torch/package/exporter.py - platform/external/pytorch - Git at Google

 import torch
 from torch.serialization import normalize_storage_type, location_tag, _should_read_directly
 import io
 import pickle
 import pickletools
 from .find_file_dependencies import find_files_source_depends_on
 from ._custom_import_pickler import CustomImportPickler
 from ._importlib import _normalize_path
 import types
 import importlib
 from typing import List, Any, Callable, Dict, Tuple
 from distutils.sysconfig import get_python_lib
 from pathlib import Path
 import linecache
 import sys
 from urllib.parse import quote

 class PackageExporter:
     """ Exporters allow you to write packages of code, pickled python data, and
     arbitrary binary and text resources into a self-contained package.

     Imports can load this code in a hermetic way, such that code is loaded
     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 code contained in packages is copied file-by-file from the original
     source when it is created, and the file format is a specially organized
     zip file. Future users of the package can unzip the package, and edit the code
     in order to perform custom modifications to it.

     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 using :method:`extern_module`.
     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.


     Dependencies
     ------------

     When source code is added to the package, the exporter optionally can scan it
     for further code dependencies (`dependencies=True`). It looks for import statements,
     resolves relative references to qualified module names, and calls :method:`require_module`
     on each it finds, recursively resolving dependencies.

     """

     importers: List[Callable[[str], Any]]
     """ A list of functions that will be called in order to find the module assocated
     with module names referenced by other modules or by pickled objects. Initialized to
     `[importlib.import_module]` by default. When pickling code or objects that was loaded
     from an imported packaged, that `importer.import_module` should be put into the importer list.
     When a name conflict occurs between importers, the first importer in the list takes precedence,
     and only objects that refer to this first importers class can be saved
     """


     def __init__(self, filename: str, verbose: bool = True):
         """
         Create an exporter.

         Args:
             filename: e.g. my_package.zip
             verbose: Print information about dependency resolution to stdout.
                 Useful for tracking down why certain files get included.
         """
         self.zip_file = torch._C.PyTorchFileWriter(filename)
         self.serialized_storages : Dict[str, Any] = {}
         self.external : List[str] = []
         self.provided : Dict[str, bool] = {}
         self.verbose = verbose
         self.importers = [importlib.import_module]
         self.debug_deps : List[Tuple[str, str]] = []

     def save_source_file(self, module_name: str, file_or_directory: str, dependencies=True):
         """Adds the local file system `file_or_directory` to the source package to provide the code
         for `module_name`.

         Args:
             module_name (str): e.g. `my_package.my_subpackage`, code will be saved to provide code for this package.
             file_or_directory (str): the path to a file or directory of code. When a directory, all python files in the directory
                 are recursively copied using :meth:`save_source_file`. If a file is named "/__init__.py" the code is treated
                 as a package.
             dependencies (bool, optional): If True, we scan the source for dependencies (see :ref:`Dependencies`).
         """
         path = Path(file_or_directory)
         if path.is_dir():
             to_save = []  # list of tuples with arguments to save_source_string
             module_path = module_name.replace('.', '/')
             for filename in path.glob('**/*.py'):
                 relative_path = filename.relative_to(path).as_posix()
                 archivename = module_path + '/' + relative_path
                 if filename.is_dir():
                     self.provided[archivename] = True
                 else:
                     submodule_name = None
                     if filename.name == '__init__.py':
                         submodule_name = archivename[:-len('/__init__.py')].replace('/', '.')
                         is_package = True
                     else:
                         submodule_name = archivename[:-len('.py')].replace('/', '.')
                         is_package = False

                     self.provided[submodule_name] = True
                     # we delay the call to save_source_string so that we record all the source files
                     # being provided by this directory structure _before_ attempting to resolve the dependencies
                     # on the source. This makes sure we don't try to copy over modules that will just get
                     # overwritten by this directory blob
                     to_save.append((submodule_name, _read_file(str(filename)), is_package, dependencies, str(filename)))

             for item in to_save:
                 self.save_source_string(*item)
         else:
             is_package = path.name == '__init__.py'
             self.save_source_string(module_name, _read_file(file_or_directory), is_package, dependencies, file_or_directory)

     def save_source_string(self, module_name: str, src: str, is_package: bool = False,
                            dependencies: bool = True, orig_file_name: str = None):
         """Adds `src` as the source code for `module_name` in the exported package.

         Args:
             module_name (str): e.g. `my_package.my_subpackage`, code will be saved to provide code for this package.
             src (str): The python source code to save for this package
             is_package (bool, optional): If True, this module is treated as a package. Packages are allowed to have submodules
                 (e.g. my_package.my_subpackage.my_subsubpackage), and resources can be saved inside them. Defaults to False.
             dependencies (bool, optional): If True, we scan the source for dependencies (see :ref:`Dependencies`).
             orig_file_name (str, optional): If present, used in logging to identifying where the source came from. Defaults to None.
         """
         self.provided[module_name] = True
         extension = '/__init__.py' if is_package else '.py'
         filename = module_name.replace('.', '/') + extension
         self._write(filename, src)
         if dependencies:
             package = module_name if is_package else module_name.rsplit('.', maxsplit=1)[0]
             dep_pairs = find_files_source_depends_on(src, package)
             dep_list = {}
             for dep_module_name, dep_module_obj in dep_pairs:
                 # handle the case where someone did something like `from pack import sub`
                 # where `sub` is a submodule. In this case we don't have to save pack, just sub.
                 # this ensures we don't pick up additional dependencies on pack.
                 # However, in the case where `sub` is not a submodule but an object, then we do have
                 # to save pack.
                 if dep_module_obj is not None:
                     possible_submodule = f'{dep_module_name}.{dep_module_obj}'
                     if self._module_exists(possible_submodule):
                         dep_list[possible_submodule] = True
                         # we don't need to save `pack`
                         continue
                 if self._module_exists(dep_module_name):
                     dep_list[dep_module_name] = True

             for dep in dep_list.keys():
                 self.debug_deps.append((module_name, dep))

             if self.verbose:
                 dep_str = ''.join(f'  {dep}\n' for dep in dep_list.keys())
                 file_info = f'(from file {orig_file_name}) ' if orig_file_name is not None else ''
                 print(f"{module_name} {file_info}depends on:\n{dep_str}\n")

             for dep in dep_list.keys():
                 self.require_module_if_not_provided(dep)

     def _module_exists(self, module_name: str) -> bool:
         try:
             self._import_module(module_name)
             return True
         except Exception:
             return False

     def _write_dep_graph(self, failing_module=None):
         edges = '\n'.join(f'"{f}" -> "{t}";' for f, t in self.debug_deps)
         failing = '' if failing_module is None else f'{failing_module} [color=red];'
         template = f"""\
 digraph G {{
 rankdir = LR;
 node [shape=box];
 {failing}
 {edges}
 }}
 """
         arg = quote(template, safe='')
         return f'https://dreampuf.github.io/GraphvizOnline/#{arg}'

     def _get_source_of_module(self, module: types.ModuleType) -> str:
         filename = getattr(module, '__file__', None)
         result = None if filename is None or not filename.endswith('.py') else linecache.getlines(filename, module.__dict__)
         if result is None:
             extra = ''
             if self.verbose:
                 extra = f' See the dependency graph for more info: {self._write_dep_graph(module.__name__)}'
             raise ValueError(f'cannot save source for module "{module.__name__}" because '
                              f'its source file "{filename}" could not be found.{extra}')
         return ''.join(result)

     def require_module_if_not_provided(self, module_name: str, dependencies=True):
         if self._module_is_already_provided(module_name):
             return
         self.require_module(module_name, dependencies)

     def require_module(self, module_name: str, dependencies=True):
         """This is called by dependencies resolution when it finds that something in the package
         depends on the module and it is not already present. It then decides how to provide that module.
         The default resolution rules will mark the module as extern if it is part of the standard library,
         and call `save_module` otherwise. Clients can subclass this object
         and override this method to provide other behavior, such as automatically mocking out a whole class
         of modules"""

         root_name = module_name.split('.', maxsplit=1)[0]
         if self._can_implicitly_extern(root_name):
             if self.verbose:
                 print(f'implicitly adding {root_name} to external modules '
                       f'since it is part of the standard library and is a dependency.')
             self.extern_module(root_name)
             return

         self.save_module(module_name, dependencies)

     def save_module(self, module_name: str, dependencies=True):
         """Save the code for `module_name` into the package. Code for the module is resolved using the `importers` path to find the
         module object, and then using its `__file__` attribute to find the source code.
         Args:
             module_name (str): e.g. `my_package.my_subpackage`, code will be saved to provide code for this package.
             dependencies (bool, optional): If True, we scan the source for dependencies (see :ref:`Dependencies`).
         """
         module = self._import_module(module_name)
         source = self._get_source_of_module(module)
         self.save_source_string(module_name, source, hasattr(module, '__path__'), dependencies, module.__file__)


     def _import_module(self, module_name):
         last_err = None
         for import_module in self.importers:
             try:
                 return import_module(module_name)
             except ModuleNotFoundError as err:
                 last_err = err

         if last_err is not None:
             raise last_err
         else:
             raise ModuleNotFoundError(module_name)

     def _create_pickler(self, data_buf):
         if self.importers == [importlib.import_module]:
             # if we are using the normal import library system, then
             # we can use the C implementation of pickle which is faster
             return pickle.Pickler(data_buf, protocol=3)
         else:
             return CustomImportPickler(self._import_module, data_buf, protocol=3)

     def save_pickle(self, package: str, resource: str, obj: Any, dependencies: bool = True):
         """Save a python object to the archive using pickle. Equivalent to :func:`torch.save` but saving into
         the archive rather than a stand-alone file. Stanard pickle does not save the code, only the objects.
         If `dependencies` is true, this method will also scan the pickled objects for which modules are required
         to reconstruct them and save the relevant code.

         To be able to save an object where `type(obj).__name__` is `my_module.MyObject`,
         `my_module.MyObject` must resolve to the class of the object according to the `importer` order. When saving objects that
         have previously been packaged, the importer's `import_module` method will need to be present in the `importer` list
         for this to work.

         Args:
             package (str): The name of module package this resource should go it (e.g. "my_package.my_subpackage")
             resource (str): A unique name for the resource, used to indentify it to load.
             obj (Any): The object to save, must be picklable.
             dependencies (bool, optional): If True, we scan the source for dependencies (see :ref:`Dependencies`).
         """
         filename = self._filename(package, resource)
         # Write the pickle data for `obj`
         data_buf = io.BytesIO()
         pickler = self._create_pickler(data_buf)
         pickler.persistent_id = self._persistent_id
         pickler.dump(obj)
         data_value = data_buf.getvalue()

         if dependencies:
             all_dependencies = []
             for opcode, arg, pos in pickletools.genops(data_value):
                 if opcode.name == 'GLOBAL':  # a global reference
                     assert isinstance(arg, str)
                     module, field = arg.split(' ')
                     if module not in all_dependencies:
                         all_dependencies.append(module)

             for dep in all_dependencies:
                 self.debug_deps.append((package + '.' + resource, dep))

             if self.verbose:
                 dep_string = ''.join(f'  {dep}\n' for dep in all_dependencies)
                 print(f"{resource} depends on:\n{dep_string}\n")

             for module_name in all_dependencies:
                 self.require_module_if_not_provided(module_name)

         self._write(filename, data_value)

     def save_text(self, package: str, resource: str, text: str):
         """Save text data to the package

         Args:
             package (str): The name of module package this resource should go it (e.g. "my_package.my_subpackage")
             resource (str): A unique name for the resource, used to indentify it to load.
             text (str): The contents to save
         """
         return self.save_binary(package, resource, text.encode('utf-8'))

     def save_binary(self, package, resource, binary: bytes):
         """Save raw bytes to the package.

         Args:
             package (str): The name of module package this resource should go it (e.g. "my_package.my_subpackage")
             resource (str): A unique name for the resource, used to indentify it to load.
             binary (str): The data to save.
         """
         filename = self._filename(package, resource)
         self._write(filename, binary)

     def extern_module(self, module_name: str):
         """Include `module` in the list of external modules the package can import.
         This will prevent dependency discover from saving
         it in the package. The importer will load an external module directly from the standard import system.
         Code for extern modules must also exist in the process loading the package.

         Args:
             module_name (str): e.g. "my_package.my_subpackage" the name of the external module
         """
         if module_name not in self.external:
             self.external.append(module_name)

     def extern_modules(self, module_names: List[str]):
         """Extern a list of modules. Convience wrapper for calling :meth:`extern_module` on many items.

         Args:
             module_names (List[str]): List of module names
         """
         for m in module_names:
             self.extern_module(m)

     def mock_module(self, module_name: str):
         """Replace the code for `module_name` in the package with a fake implementation. This module will return a fake
         object for any attribute accessed from it. Because we copy file-by-file, the dependency resolution will sometimes
         find files that are imported by model files but whose functionality is never used
         (e.g. custom serialization code or training helpers).
         Use this function to mock this functionality out without having to modify the original code.

         Args:
             module_name (str): e.g. "my_package.my_subpackage" the name of the module to be mocked out.
         """
         if '_mock' not in self.provided:
             self.save_source_file('_mock', str(Path(__file__).parent / '_mock.py'), dependencies=False)
         is_package = hasattr(self._import_module(module_name), '__path__')
         self.save_source_string(module_name, _MOCK_IMPL, is_package, dependencies=False)


     def mock_modules(self, module_names):
         """Mock a list of modules. Convience wrapper for calling :meth:`mock_module` on many items.

         Args:
             module_names (List[str]): List of module names
         """
         for module_name in module_names:
             self.mock_module(module_name)

     def _module_is_already_provided(self, qualified_name: str) -> bool:
         for mod in self.external:
             if qualified_name == mod or qualified_name.startswith(mod + '.'):
                 return True
         return qualified_name in self.provided

     def _persistent_id(self, obj):
         # FIXME: the docs say that persistent_id should only return a string
         # but torch store returns tuples. This works only in the binary protocol
         # see
         # https://docs.python.org/2/library/pickle.html#pickling-and-unpickling-external-objects
         # https://github.com/python/cpython/blob/master/Lib/pickle.py#L527-L537
         if torch.is_storage(obj):
             storage_type = normalize_storage_type(type(obj))
             obj_key = str(obj._cdata)
             location = location_tag(obj)
             self.serialized_storages[obj_key] = obj

             return ('storage',
                     storage_type,
                     obj_key,
                     location,
                     obj.size())
         return None

     def __enter__(self):
         return self

     def __exit__(self, type, value, traceback):
         self.close()

     def _write(self, filename, str_or_bytes):
         if isinstance(str_or_bytes, str):
             str_or_bytes = str_or_bytes.encode('utf-8')
         self.zip_file.write_record(filename, str_or_bytes, len(str_or_bytes))

     def close(self):
         """Write the package to the filesystem. Any calls after close are now invalid.
         It is preferable to use resource guard syntax instead:

             with PackageExporter("file.zip") as e:
                 ...
         """
         if self.verbose:
             print(f"Dependency graph for exported package: {self._write_dep_graph()}")

         # Write each tensor to a file named tensor/the_tensor_key in the zip archive
         for key in sorted(self.serialized_storages.keys()):
             name = 'data/{}'.format(key)
             storage = self.serialized_storages[key]
             if storage.device.type == 'cpu':
                 # If it's on the CPU we can directly copy it into the zip file
                 num_bytes = storage.size() * storage.element_size()
                 self.zip_file.write_record(name, storage.data_ptr(), num_bytes)
             else:
                 # Copy to a buffer, then serialize that
                 buf = io.BytesIO()
                 storage._write_file(buf, _should_read_directly(buf))
                 buf_value = buf.getvalue()
                 self._write(name, buf_value)
         contents = ('\n'.join(self.external) + '\n')
         self._write('extern_modules', contents)
         del self.zip_file


     def _filename(self, package, resource):
         package_path = package.replace('.', '/')
         resource = _normalize_path(resource)
         return f'{package_path}/{resource}'

     def _can_implicitly_extern(self, module_name: str):
         return module_name == 'torch' or (module_name not in _DISALLOWED_MODULES
                                           and _is_builtin_or_stdlib_module(self._import_module(module_name)))


 # even though these are in the standard library, we do not allow them to be
 # automatically externed since they offer a lot of system level access
 _DISALLOWED_MODULES = ['sys', 'io']

 def _is_builtin_or_stdlib_module(module: types.ModuleType) -> bool:
     if module.__name__ in sys.builtin_module_names:
         return True
     filename = getattr(module, '__file__', None)
     if filename is None:
         return False
     standard_lib = get_python_lib(standard_lib=True)
     # this is often a subdirectory of standard_lib so we have to check
     # that the file is in the standard_lib directory but not in this one
     installed_libs = get_python_lib(standard_lib=False)
     in_standard_lib = filename.startswith(standard_lib + '/')
     in_installed_libs = filename.startswith(installed_libs + '/')
     return in_standard_lib and not in_installed_libs

 _MOCK_IMPL = """\
 from _mock import MockedObject
 def __getattr__(attr: str):
     return MockedObject(__name__ + '.' + attr)
 """

 def _read_file(filename: str) -> str:
     with open(filename, 'rb') as f:
         b = f.read()
         return b.decode('utf-8')
	import torch
	from torch.serialization import normalize_storage_type, location_tag, _should_read_directly
	import io
	import pickle
	import pickletools
	from .find_file_dependencies import find_files_source_depends_on
	from ._custom_import_pickler import CustomImportPickler
	from ._importlib import _normalize_path
	import types
	import importlib
	from typing import List, Any, Callable, Dict, Tuple
	from distutils.sysconfig import get_python_lib
	from pathlib import Path
	import linecache
	import sys
	from urllib.parse import quote

	class PackageExporter:
	""" Exporters allow you to write packages of code, pickled python data, and
	arbitrary binary and text resources into a self-contained package.

	Imports can load this code in a hermetic way, such that code is loaded
	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 code contained in packages is copied file-by-file from the original
	source when it is created, and the file format is a specially organized
	zip file. Future users of the package can unzip the package, and edit the code
	in order to perform custom modifications to it.

	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 using :method:`extern_module`.
	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.


	Dependencies
	------------

	When source code is added to the package, the exporter optionally can scan it
	for further code dependencies (`dependencies=True`). It looks for import statements,
	resolves relative references to qualified module names, and calls :method:`require_module`
	on each it finds, recursively resolving dependencies.

	"""

	importers: List[Callable[[str], Any]]
	""" A list of functions that will be called in order to find the module assocated
	with module names referenced by other modules or by pickled objects. Initialized to
	`[importlib.import_module]` by default. When pickling code or objects that was loaded
	from an imported packaged, that `importer.import_module` should be put into the importer list.
	When a name conflict occurs between importers, the first importer in the list takes precedence,
	and only objects that refer to this first importers class can be saved
	"""


	def __init__(self, filename: str, verbose: bool = True):
	"""
	Create an exporter.

	Args:
	filename: e.g. my_package.zip
	verbose: Print information about dependency resolution to stdout.
	Useful for tracking down why certain files get included.
	"""
	self.zip_file = torch._C.PyTorchFileWriter(filename)
	self.serialized_storages : Dict[str, Any] = {}
	self.external : List[str] = []
	self.provided : Dict[str, bool] = {}
	self.verbose = verbose
	self.importers = [importlib.import_module]
	self.debug_deps : List[Tuple[str, str]] = []

	def save_source_file(self, module_name: str, file_or_directory: str, dependencies=True):
	"""Adds the local file system `file_or_directory` to the source package to provide the code
	for `module_name`.

	Args:
	module_name (str): e.g. `my_package.my_subpackage`, code will be saved to provide code for this package.
	file_or_directory (str): the path to a file or directory of code. When a directory, all python files in the directory
	are recursively copied using :meth:`save_source_file`. If a file is named "/__init__.py" the code is treated
	as a package.
	dependencies (bool, optional): If True, we scan the source for dependencies (see :ref:`Dependencies`).
	"""
	path = Path(file_or_directory)
	if path.is_dir():
	to_save = [] # list of tuples with arguments to save_source_string
	module_path = module_name.replace('.', '/')
	for filename in path.glob('*/.py'):
	relative_path = filename.relative_to(path).as_posix()
	archivename = module_path + '/' + relative_path
	if filename.is_dir():
	self.provided[archivename] = True
	else:
	submodule_name = None
	if filename.name == '__init__.py':
	submodule_name = archivename[:-len('/__init__.py')].replace('/', '.')
	is_package = True
	else:
	submodule_name = archivename[:-len('.py')].replace('/', '.')
	is_package = False

	self.provided[submodule_name] = True
	# we delay the call to save_source_string so that we record all the source files
	# being provided by this directory structure _before_ attempting to resolve the dependencies
	# on the source. This makes sure we don't try to copy over modules that will just get
	# overwritten by this directory blob
	to_save.append((submodule_name, _read_file(str(filename)), is_package, dependencies, str(filename)))

	for item in to_save:
	self.save_source_string(*item)
	else:
	is_package = path.name == '__init__.py'
	self.save_source_string(module_name, _read_file(file_or_directory), is_package, dependencies, file_or_directory)

	def save_source_string(self, module_name: str, src: str, is_package: bool = False,
	dependencies: bool = True, orig_file_name: str = None):
	"""Adds `src` as the source code for `module_name` in the exported package.

	Args:
	module_name (str): e.g. `my_package.my_subpackage`, code will be saved to provide code for this package.
	src (str): The python source code to save for this package
	is_package (bool, optional): If True, this module is treated as a package. Packages are allowed to have submodules
	(e.g. my_package.my_subpackage.my_subsubpackage), and resources can be saved inside them. Defaults to False.
	dependencies (bool, optional): If True, we scan the source for dependencies (see :ref:`Dependencies`).
	orig_file_name (str, optional): If present, used in logging to identifying where the source came from. Defaults to None.
	"""
	self.provided[module_name] = True
	extension = '/__init__.py' if is_package else '.py'
	filename = module_name.replace('.', '/') + extension
	self._write(filename, src)
	if dependencies:
	package = module_name if is_package else module_name.rsplit('.', maxsplit=1)[0]
	dep_pairs = find_files_source_depends_on(src, package)
	dep_list = {}
	for dep_module_name, dep_module_obj in dep_pairs:
	# handle the case where someone did something like `from pack import sub`
	# where `sub` is a submodule. In this case we don't have to save pack, just sub.
	# this ensures we don't pick up additional dependencies on pack.
	# However, in the case where `sub` is not a submodule but an object, then we do have
	# to save pack.
	if dep_module_obj is not None:
	possible_submodule = f'{dep_module_name}.{dep_module_obj}'
	if self._module_exists(possible_submodule):
	dep_list[possible_submodule] = True
	# we don't need to save `pack`
	continue
	if self._module_exists(dep_module_name):
	dep_list[dep_module_name] = True

	for dep in dep_list.keys():
	self.debug_deps.append((module_name, dep))

	if self.verbose:
	dep_str = ''.join(f' {dep}\n' for dep in dep_list.keys())
	file_info = f'(from file {orig_file_name}) ' if orig_file_name is not None else ''
	print(f"{module_name} {file_info}depends on:\n{dep_str}\n")

	for dep in dep_list.keys():
	self.require_module_if_not_provided(dep)

	def _module_exists(self, module_name: str) -> bool:
	try:
	self._import_module(module_name)
	return True
	except Exception:
	return False

	def _write_dep_graph(self, failing_module=None):
	edges = '\n'.join(f'"{f}" -> "{t}";' for f, t in self.debug_deps)
	failing = '' if failing_module is None else f'{failing_module} [color=red];'
	template = f"""\
	digraph G {{
	rankdir = LR;
	node [shape=box];
	{failing}
	{edges}
	}}
	"""
	arg = quote(template, safe='')
	return f'https://dreampuf.github.io/GraphvizOnline/#{arg}'

	def _get_source_of_module(self, module: types.ModuleType) -> str:
	filename = getattr(module, '__file__', None)
	result = None if filename is None or not filename.endswith('.py') else linecache.getlines(filename, module.__dict__)
	if result is None:
	extra = ''
	if self.verbose:
	extra = f' See the dependency graph for more info: {self._write_dep_graph(module.__name__)}'
	raise ValueError(f'cannot save source for module "{module.__name__}" because '
	f'its source file "{filename}" could not be found.{extra}')
	return ''.join(result)

	def require_module_if_not_provided(self, module_name: str, dependencies=True):
	if self._module_is_already_provided(module_name):
	return
	self.require_module(module_name, dependencies)

	def require_module(self, module_name: str, dependencies=True):
	"""This is called by dependencies resolution when it finds that something in the package
	depends on the module and it is not already present. It then decides how to provide that module.
	The default resolution rules will mark the module as extern if it is part of the standard library,
	and call `save_module` otherwise. Clients can subclass this object
	and override this method to provide other behavior, such as automatically mocking out a whole class
	of modules"""

	root_name = module_name.split('.', maxsplit=1)[0]
	if self._can_implicitly_extern(root_name):
	if self.verbose:
	print(f'implicitly adding {root_name} to external modules '
	f'since it is part of the standard library and is a dependency.')
	self.extern_module(root_name)
	return

	self.save_module(module_name, dependencies)

	def save_module(self, module_name: str, dependencies=True):
	"""Save the code for `module_name` into the package. Code for the module is resolved using the `importers` path to find the
	module object, and then using its `__file__` attribute to find the source code.
	Args:
	module_name (str): e.g. `my_package.my_subpackage`, code will be saved to provide code for this package.
	dependencies (bool, optional): If True, we scan the source for dependencies (see :ref:`Dependencies`).
	"""
	module = self._import_module(module_name)
	source = self._get_source_of_module(module)
	self.save_source_string(module_name, source, hasattr(module, '__path__'), dependencies, module.__file__)


	def _import_module(self, module_name):
	last_err = None
	for import_module in self.importers:
	try:
	return import_module(module_name)
	except ModuleNotFoundError as err:
	last_err = err

	if last_err is not None:
	raise last_err
	else:
	raise ModuleNotFoundError(module_name)

	def _create_pickler(self, data_buf):
	if self.importers == [importlib.import_module]:
	# if we are using the normal import library system, then
	# we can use the C implementation of pickle which is faster
	return pickle.Pickler(data_buf, protocol=3)
	else:
	return CustomImportPickler(self._import_module, data_buf, protocol=3)

	def save_pickle(self, package: str, resource: str, obj: Any, dependencies: bool = True):
	"""Save a python object to the archive using pickle. Equivalent to :func:`torch.save` but saving into
	the archive rather than a stand-alone file. Stanard pickle does not save the code, only the objects.
	If `dependencies` is true, this method will also scan the pickled objects for which modules are required
	to reconstruct them and save the relevant code.

	To be able to save an object where `type(obj).__name__` is `my_module.MyObject`,
	`my_module.MyObject` must resolve to the class of the object according to the `importer` order. When saving objects that
	have previously been packaged, the importer's `import_module` method will need to be present in the `importer` list
	for this to work.

	Args:
	package (str): The name of module package this resource should go it (e.g. "my_package.my_subpackage")
	resource (str): A unique name for the resource, used to indentify it to load.
	obj (Any): The object to save, must be picklable.
	dependencies (bool, optional): If True, we scan the source for dependencies (see :ref:`Dependencies`).
	"""
	filename = self._filename(package, resource)
	# Write the pickle data for `obj`
	data_buf = io.BytesIO()
	pickler = self._create_pickler(data_buf)
	pickler.persistent_id = self._persistent_id
	pickler.dump(obj)
	data_value = data_buf.getvalue()

	if dependencies:
	all_dependencies = []
	for opcode, arg, pos in pickletools.genops(data_value):
	if opcode.name == 'GLOBAL': # a global reference
	assert isinstance(arg, str)
	module, field = arg.split(' ')
	if module not in all_dependencies:
	all_dependencies.append(module)

	for dep in all_dependencies:
	self.debug_deps.append((package + '.' + resource, dep))

	if self.verbose:
	dep_string = ''.join(f' {dep}\n' for dep in all_dependencies)
	print(f"{resource} depends on:\n{dep_string}\n")

	for module_name in all_dependencies:
	self.require_module_if_not_provided(module_name)

	self._write(filename, data_value)

	def save_text(self, package: str, resource: str, text: str):
	"""Save text data to the package

	Args:
	package (str): The name of module package this resource should go it (e.g. "my_package.my_subpackage")
	resource (str): A unique name for the resource, used to indentify it to load.
	text (str): The contents to save
	"""
	return self.save_binary(package, resource, text.encode('utf-8'))

	def save_binary(self, package, resource, binary: bytes):
	"""Save raw bytes to the package.

	Args:
	package (str): The name of module package this resource should go it (e.g. "my_package.my_subpackage")
	resource (str): A unique name for the resource, used to indentify it to load.
	binary (str): The data to save.
	"""
	filename = self._filename(package, resource)
	self._write(filename, binary)

	def extern_module(self, module_name: str):
	"""Include `module` in the list of external modules the package can import.
	This will prevent dependency discover from saving
	it in the package. The importer will load an external module directly from the standard import system.
	Code for extern modules must also exist in the process loading the package.

	Args:
	module_name (str): e.g. "my_package.my_subpackage" the name of the external module
	"""
	if module_name not in self.external:
	self.external.append(module_name)

	def extern_modules(self, module_names: List[str]):
	"""Extern a list of modules. Convience wrapper for calling :meth:`extern_module` on many items.

	Args:
	module_names (List[str]): List of module names
	"""
	for m in module_names:
	self.extern_module(m)

	def mock_module(self, module_name: str):
	"""Replace the code for `module_name` in the package with a fake implementation. This module will return a fake
	object for any attribute accessed from it. Because we copy file-by-file, the dependency resolution will sometimes
	find files that are imported by model files but whose functionality is never used
	(e.g. custom serialization code or training helpers).
	Use this function to mock this functionality out without having to modify the original code.

	Args:
	module_name (str): e.g. "my_package.my_subpackage" the name of the module to be mocked out.
	"""
	if '_mock' not in self.provided:
	self.save_source_file('_mock', str(Path(__file__).parent / '_mock.py'), dependencies=False)
	is_package = hasattr(self._import_module(module_name), '__path__')
	self.save_source_string(module_name, _MOCK_IMPL, is_package, dependencies=False)


	def mock_modules(self, module_names):
	"""Mock a list of modules. Convience wrapper for calling :meth:`mock_module` on many items.

	Args:
	module_names (List[str]): List of module names
	"""
	for module_name in module_names:
	self.mock_module(module_name)

	def _module_is_already_provided(self, qualified_name: str) -> bool:
	for mod in self.external:
	if qualified_name == mod or qualified_name.startswith(mod + '.'):
	return True
	return qualified_name in self.provided

	def _persistent_id(self, obj):
	# FIXME: the docs say that persistent_id should only return a string
	# but torch store returns tuples. This works only in the binary protocol
	# see
	# https://docs.python.org/2/library/pickle.html#pickling-and-unpickling-external-objects
	# https://github.com/python/cpython/blob/master/Lib/pickle.py#L527-L537
	if torch.is_storage(obj):
	storage_type = normalize_storage_type(type(obj))
	obj_key = str(obj._cdata)
	location = location_tag(obj)
	self.serialized_storages[obj_key] = obj

	return ('storage',
	storage_type,
	obj_key,
	location,
	obj.size())
	return None

	def __enter__(self):
	return self

	def __exit__(self, type, value, traceback):
	self.close()

	def _write(self, filename, str_or_bytes):
	if isinstance(str_or_bytes, str):
	str_or_bytes = str_or_bytes.encode('utf-8')
	self.zip_file.write_record(filename, str_or_bytes, len(str_or_bytes))

	def close(self):
	"""Write the package to the filesystem. Any calls after close are now invalid.
	It is preferable to use resource guard syntax instead:

	with PackageExporter("file.zip") as e:
	...
	"""
	if self.verbose:
	print(f"Dependency graph for exported package: {self._write_dep_graph()}")

	# Write each tensor to a file named tensor/the_tensor_key in the zip archive
	for key in sorted(self.serialized_storages.keys()):
	name = 'data/{}'.format(key)
	storage = self.serialized_storages[key]
	if storage.device.type == 'cpu':
	# If it's on the CPU we can directly copy it into the zip file
	num_bytes = storage.size() * storage.element_size()
	self.zip_file.write_record(name, storage.data_ptr(), num_bytes)
	else:
	# Copy to a buffer, then serialize that
	buf = io.BytesIO()
	storage._write_file(buf, _should_read_directly(buf))
	buf_value = buf.getvalue()
	self._write(name, buf_value)
	contents = ('\n'.join(self.external) + '\n')
	self._write('extern_modules', contents)
	del self.zip_file


	def _filename(self, package, resource):
	package_path = package.replace('.', '/')
	resource = _normalize_path(resource)
	return f'{package_path}/{resource}'

	def _can_implicitly_extern(self, module_name: str):
	return module_name == 'torch' or (module_name not in _DISALLOWED_MODULES
	and _is_builtin_or_stdlib_module(self._import_module(module_name)))


	# even though these are in the standard library, we do not allow them to be
	# automatically externed since they offer a lot of system level access
	_DISALLOWED_MODULES = ['sys', 'io']

	def _is_builtin_or_stdlib_module(module: types.ModuleType) -> bool:
	if module.__name__ in sys.builtin_module_names:
	return True
	filename = getattr(module, '__file__', None)
	if filename is None:
	return False
	standard_lib = get_python_lib(standard_lib=True)
	# this is often a subdirectory of standard_lib so we have to check
	# that the file is in the standard_lib directory but not in this one
	installed_libs = get_python_lib(standard_lib=False)
	in_standard_lib = filename.startswith(standard_lib + '/')
	in_installed_libs = filename.startswith(installed_libs + '/')
	return in_standard_lib and not in_installed_libs

	_MOCK_IMPL = """\
	from _mock import MockedObject
	def __getattr__(attr: str):
	return MockedObject(__name__ + '.' + attr)
	"""

	def _read_file(filename: str) -> str:
	with open(filename, 'rb') as f:
	b = f.read()
	return b.decode('utf-8')