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+.venv/Scripts/transformers-cli.exe filter=lfs diff=lfs merge=lfs -text
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.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml

.idea/.name

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+activate_this.py

.idea/PythonProject1.iml

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+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.13 (PythonProject1)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

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+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.13 (PythonProject1)" />
+  </component>
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/PythonProject1.iml" filepath="$PROJECT_DIR$/.idea/PythonProject1.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$/transformers" vcs="Git" />
+  </component>
+</project>

.idea/workspace.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="AutoImportSettings">
+    <option name="autoReloadType" value="SELECTIVE" />
+  </component>
+  <component name="ChangeListManager">
+    <list default="true" id="e1ca9eab-780d-4022-8547-846f10a707ca" name="Changes" comment="" />
+    <option name="SHOW_DIALOG" value="false" />
+    <option name="HIGHLIGHT_CONFLICTS" value="true" />
+    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
+    <option name="LAST_RESOLUTION" value="IGNORE" />
+  </component>
+  <component name="FileTemplateManagerImpl">
+    <option name="RECENT_TEMPLATES">
+      <list>
+        <option value="Python Script" />
+      </list>
+    </option>
+  </component>
+  <component name="HighlightingSettingsPerFile">
+    <setting file="file://$PROJECT_DIR$/.venv/PythonProjectFile1.py" root0="SKIP_INSPECTION" />
+  </component>
+  <component name="ProjectColorInfo">{
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+}</component>
+  <component name="ProjectId" id="2tBGyUhll7hTnhrUSkmyqZXcHMI" />
+  <component name="ProjectViewState">
+    <option name="autoscrollFromSource" value="true" />
+    <option name="hideEmptyMiddlePackages" value="true" />
+    <option name="showLibraryContents" value="true" />
+  </component>
+  <component name="PropertiesComponent"><![CDATA[{
+  "keyToString": {
+    "Python.PythonProjectFile1.executor": "Run",
+    "Python.PythonProjectFile2.executor": "Run",
+    "RunOnceActivity.ShowReadmeOnStart": "true",
+    "ignore.virus.scanning.warn.message": "true",
+    "last_opened_file_path": "C:/Users/Joshua Davis/PycharmProjects/PythonProject1"
+  }
+}]]></component>
+  <component name="SharedIndexes">
+    <attachedChunks>
+      <set>
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+  </component>
+  <component name="SpellCheckerSettings" RuntimeDictionaries="0" Folders="0" CustomDictionaries="0" DefaultDictionary="application-level" UseSingleDictionary="true" transferred="true" />
+  <component name="TaskManager">
+    <task active="true" id="Default" summary="Default task">
+      <changelist id="e1ca9eab-780d-4022-8547-846f10a707ca" name="Changes" comment="" />
+      <created>1739818308621</created>
+      <option name="number" value="Default" />
+      <option name="presentableId" value="Default" />
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+    </task>
+    <servers />
+  </component>
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.venv/.gitignore

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+# Created by venv; see https://docs.python.org/3/library/venv.html
+*

.venv/Lib/site-packages/MarkupSafe-3.0.2.dist-info/INSTALLER

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+pip

.venv/Lib/site-packages/MarkupSafe-3.0.2.dist-info/LICENSE.txt

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+Copyright 2010 Pallets
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+1.  Redistributions of source code must retain the above copyright
+    notice, this list of conditions and the following disclaimer.
+
+2.  Redistributions in binary form must reproduce the above copyright
+    notice, this list of conditions and the following disclaimer in the
+    documentation and/or other materials provided with the distribution.
+
+3.  Neither the name of the copyright holder nor the names of its
+    contributors may be used to endorse or promote products derived from
+    this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
+PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
+TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

.venv/Lib/site-packages/MarkupSafe-3.0.2.dist-info/METADATA

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+Metadata-Version: 2.1
+Name: MarkupSafe
+Version: 3.0.2
+Summary: Safely add untrusted strings to HTML/XML markup.
+Maintainer-email: Pallets <contact@palletsprojects.com>
+License: Copyright 2010 Pallets
+        
+        Redistribution and use in source and binary forms, with or without
+        modification, are permitted provided that the following conditions are
+        met:
+        
+        1.  Redistributions of source code must retain the above copyright
+            notice, this list of conditions and the following disclaimer.
+        
+        2.  Redistributions in binary form must reproduce the above copyright
+            notice, this list of conditions and the following disclaimer in the
+            documentation and/or other materials provided with the distribution.
+        
+        3.  Neither the name of the copyright holder nor the names of its
+            contributors may be used to endorse or promote products derived from
+            this software without specific prior written permission.
+        
+        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+        "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+        LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
+        PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+        HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+        SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
+        TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+        PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+        LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+        NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+        SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+        
+Project-URL: Donate, https://palletsprojects.com/donate
+Project-URL: Documentation, https://markupsafe.palletsprojects.com/
+Project-URL: Changes, https://markupsafe.palletsprojects.com/changes/
+Project-URL: Source, https://github.com/pallets/markupsafe/
+Project-URL: Chat, https://discord.gg/pallets
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Web Environment
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python
+Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
+Classifier: Topic :: Text Processing :: Markup :: HTML
+Classifier: Typing :: Typed
+Requires-Python: >=3.9
+Description-Content-Type: text/markdown
+License-File: LICENSE.txt
+
+# MarkupSafe
+
+MarkupSafe implements a text object that escapes characters so it is
+safe to use in HTML and XML. Characters that have special meanings are
+replaced so that they display as the actual characters. This mitigates
+injection attacks, meaning untrusted user input can safely be displayed
+on a page.
+
+
+## Examples
+
+```pycon
+>>> from markupsafe import Markup, escape
+
+>>> # escape replaces special characters and wraps in Markup
+>>> escape("<script>alert(document.cookie);</script>")
+Markup('&lt;script&gt;alert(document.cookie);&lt;/script&gt;')
+
+>>> # wrap in Markup to mark text "safe" and prevent escaping
+>>> Markup("<strong>Hello</strong>")
+Markup('<strong>hello</strong>')
+
+>>> escape(Markup("<strong>Hello</strong>"))
+Markup('<strong>hello</strong>')
+
+>>> # Markup is a str subclass
+>>> # methods and operators escape their arguments
+>>> template = Markup("Hello <em>{name}</em>")
+>>> template.format(name='"World"')
+Markup('Hello <em>&#34;World&#34;</em>')
+```
+
+## Donate
+
+The Pallets organization develops and supports MarkupSafe and other
+popular packages. In order to grow the community of contributors and
+users, and allow the maintainers to devote more time to the projects,
+[please donate today][].
+
+[please donate today]: https://palletsprojects.com/donate

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.venv/Lib/site-packages/PyYAML-6.0.2.dist-info/INSTALLER

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.venv/Lib/site-packages/PyYAML-6.0.2.dist-info/LICENSE

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+Copyright (c) 2017-2021 Ingy döt Net
+Copyright (c) 2006-2016 Kirill Simonov
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+of the Software, and to permit persons to whom the Software is furnished to do
+so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

.venv/Lib/site-packages/PyYAML-6.0.2.dist-info/METADATA

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+Metadata-Version: 2.1
+Name: PyYAML
+Version: 6.0.2
+Summary: YAML parser and emitter for Python
+Home-page: https://pyyaml.org/
+Download-URL: https://pypi.org/project/PyYAML/
+Author: Kirill Simonov
+Author-email: xi@resolvent.net
+License: MIT
+Project-URL: Bug Tracker, https://github.com/yaml/pyyaml/issues
+Project-URL: CI, https://github.com/yaml/pyyaml/actions
+Project-URL: Documentation, https://pyyaml.org/wiki/PyYAMLDocumentation
+Project-URL: Mailing lists, http://lists.sourceforge.net/lists/listinfo/yaml-core
+Project-URL: Source Code, https://github.com/yaml/pyyaml
+Platform: Any
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Cython
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Classifier: Topic :: Text Processing :: Markup
+Requires-Python: >=3.8
+License-File: LICENSE
+
+YAML is a data serialization format designed for human readability
+and interaction with scripting languages.  PyYAML is a YAML parser
+and emitter for Python.
+
+PyYAML features a complete YAML 1.1 parser, Unicode support, pickle
+support, capable extension API, and sensible error messages.  PyYAML
+supports standard YAML tags and provides Python-specific tags that
+allow to represent an arbitrary Python object.
+
+PyYAML is applicable for a broad range of tasks from complex
+configuration files to object serialization and persistence.

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+

.venv/Lib/site-packages/PyYAML-6.0.2.dist-info/top_level.txt

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+yaml

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.venv/Lib/site-packages/_distutils_hack/__init__.py

@@ -0,0 +1,239 @@
+# don't import any costly modules
+import os
+import sys
+
+report_url = (
+    "https://github.com/pypa/setuptools/issues/new?template=distutils-deprecation.yml"
+)
+
+
+def warn_distutils_present():
+    if 'distutils' not in sys.modules:
+        return
+    import warnings
+
+    warnings.warn(
+        "Distutils was imported before Setuptools, but importing Setuptools "
+        "also replaces the `distutils` module in `sys.modules`. This may lead "
+        "to undesirable behaviors or errors. To avoid these issues, avoid "
+        "using distutils directly, ensure that setuptools is installed in the "
+        "traditional way (e.g. not an editable install), and/or make sure "
+        "that setuptools is always imported before distutils."
+    )
+
+
+def clear_distutils():
+    if 'distutils' not in sys.modules:
+        return
+    import warnings
+
+    warnings.warn(
+        "Setuptools is replacing distutils. Support for replacing "
+        "an already imported distutils is deprecated. In the future, "
+        "this condition will fail. "
+        f"Register concerns at {report_url}"
+    )
+    mods = [
+        name
+        for name in sys.modules
+        if name == "distutils" or name.startswith("distutils.")
+    ]
+    for name in mods:
+        del sys.modules[name]
+
+
+def enabled():
+    """
+    Allow selection of distutils by environment variable.
+    """
+    which = os.environ.get('SETUPTOOLS_USE_DISTUTILS', 'local')
+    if which == 'stdlib':
+        import warnings
+
+        warnings.warn(
+            "Reliance on distutils from stdlib is deprecated. Users "
+            "must rely on setuptools to provide the distutils module. "
+            "Avoid importing distutils or import setuptools first, "
+            "and avoid setting SETUPTOOLS_USE_DISTUTILS=stdlib. "
+            f"Register concerns at {report_url}"
+        )
+    return which == 'local'
+
+
+def ensure_local_distutils():
+    import importlib
+
+    clear_distutils()
+
+    # With the DistutilsMetaFinder in place,
+    # perform an import to cause distutils to be
+    # loaded from setuptools._distutils. Ref #2906.
+    with shim():
+        importlib.import_module('distutils')
+
+    # check that submodules load as expected
+    core = importlib.import_module('distutils.core')
+    assert '_distutils' in core.__file__, core.__file__
+    assert 'setuptools._distutils.log' not in sys.modules
+
+
+def do_override():
+    """
+    Ensure that the local copy of distutils is preferred over stdlib.
+
+    See https://github.com/pypa/setuptools/issues/417#issuecomment-392298401
+    for more motivation.
+    """
+    if enabled():
+        warn_distutils_present()
+        ensure_local_distutils()
+
+
+class _TrivialRe:
+    def __init__(self, *patterns) -> None:
+        self._patterns = patterns
+
+    def match(self, string):
+        return all(pat in string for pat in self._patterns)
+
+
+class DistutilsMetaFinder:
+    def find_spec(self, fullname, path, target=None):
+        # optimization: only consider top level modules and those
+        # found in the CPython test suite.
+        if path is not None and not fullname.startswith('test.'):
+            return None
+
+        method_name = 'spec_for_{fullname}'.format(**locals())
+        method = getattr(self, method_name, lambda: None)
+        return method()
+
+    def spec_for_distutils(self):
+        if self.is_cpython():
+            return None
+
+        import importlib
+        import importlib.abc
+        import importlib.util
+
+        try:
+            mod = importlib.import_module('setuptools._distutils')
+        except Exception:
+            # There are a couple of cases where setuptools._distutils
+            # may not be present:
+            # - An older Setuptools without a local distutils is
+            #   taking precedence. Ref #2957.
+            # - Path manipulation during sitecustomize removes
+            #   setuptools from the path but only after the hook
+            #   has been loaded. Ref #2980.
+            # In either case, fall back to stdlib behavior.
+            return None
+
+        class DistutilsLoader(importlib.abc.Loader):
+            def create_module(self, spec):
+                mod.__name__ = 'distutils'
+                return mod
+
+            def exec_module(self, module):
+                pass
+
+        return importlib.util.spec_from_loader(
+            'distutils', DistutilsLoader(), origin=mod.__file__
+        )
+
+    @staticmethod
+    def is_cpython():
+        """
+        Suppress supplying distutils for CPython (build and tests).
+        Ref #2965 and #3007.
+        """
+        return os.path.isfile('pybuilddir.txt')
+
+    def spec_for_pip(self):
+        """
+        Ensure stdlib distutils when running under pip.
+        See pypa/pip#8761 for rationale.
+        """
+        if sys.version_info >= (3, 12) or self.pip_imported_during_build():
+            return
+        clear_distutils()
+        self.spec_for_distutils = lambda: None
+
+    @classmethod
+    def pip_imported_during_build(cls):
+        """
+        Detect if pip is being imported in a build script. Ref #2355.
+        """
+        import traceback
+
+        return any(
+            cls.frame_file_is_setup(frame) for frame, line in traceback.walk_stack(None)
+        )
+
+    @staticmethod
+    def frame_file_is_setup(frame):
+        """
+        Return True if the indicated frame suggests a setup.py file.
+        """
+        # some frames may not have __file__ (#2940)
+        return frame.f_globals.get('__file__', '').endswith('setup.py')
+
+    def spec_for_sensitive_tests(self):
+        """
+        Ensure stdlib distutils when running select tests under CPython.
+
+        python/cpython#91169
+        """
+        clear_distutils()
+        self.spec_for_distutils = lambda: None
+
+    sensitive_tests = (
+        [
+            'test.test_distutils',
+            'test.test_peg_generator',
+            'test.test_importlib',
+        ]
+        if sys.version_info < (3, 10)
+        else [
+            'test.test_distutils',
+        ]
+    )
+
+
+for name in DistutilsMetaFinder.sensitive_tests:
+    setattr(
+        DistutilsMetaFinder,
+        f'spec_for_{name}',
+        DistutilsMetaFinder.spec_for_sensitive_tests,
+    )
+
+
+DISTUTILS_FINDER = DistutilsMetaFinder()
+
+
+def add_shim():
+    DISTUTILS_FINDER in sys.meta_path or insert_shim()
+
+
+class shim:
+    def __enter__(self) -> None:
+        insert_shim()
+
+    def __exit__(self, exc: object, value: object, tb: object) -> None:
+        _remove_shim()
+
+
+def insert_shim():
+    sys.meta_path.insert(0, DISTUTILS_FINDER)
+
+
+def _remove_shim():
+    try:
+        sys.meta_path.remove(DISTUTILS_FINDER)
+    except ValueError:
+        pass
+
+
+if sys.version_info < (3, 12):
+    # DistutilsMetaFinder can only be disabled in Python < 3.12 (PEP 632)
+    remove_shim = _remove_shim

.venv/Lib/site-packages/_distutils_hack/override.py

@@ -0,0 +1 @@
+__import__('_distutils_hack').do_override()

.venv/Lib/site-packages/_virtualenv.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:69ac3d8f27e679c81b94ab30b3b56e9cd138219b1ba94a1fa3606d5a76a1433d
+size 18

.venv/Lib/site-packages/_virtualenv.py

@@ -0,0 +1,102 @@
+"""Patches that are applied at runtime to the virtual environment."""
+
+from __future__ import annotations
+
+import os
+import sys
+from contextlib import suppress
+
+VIRTUALENV_PATCH_FILE = os.path.join(__file__)
+
+
+def patch_dist(dist):
+    """
+    Distutils allows user to configure some arguments via a configuration file:
+    https://docs.python.org/3/install/index.html#distutils-configuration-files.
+
+    Some of this arguments though don't make sense in context of the virtual environment files, let's fix them up.
+    """  # noqa: D205
+    # we cannot allow some install config as that would get packages installed outside of the virtual environment
+    old_parse_config_files = dist.Distribution.parse_config_files
+
+    def parse_config_files(self, *args, **kwargs):
+        result = old_parse_config_files(self, *args, **kwargs)
+        install = self.get_option_dict("install")
+
+        if "prefix" in install:  # the prefix governs where to install the libraries
+            install["prefix"] = VIRTUALENV_PATCH_FILE, os.path.abspath(sys.prefix)
+        for base in ("purelib", "platlib", "headers", "scripts", "data"):
+            key = f"install_{base}"
+            if key in install:  # do not allow global configs to hijack venv paths
+                install.pop(key, None)
+        return result
+
+    dist.Distribution.parse_config_files = parse_config_files
+
+
+# Import hook that patches some modules to ignore configuration values that break package installation in case
+# of virtual environments.
+_DISTUTILS_PATCH = "distutils.dist", "setuptools.dist"
+# https://docs.python.org/3/library/importlib.html#setting-up-an-importer
+
+
+class _Finder:
+    """A meta path finder that allows patching the imported distutils modules."""
+
+    fullname = None
+
+    # lock[0] is threading.Lock(), but initialized lazily to avoid importing threading very early at startup,
+    # because there are gevent-based applications that need to be first to import threading by themselves.
+    # See https://github.com/pypa/virtualenv/issues/1895 for details.
+    lock = []  # noqa: RUF012
+
+    def find_spec(self, fullname, path, target=None):  # noqa: ARG002
+        if fullname in _DISTUTILS_PATCH and self.fullname is None:
+            # initialize lock[0] lazily
+            if len(self.lock) == 0:
+                import threading
+
+                lock = threading.Lock()
+                # there is possibility that two threads T1 and T2 are simultaneously running into find_spec,
+                # observing .lock as empty, and further going into hereby initialization. However due to the GIL,
+                # list.append() operation is atomic and this way only one of the threads will "win" to put the lock
+                # - that every thread will use - into .lock[0].
+                # https://docs.python.org/3/faq/library.html#what-kinds-of-global-value-mutation-are-thread-safe
+                self.lock.append(lock)
+
+            from functools import partial
+            from importlib.util import find_spec
+
+            with self.lock[0]:
+                self.fullname = fullname
+                try:
+                    spec = find_spec(fullname, path)
+                    if spec is not None:
+                        # https://www.python.org/dev/peps/pep-0451/#how-loading-will-work
+                        is_new_api = hasattr(spec.loader, "exec_module")
+                        func_name = "exec_module" if is_new_api else "load_module"
+                        old = getattr(spec.loader, func_name)
+                        func = self.exec_module if is_new_api else self.load_module
+                        if old is not func:
+                            with suppress(AttributeError):  # C-Extension loaders are r/o such as zipimporter with <3.7
+                                setattr(spec.loader, func_name, partial(func, old))
+                        return spec
+                finally:
+                    self.fullname = None
+        return None
+
+    @staticmethod
+    def exec_module(old, module):
+        old(module)
+        if module.__name__ in _DISTUTILS_PATCH:
+            patch_dist(module)
+
+    @staticmethod
+    def load_module(old, name):
+        module = old(name)
+        if module.__name__ in _DISTUTILS_PATCH:
+            patch_dist(module)
+        return module
+
+
+sys.meta_path.insert(0, _Finder())

.venv/Lib/site-packages/_yaml/__init__.py

@@ -0,0 +1,33 @@
+# This is a stub package designed to roughly emulate the _yaml
+# extension module, which previously existed as a standalone module
+# and has been moved into the `yaml` package namespace.
+# It does not perfectly mimic its old counterpart, but should get
+# close enough for anyone who's relying on it even when they shouldn't.
+import yaml
+
+# in some circumstances, the yaml module we imoprted may be from a different version, so we need
+# to tread carefully when poking at it here (it may not have the attributes we expect)
+if not getattr(yaml, '__with_libyaml__', False):
+    from sys import version_info
+
+    exc = ModuleNotFoundError if version_info >= (3, 6) else ImportError
+    raise exc("No module named '_yaml'")
+else:
+    from yaml._yaml import *
+    import warnings
+    warnings.warn(
+        'The _yaml extension module is now located at yaml._yaml'
+        ' and its location is subject to change.  To use the'
+        ' LibYAML-based parser and emitter, import from `yaml`:'
+        ' `from yaml import CLoader as Loader, CDumper as Dumper`.',
+        DeprecationWarning
+    )
+    del warnings
+    # Don't `del yaml` here because yaml is actually an existing
+    # namespace member of _yaml.
+
+__name__ = '_yaml'
+# If the module is top-level (i.e. not a part of any specific package)
+# then the attribute should be set to ''.
+# https://docs.python.org/3.8/library/types.html
+__package__ = ''

.venv/Lib/site-packages/accelerate-1.4.0.dist-info/INSTALLER

@@ -0,0 +1 @@
+pip

.venv/Lib/site-packages/accelerate-1.4.0.dist-info/LICENSE

@@ -0,0 +1,201 @@
+                                 Apache License
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+
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.venv/Lib/site-packages/accelerate-1.4.0.dist-info/METADATA

@@ -0,0 +1,375 @@
+Metadata-Version: 2.1
+Name: accelerate
+Version: 1.4.0
+Summary: Accelerate
+Home-page: https://github.com/huggingface/accelerate
+Author: The HuggingFace team
+Author-email: zach.mueller@huggingface.co
+License: Apache
+Keywords: deep learning
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: Apache Software License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
+Requires-Python: >=3.9.0
+Description-Content-Type: text/markdown
+License-File: LICENSE
+Requires-Dist: numpy (<3.0.0,>=1.17)
+Requires-Dist: packaging (>=20.0)
+Requires-Dist: psutil
+Requires-Dist: pyyaml
+Requires-Dist: torch (>=2.0.0)
+Requires-Dist: huggingface-hub (>=0.21.0)
+Requires-Dist: safetensors (>=0.4.3)
+Provides-Extra: deepspeed
+Requires-Dist: deepspeed ; extra == 'deepspeed'
+Provides-Extra: dev
+Requires-Dist: black (~=23.1) ; extra == 'dev'
+Requires-Dist: hf-doc-builder (>=0.3.0) ; extra == 'dev'
+Requires-Dist: ruff (~=0.6.4) ; extra == 'dev'
+Requires-Dist: pytest (<=8.0.0,>=7.2.0) ; extra == 'dev'
+Requires-Dist: pytest-xdist ; extra == 'dev'
+Requires-Dist: pytest-subtests ; extra == 'dev'
+Requires-Dist: parameterized ; extra == 'dev'
+Requires-Dist: datasets ; extra == 'dev'
+Requires-Dist: diffusers ; extra == 'dev'
+Requires-Dist: evaluate ; extra == 'dev'
+Requires-Dist: torchdata (>=0.8.0) ; extra == 'dev'
+Requires-Dist: torchpippy (>=0.2.0) ; extra == 'dev'
+Requires-Dist: transformers ; extra == 'dev'
+Requires-Dist: scipy ; extra == 'dev'
+Requires-Dist: scikit-learn ; extra == 'dev'
+Requires-Dist: tqdm ; extra == 'dev'
+Requires-Dist: bitsandbytes ; extra == 'dev'
+Requires-Dist: timm ; extra == 'dev'
+Requires-Dist: rich ; extra == 'dev'
+Provides-Extra: docs
+Provides-Extra: quality
+Requires-Dist: black (~=23.1) ; extra == 'quality'
+Requires-Dist: hf-doc-builder (>=0.3.0) ; extra == 'quality'
+Requires-Dist: ruff (~=0.6.4) ; extra == 'quality'
+Provides-Extra: rich
+Requires-Dist: rich ; extra == 'rich'
+Provides-Extra: sagemaker
+Requires-Dist: sagemaker ; extra == 'sagemaker'
+Provides-Extra: test_dev
+Requires-Dist: datasets ; extra == 'test_dev'
+Requires-Dist: diffusers ; extra == 'test_dev'
+Requires-Dist: evaluate ; extra == 'test_dev'
+Requires-Dist: torchdata (>=0.8.0) ; extra == 'test_dev'
+Requires-Dist: torchpippy (>=0.2.0) ; extra == 'test_dev'
+Requires-Dist: transformers ; extra == 'test_dev'
+Requires-Dist: scipy ; extra == 'test_dev'
+Requires-Dist: scikit-learn ; extra == 'test_dev'
+Requires-Dist: tqdm ; extra == 'test_dev'
+Requires-Dist: bitsandbytes ; extra == 'test_dev'
+Requires-Dist: timm ; extra == 'test_dev'
+Provides-Extra: test_prod
+Requires-Dist: pytest (<=8.0.0,>=7.2.0) ; extra == 'test_prod'
+Requires-Dist: pytest-xdist ; extra == 'test_prod'
+Requires-Dist: pytest-subtests ; extra == 'test_prod'
+Requires-Dist: parameterized ; extra == 'test_prod'
+Provides-Extra: test_trackers
+Requires-Dist: wandb ; extra == 'test_trackers'
+Requires-Dist: comet-ml ; extra == 'test_trackers'
+Requires-Dist: tensorboard ; extra == 'test_trackers'
+Requires-Dist: dvclive ; extra == 'test_trackers'
+Provides-Extra: testing
+Requires-Dist: pytest (<=8.0.0,>=7.2.0) ; extra == 'testing'
+Requires-Dist: pytest-xdist ; extra == 'testing'
+Requires-Dist: pytest-subtests ; extra == 'testing'
+Requires-Dist: parameterized ; extra == 'testing'
+Requires-Dist: datasets ; extra == 'testing'
+Requires-Dist: diffusers ; extra == 'testing'
+Requires-Dist: evaluate ; extra == 'testing'
+Requires-Dist: torchdata (>=0.8.0) ; extra == 'testing'
+Requires-Dist: torchpippy (>=0.2.0) ; extra == 'testing'
+Requires-Dist: transformers ; extra == 'testing'
+Requires-Dist: scipy ; extra == 'testing'
+Requires-Dist: scikit-learn ; extra == 'testing'
+Requires-Dist: tqdm ; extra == 'testing'
+Requires-Dist: bitsandbytes ; extra == 'testing'
+Requires-Dist: timm ; extra == 'testing'
+
+<!---
+Copyright 2021 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+<p align="center">
+    <br>
+    <img src="https://raw.githubusercontent.com/huggingface/accelerate/main/docs/source/imgs/accelerate_logo.png" width="400"/>
+    <br>
+<p>
+
+<p align="center">
+    <!-- Uncomment when CircleCI is set up
+    <a href="https://circleci.com/gh/huggingface/accelerate"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/master"></a>
+    -->
+    <a href="https://github.com/huggingface/accelerate/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/github/license/huggingface/accelerate.svg?color=blue"></a>
+    <a href="https://huggingface.co/docs/accelerate/index.html"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/accelerate/index.html.svg?down_color=red&down_message=offline&up_message=online"></a>
+    <a href="https://github.com/huggingface/accelerate/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/accelerate.svg"></a>
+    <a href="https://github.com/huggingface/accelerate/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
+</p>
+
+<h3 align="center">
+<p>Run your *raw* PyTorch training script on any kind of device
+</h3>
+
+<h3 align="center">
+    <a href="https://hf.co/course"><img src="https://raw.githubusercontent.com/huggingface/accelerate/main/docs/source/imgs/course_banner.png"></a>
+</h3>
+
+## Easy to integrate
+
+🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.
+
+🤗 Accelerate abstracts exactly and only the boilerplate code related to multi-GPUs/TPU/fp16 and leaves the rest of your code unchanged.
+
+Here is an example:
+
+```diff
+  import torch
+  import torch.nn.functional as F
+  from datasets import load_dataset
++ from accelerate import Accelerator
+
++ accelerator = Accelerator()
+- device = 'cpu'
++ device = accelerator.device
+
+  model = torch.nn.Transformer().to(device)
+  optimizer = torch.optim.Adam(model.parameters())
+
+  dataset = load_dataset('my_dataset')
+  data = torch.utils.data.DataLoader(dataset, shuffle=True)
+
++ model, optimizer, data = accelerator.prepare(model, optimizer, data)
+
+  model.train()
+  for epoch in range(10):
+      for source, targets in data:
+          source = source.to(device)
+          targets = targets.to(device)
+
+          optimizer.zero_grad()
+
+          output = model(source)
+          loss = F.cross_entropy(output, targets)
+
+-         loss.backward()
++         accelerator.backward(loss)
+
+          optimizer.step()
+```
+
+As you can see in this example, by adding 5-lines to any standard PyTorch training script you can now run on any kind of single or distributed node setting (single CPU, single GPU, multi-GPUs and TPUs) as well as with or without mixed precision (fp8, fp16, bf16).
+
+In particular, the same code can then be run without modification on your local machine for debugging or your training environment.
+
+🤗 Accelerate even handles the device placement for you (which requires a few more changes to your code, but is safer in general), so you can even simplify your training loop further:
+
+```diff
+  import torch
+  import torch.nn.functional as F
+  from datasets import load_dataset
++ from accelerate import Accelerator
+
+- device = 'cpu'
++ accelerator = Accelerator()
+
+- model = torch.nn.Transformer().to(device)
++ model = torch.nn.Transformer()
+  optimizer = torch.optim.Adam(model.parameters())
+
+  dataset = load_dataset('my_dataset')
+  data = torch.utils.data.DataLoader(dataset, shuffle=True)
+
++ model, optimizer, data = accelerator.prepare(model, optimizer, data)
+
+  model.train()
+  for epoch in range(10):
+      for source, targets in data:
+-         source = source.to(device)
+-         targets = targets.to(device)
+
+          optimizer.zero_grad()
+
+          output = model(source)
+          loss = F.cross_entropy(output, targets)
+
+-         loss.backward()
++         accelerator.backward(loss)
+
+          optimizer.step()
+```
+
+Want to learn more? Check out the [documentation](https://huggingface.co/docs/accelerate) or have a look at our [examples](https://github.com/huggingface/accelerate/tree/main/examples).
+
+## Launching script
+
+🤗 Accelerate also provides an optional CLI tool that allows you to quickly configure and test your training environment before launching the scripts. No need to remember how to use `torch.distributed.run` or to write a specific launcher for TPU training!
+On your machine(s) just run:
+
+```bash
+accelerate config
+```
+
+and answer the questions asked. This will generate a config file that will be used automatically to properly set the default options when doing
+
+```bash
+accelerate launch my_script.py --args_to_my_script
+``` 
+
+For instance, here is how you would run the GLUE example on the MRPC task (from the root of the repo):
+
+```bash
+accelerate launch examples/nlp_example.py
+```
+
+This CLI tool is **optional**, and you can still use `python my_script.py` or `python -m torchrun my_script.py` at your convenience.
+
+You can also directly pass in the arguments you would to `torchrun` as arguments to `accelerate launch` if you wish to not run` accelerate config`.
+
+For example, here is how to launch on two GPUs:
+
+```bash
+accelerate launch --multi_gpu --num_processes 2 examples/nlp_example.py
+```
+
+To learn more, check the CLI documentation available [here](https://huggingface.co/docs/accelerate/package_reference/cli).
+
+Or view the configuration zoo [here](https://github.com/huggingface/accelerate/blob/main/examples/config_yaml_templates/)
+
+## Launching multi-CPU run using MPI
+
+🤗 Here is another way to launch multi-CPU run using MPI. You can learn how to install Open MPI on [this page](https://www.open-mpi.org/faq/?category=building#easy-build). You can use Intel MPI or MVAPICH as well.
+Once you have MPI setup on your cluster, just run:
+```bash
+accelerate config
+```
+Answer the questions that are asked, selecting to run using multi-CPU, and answer "yes" when asked if you want accelerate to launch mpirun.
+Then, use `accelerate launch` with your script like:
+```bash
+accelerate launch examples/nlp_example.py
+```
+Alternatively, you can use mpirun directly, without using the CLI like:
+```bash
+mpirun -np 2 python examples/nlp_example.py
+```
+
+## Launching training using DeepSpeed
+
+🤗 Accelerate supports training on single/multiple GPUs using DeepSpeed. To use it, you don't need to change anything in your training code; you can set everything using just `accelerate config`. However, if you desire to tweak your DeepSpeed related args from your Python script, we provide you the `DeepSpeedPlugin`.
+
+```python
+from accelerate import Accelerator, DeepSpeedPlugin
+
+# deepspeed needs to know your gradient accumulation steps beforehand, so don't forget to pass it
+# Remember you still need to do gradient accumulation by yourself, just like you would have done without deepspeed
+deepspeed_plugin = DeepSpeedPlugin(zero_stage=2, gradient_accumulation_steps=2)
+accelerator = Accelerator(mixed_precision='fp16', deepspeed_plugin=deepspeed_plugin)
+
+# How to save your 🤗 Transformer?
+accelerator.wait_for_everyone()
+unwrapped_model = accelerator.unwrap_model(model)
+unwrapped_model.save_pretrained(save_dir, save_function=accelerator.save, state_dict=accelerator.get_state_dict(model))
+```
+
+Note: DeepSpeed support is experimental for now. In case you get into some problem, please open an issue.
+
+## Launching your training from a notebook
+
+🤗 Accelerate also provides a `notebook_launcher` function you can use in a notebook to launch a distributed training. This is especially useful for Colab or Kaggle notebooks with a TPU backend. Just define your training loop in a `training_function` then in your last cell, add:
+
+```python
+from accelerate import notebook_launcher
+
+notebook_launcher(training_function)
+```
+
+An example can be found in [this notebook](https://github.com/huggingface/notebooks/blob/main/examples/accelerate_examples/simple_nlp_example.ipynb). [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/accelerate_examples/simple_nlp_example.ipynb)
+
+## Why should I use 🤗 Accelerate?
+
+You should use 🤗 Accelerate when you want to easily run your training scripts in a distributed environment without having to renounce full control over your training loop. This is not a high-level framework above PyTorch, just a thin wrapper so you don't have to learn a new library. In fact, the whole API of 🤗 Accelerate is in one class, the `Accelerator` object.
+
+## Why shouldn't I use 🤗 Accelerate?
+
+You shouldn't use 🤗 Accelerate if you don't want to write a training loop yourself. There are plenty of high-level libraries above PyTorch that will offer you that, 🤗 Accelerate is not one of them.
+
+## Frameworks using 🤗 Accelerate
+
+If you like the simplicity of 🤗 Accelerate but would prefer a higher-level abstraction around its capabilities, some frameworks and libraries that are built on top of 🤗 Accelerate are listed below:
+
+* [Amphion](https://github.com/open-mmlab/Amphion) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.
+* [Animus](https://github.com/Scitator/animus) is a minimalistic framework to run machine learning experiments. Animus highlights common "breakpoints" in ML experiments and provides a unified interface for them within [IExperiment](https://github.com/Scitator/animus/blob/main/animus/core.py#L76).
+* [Catalyst](https://github.com/catalyst-team/catalyst#getting-started) is a PyTorch framework for Deep Learning Research and Development. It focuses on reproducibility, rapid experimentation, and codebase reuse so you can create something new rather than write yet another train loop. Catalyst provides a [Runner](https://catalyst-team.github.io/catalyst/api/core.html#runner) to connect all parts of the experiment: hardware backend, data transformations, model training, and inference logic.
+* [fastai](https://github.com/fastai/fastai#installing) is a PyTorch framework for Deep Learning that simplifies training fast and accurate neural nets using modern best practices. fastai provides a [Learner](https://docs.fast.ai/learner.html#Learner) to handle the training, fine-tuning, and inference of deep learning algorithms.
+* [Finetuner](https://github.com/jina-ai/finetuner) is a service that enables models to create higher-quality embeddings for semantic search, visual similarity search, cross-modal text<->image search, recommendation systems, clustering, duplication detection, anomaly detection, or other uses.
+* [InvokeAI](https://github.com/invoke-ai/InvokeAI) is a creative engine for Stable Diffusion models, offering industry-leading WebUI, terminal usage support, and serves as the foundation for many commercial products.
+* [Kornia](https://kornia.readthedocs.io/en/latest/get-started/introduction.html) is a differentiable library that allows classical computer vision to be integrated into deep learning models. Kornia provides a [Trainer](https://kornia.readthedocs.io/en/latest/x.html#kornia.x.Trainer) with the specific purpose to train and fine-tune the supported deep learning algorithms within the library.
+* [Open Assistant](https://projects.laion.ai/Open-Assistant/) is a chat-based assistant that understands tasks, can interact with their party systems, and retrieve information dynamically to do so. 
+* [pytorch-accelerated](https://github.com/Chris-hughes10/pytorch-accelerated) is a lightweight training library, with a streamlined feature set centered around a general-purpose [Trainer](https://pytorch-accelerated.readthedocs.io/en/latest/trainer.html), that places a huge emphasis on simplicity and transparency; enabling users to understand exactly what is going on under the hood, but without having to write and maintain the boilerplate themselves!
+* [Stable Diffusion web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) is an open-source browser-based easy-to-use interface based on the Gradio library for Stable Diffusion.
+* [torchkeras](https://github.com/lyhue1991/torchkeras) is a simple tool for training pytorch model just in a keras style, a dynamic and beautiful plot is provided in notebook to monitor your loss or metric.
+* [transformers](https://github.com/huggingface/transformers) as a tool for helping train state-of-the-art machine learning models in PyTorch, Tensorflow, and JAX. (Accelerate is the backend for the PyTorch side).
+
+
+## Installation
+
+This repository is tested on Python 3.8+ and PyTorch 1.10.0+
+
+You should install 🤗 Accelerate in a [virtual environment](https://docs.python.org/3/library/venv.html). If you're unfamiliar with Python virtual environments, check out the [user guide](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
+
+First, create a virtual environment with the version of Python you're going to use and activate it.
+
+Then, you will need to install PyTorch: refer to the [official installation page](https://pytorch.org/get-started/locally/#start-locally) regarding the specific install command for your platform. Then 🤗 Accelerate can be installed using pip as follows:
+
+```bash
+pip install accelerate
+```
+
+## Supported integrations
+
+- CPU only
+- multi-CPU on one node (machine)
+- multi-CPU on several nodes (machines)
+- single GPU
+- multi-GPU on one node (machine)
+- multi-GPU on several nodes (machines)
+- TPU
+- FP16/BFloat16 mixed precision
+- FP8 mixed precision with [Transformer Engine](https://github.com/NVIDIA/TransformerEngine) or [MS-AMP](https://github.com/Azure/MS-AMP/)
+- DeepSpeed support (Experimental)
+- PyTorch Fully Sharded Data Parallel (FSDP) support (Experimental)
+- Megatron-LM support (Experimental)
+
+## Citing 🤗 Accelerate
+
+If you use 🤗 Accelerate in your publication, please cite it by using the following BibTeX entry.
+
+```bibtex
+@Misc{accelerate,
+  title =        {Accelerate: Training and inference at scale made simple, efficient and adaptable.},
+  author =       {Sylvain Gugger and Lysandre Debut and Thomas Wolf and Philipp Schmid and Zachary Mueller and Sourab Mangrulkar and Marc Sun and Benjamin Bossan},
+  howpublished = {\url{https://github.com/huggingface/accelerate}},
+  year =         {2022}
+}
+```

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.venv/Lib/site-packages/accelerate-1.4.0.dist-info/WHEEL

@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.37.1)
+Root-Is-Purelib: true
+Tag: py3-none-any
+

.venv/Lib/site-packages/accelerate-1.4.0.dist-info/entry_points.txt

@@ -0,0 +1,6 @@
+[console_scripts]
+accelerate = accelerate.commands.accelerate_cli:main
+accelerate-config = accelerate.commands.config:main
+accelerate-estimate-memory = accelerate.commands.estimate:main
+accelerate-launch = accelerate.commands.launch:main
+accelerate-merge-weights = accelerate.commands.merge:main

.venv/Lib/site-packages/accelerate-1.4.0.dist-info/top_level.txt

@@ -0,0 +1 @@
+accelerate

.venv/Lib/site-packages/accelerate/__init__.py

@@ -0,0 +1,50 @@
+# Copyright 2020 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+__version__ = "1.4.0"
+
+from .accelerator import Accelerator
+from .big_modeling import (
+    cpu_offload,
+    cpu_offload_with_hook,
+    disk_offload,
+    dispatch_model,
+    init_empty_weights,
+    init_on_device,
+    load_checkpoint_and_dispatch,
+)
+from .data_loader import skip_first_batches
+from .inference import prepare_pippy
+from .launchers import debug_launcher, notebook_launcher
+from .state import PartialState
+from .utils import (
+    AutocastKwargs,
+    DataLoaderConfiguration,
+    DDPCommunicationHookType,
+    DeepSpeedPlugin,
+    DistributedDataParallelKwargs,
+    DistributedType,
+    FullyShardedDataParallelPlugin,
+    GradScalerKwargs,
+    InitProcessGroupKwargs,
+    ProfileKwargs,
+    find_executable_batch_size,
+    infer_auto_device_map,
+    is_rich_available,
+    load_checkpoint_in_model,
+    synchronize_rng_states,
+)
+
+
+if is_rich_available():
+    from .utils import rich

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