join(atoms[:i]) raise ImportError( f"inconsistent module structure. module {name} is not a package, but has submodules" ) assert isinstance(node, _PackageNode) cur = node return cur def _add_file(self, filename: str): """Assembles a Python module out of the given file. Will ignore files in the .data directory. Args: filename (str): the name of the file inside of the package archive to be added """ *prefix, last = filename.split("/") if len(prefix) > 1 and prefix[0] == ".data": return package = self._get_or_create_package(prefix) if isinstance(package, _ExternNode): raise ImportError( f"inconsistent module structure. package contains a module file {filename}" f" that is a subpackage of a module marked external." ) if last == "__init__.py": package.source_file = filename elif last.endswith(".py"): package_name = last[: -len(".py")] package.children[package_name] = _ModuleNode(filename) def _add_extern(self, extern_name: str): *prefix, last = extern_name.split(".") package = self._get_or_create_package(prefix) if isinstance(package, _ExternNode): return # the shorter extern covers this extern case package.children[last] = _ExternNode()
_NEEDS_LOADING = object() _ERR_MSG_PREFIX = "No module named " _ERR_MSG = _ERR_MSG_PREFIX + "{!r}" class _PathNode: pass class _PackageNode(_PathNode): def __init__(self, source_file: Optional[str]): self.source_file = source_file self.children: Dict[str, _PathNode] = {} class _ModuleNode(_PathNode): __slots__ = ["source_file"] def __init__(self, source_file: str): self.source_file = source_file class _ExternNode(_PathNode): pass # A private global registry of all modules that have been package-imported. _package_imported_modules: WeakValueDictionary = WeakValueDictionary() # `inspect` by default only looks in `sys.modules` to find source files for classes. # Patch it to check our private registry of package-imported modules as well. _orig_getfile = inspect.getfile def _patched_getfile(object): if inspect.isclass(object): if object.__module__ in _package_imported_modules: return _package_imported_modules[object.__module__].__file__ return _orig_getfile(object) inspect.getfile = _patched_getfile class _PackageResourceReader: """Private class used to support PackageImporter.get_resource_reader(). Confirms to the importlib.abc.ResourceReader interface. Allowed to access the innards of PackageImporter. """ def __init__(self, importer, fullname): self.importer = importer self.fullname = fullname def open_resource(self, resource): from io import BytesIO return BytesIO(self.importer.load_binary(self.fullname, resource)) def resource_path(self, resource): # The contract for resource_path is that it either returns a concrete # file system path or raises FileNotFoundError. if isinstance( self.importer.zip_reader, DirectoryReader ) and self.importer.zip_reader.has_record( os.path.join(self.fullname, resource) ): return os.path.join( self.importer.zip_reader.directory, self.fullname, resource ) raise FileNotFoundError def is_resource(self, name): path = self.importer._zipfile_path(self.fullname, name) return self.importer.zip_reader.has_record(path) def contents(self): from pathlib import Path filename = self.fullname.replace(".", "/") fullname_path = Path(self.importer._zipfile_path(self.fullname)) files = self.importer.zip_reader.get_all_records() subdirs_seen = set() for filename in files: try: relative = Path(filename).relative_to(fullname_path) except ValueError: continue # If the path of the file (which is relative to the top of the zip # namespace), relative to the package given when the resource # reader was created, has a parent, then it's a name in a # subdirectory and thus we skip it. parent_name = relative.parent.name if len(parent_name) == 0: yield relative.name elif parent_name not in subdirs_seen: subdirs_seen.add(parent_name) yield parent_name

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