diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/__pycache__/packaging.cpython-310.pyc b/llava/lib/python3.10/site-packages/pip/_internal/utils/__pycache__/packaging.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..87f24980438cd4dd73bf0d261887669110091031 Binary files /dev/null and b/llava/lib/python3.10/site-packages/pip/_internal/utils/__pycache__/packaging.cpython-310.pyc differ diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/_log.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/_log.py new file mode 100644 index 0000000000000000000000000000000000000000..92c4c6a193873ce09629f6cfaa2dabc4f14ecb03 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/_log.py @@ -0,0 +1,38 @@ +"""Customize logging + +Defines custom logger class for the `logger.verbose(...)` method. + +init_logging() must be called before any other modules that call logging.getLogger. +""" + +import logging +from typing import Any, cast + +# custom log level for `--verbose` output +# between DEBUG and INFO +VERBOSE = 15 + + +class VerboseLogger(logging.Logger): + """Custom Logger, defining a verbose log-level + + VERBOSE is between INFO and DEBUG. + """ + + def verbose(self, msg: str, *args: Any, **kwargs: Any) -> None: + return self.log(VERBOSE, msg, *args, **kwargs) + + +def getLogger(name: str) -> VerboseLogger: + """logging.getLogger, but ensures our VerboseLogger class is returned""" + return cast(VerboseLogger, logging.getLogger(name)) + + +def init_logging() -> None: + """Register our VerboseLogger and VERBOSE log level. + + Should be called before any calls to getLogger(), + i.e. in pip._internal.__init__ + """ + logging.setLoggerClass(VerboseLogger) + logging.addLevelName(VERBOSE, "VERBOSE") diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/compat.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/compat.py new file mode 100644 index 0000000000000000000000000000000000000000..d8b54e4ee51d03a7beca065971967b9c70cc3526 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/compat.py @@ -0,0 +1,79 @@ +"""Stuff that differs in different Python versions and platform +distributions.""" + +import importlib.resources +import logging +import os +import sys +from typing import IO + +__all__ = ["get_path_uid", "stdlib_pkgs", "WINDOWS"] + + +logger = logging.getLogger(__name__) + + +def has_tls() -> bool: + try: + import _ssl # noqa: F401 # ignore unused + + return True + except ImportError: + pass + + from pip._vendor.urllib3.util import IS_PYOPENSSL + + return IS_PYOPENSSL + + +def get_path_uid(path: str) -> int: + """ + Return path's uid. + + Does not follow symlinks: + https://github.com/pypa/pip/pull/935#discussion_r5307003 + + Placed this function in compat due to differences on AIX and + Jython, that should eventually go away. + + :raises OSError: When path is a symlink or can't be read. + """ + if hasattr(os, "O_NOFOLLOW"): + fd = os.open(path, os.O_RDONLY | os.O_NOFOLLOW) + file_uid = os.fstat(fd).st_uid + os.close(fd) + else: # AIX and Jython + # WARNING: time of check vulnerability, but best we can do w/o NOFOLLOW + if not os.path.islink(path): + # older versions of Jython don't have `os.fstat` + file_uid = os.stat(path).st_uid + else: + # raise OSError for parity with os.O_NOFOLLOW above + raise OSError(f"{path} is a symlink; Will not return uid for symlinks") + return file_uid + + +# The importlib.resources.open_text function was deprecated in 3.11 with suggested +# replacement we use below. +if sys.version_info < (3, 11): + open_text_resource = importlib.resources.open_text +else: + + def open_text_resource( + package: str, resource: str, encoding: str = "utf-8", errors: str = "strict" + ) -> IO[str]: + return (importlib.resources.files(package) / resource).open( + "r", encoding=encoding, errors=errors + ) + + +# packages in the stdlib that may have installation metadata, but should not be +# considered 'installed'. this theoretically could be determined based on +# dist.location (py27:`sysconfig.get_paths()['stdlib']`, +# py26:sysconfig.get_config_vars('LIBDEST')), but fear platform variation may +# make this ineffective, so hard-coding +stdlib_pkgs = {"python", "wsgiref", "argparse"} + + +# windows detection, covers cpython and ironpython +WINDOWS = sys.platform.startswith("win") or (sys.platform == "cli" and os.name == "nt") diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/compatibility_tags.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/compatibility_tags.py new file mode 100644 index 0000000000000000000000000000000000000000..2e7b7450dcea5b3bbcfe118f2e4cbe3fc16a7b1a --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/compatibility_tags.py @@ -0,0 +1,188 @@ +"""Generate and work with PEP 425 Compatibility Tags. +""" + +import re +from typing import List, Optional, Tuple + +from pip._vendor.packaging.tags import ( + PythonVersion, + Tag, + compatible_tags, + cpython_tags, + generic_tags, + interpreter_name, + interpreter_version, + ios_platforms, + mac_platforms, +) + +_apple_arch_pat = re.compile(r"(.+)_(\d+)_(\d+)_(.+)") + + +def version_info_to_nodot(version_info: Tuple[int, ...]) -> str: + # Only use up to the first two numbers. + return "".join(map(str, version_info[:2])) + + +def _mac_platforms(arch: str) -> List[str]: + match = _apple_arch_pat.match(arch) + if match: + name, major, minor, actual_arch = match.groups() + mac_version = (int(major), int(minor)) + arches = [ + # Since we have always only checked that the platform starts + # with "macosx", for backwards-compatibility we extract the + # actual prefix provided by the user in case they provided + # something like "macosxcustom_". It may be good to remove + # this as undocumented or deprecate it in the future. + "{}_{}".format(name, arch[len("macosx_") :]) + for arch in mac_platforms(mac_version, actual_arch) + ] + else: + # arch pattern didn't match (?!) + arches = [arch] + return arches + + +def _ios_platforms(arch: str) -> List[str]: + match = _apple_arch_pat.match(arch) + if match: + name, major, minor, actual_multiarch = match.groups() + ios_version = (int(major), int(minor)) + arches = [ + # Since we have always only checked that the platform starts + # with "ios", for backwards-compatibility we extract the + # actual prefix provided by the user in case they provided + # something like "ioscustom_". It may be good to remove + # this as undocumented or deprecate it in the future. + "{}_{}".format(name, arch[len("ios_") :]) + for arch in ios_platforms(ios_version, actual_multiarch) + ] + else: + # arch pattern didn't match (?!) + arches = [arch] + return arches + + +def _custom_manylinux_platforms(arch: str) -> List[str]: + arches = [arch] + arch_prefix, arch_sep, arch_suffix = arch.partition("_") + if arch_prefix == "manylinux2014": + # manylinux1/manylinux2010 wheels run on most manylinux2014 systems + # with the exception of wheels depending on ncurses. PEP 599 states + # manylinux1/manylinux2010 wheels should be considered + # manylinux2014 wheels: + # https://www.python.org/dev/peps/pep-0599/#backwards-compatibility-with-manylinux2010-wheels + if arch_suffix in {"i686", "x86_64"}: + arches.append("manylinux2010" + arch_sep + arch_suffix) + arches.append("manylinux1" + arch_sep + arch_suffix) + elif arch_prefix == "manylinux2010": + # manylinux1 wheels run on most manylinux2010 systems with the + # exception of wheels depending on ncurses. PEP 571 states + # manylinux1 wheels should be considered manylinux2010 wheels: + # https://www.python.org/dev/peps/pep-0571/#backwards-compatibility-with-manylinux1-wheels + arches.append("manylinux1" + arch_sep + arch_suffix) + return arches + + +def _get_custom_platforms(arch: str) -> List[str]: + arch_prefix, arch_sep, arch_suffix = arch.partition("_") + if arch.startswith("macosx"): + arches = _mac_platforms(arch) + elif arch.startswith("ios"): + arches = _ios_platforms(arch) + elif arch_prefix in ["manylinux2014", "manylinux2010"]: + arches = _custom_manylinux_platforms(arch) + else: + arches = [arch] + return arches + + +def _expand_allowed_platforms(platforms: Optional[List[str]]) -> Optional[List[str]]: + if not platforms: + return None + + seen = set() + result = [] + + for p in platforms: + if p in seen: + continue + additions = [c for c in _get_custom_platforms(p) if c not in seen] + seen.update(additions) + result.extend(additions) + + return result + + +def _get_python_version(version: str) -> PythonVersion: + if len(version) > 1: + return int(version[0]), int(version[1:]) + else: + return (int(version[0]),) + + +def _get_custom_interpreter( + implementation: Optional[str] = None, version: Optional[str] = None +) -> str: + if implementation is None: + implementation = interpreter_name() + if version is None: + version = interpreter_version() + return f"{implementation}{version}" + + +def get_supported( + version: Optional[str] = None, + platforms: Optional[List[str]] = None, + impl: Optional[str] = None, + abis: Optional[List[str]] = None, +) -> List[Tag]: + """Return a list of supported tags for each version specified in + `versions`. + + :param version: a string version, of the form "33" or "32", + or None. The version will be assumed to support our ABI. + :param platform: specify a list of platforms you want valid + tags for, or None. If None, use the local system platform. + :param impl: specify the exact implementation you want valid + tags for, or None. If None, use the local interpreter impl. + :param abis: specify a list of abis you want valid + tags for, or None. If None, use the local interpreter abi. + """ + supported: List[Tag] = [] + + python_version: Optional[PythonVersion] = None + if version is not None: + python_version = _get_python_version(version) + + interpreter = _get_custom_interpreter(impl, version) + + platforms = _expand_allowed_platforms(platforms) + + is_cpython = (impl or interpreter_name()) == "cp" + if is_cpython: + supported.extend( + cpython_tags( + python_version=python_version, + abis=abis, + platforms=platforms, + ) + ) + else: + supported.extend( + generic_tags( + interpreter=interpreter, + abis=abis, + platforms=platforms, + ) + ) + supported.extend( + compatible_tags( + python_version=python_version, + interpreter=interpreter, + platforms=platforms, + ) + ) + + return supported diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/datetime.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/datetime.py new file mode 100644 index 0000000000000000000000000000000000000000..8668b3b0ec1deec2aeb7ff6bd94265d6705e05bf --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/datetime.py @@ -0,0 +1,11 @@ +"""For when pip wants to check the date or time. +""" + +import datetime + + +def today_is_later_than(year: int, month: int, day: int) -> bool: + today = datetime.date.today() + given = datetime.date(year, month, day) + + return today > given diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/deprecation.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/deprecation.py new file mode 100644 index 0000000000000000000000000000000000000000..0911147e784737f58f174dce98ecae32b615c7b7 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/deprecation.py @@ -0,0 +1,124 @@ +""" +A module that implements tooling to enable easy warnings about deprecations. +""" + +import logging +import warnings +from typing import Any, Optional, TextIO, Type, Union + +from pip._vendor.packaging.version import parse + +from pip import __version__ as current_version # NOTE: tests patch this name. + +DEPRECATION_MSG_PREFIX = "DEPRECATION: " + + +class PipDeprecationWarning(Warning): + pass + + +_original_showwarning: Any = None + + +# Warnings <-> Logging Integration +def _showwarning( + message: Union[Warning, str], + category: Type[Warning], + filename: str, + lineno: int, + file: Optional[TextIO] = None, + line: Optional[str] = None, +) -> None: + if file is not None: + if _original_showwarning is not None: + _original_showwarning(message, category, filename, lineno, file, line) + elif issubclass(category, PipDeprecationWarning): + # We use a specially named logger which will handle all of the + # deprecation messages for pip. + logger = logging.getLogger("pip._internal.deprecations") + logger.warning(message) + else: + _original_showwarning(message, category, filename, lineno, file, line) + + +def install_warning_logger() -> None: + # Enable our Deprecation Warnings + warnings.simplefilter("default", PipDeprecationWarning, append=True) + + global _original_showwarning + + if _original_showwarning is None: + _original_showwarning = warnings.showwarning + warnings.showwarning = _showwarning + + +def deprecated( + *, + reason: str, + replacement: Optional[str], + gone_in: Optional[str], + feature_flag: Optional[str] = None, + issue: Optional[int] = None, +) -> None: + """Helper to deprecate existing functionality. + + reason: + Textual reason shown to the user about why this functionality has + been deprecated. Should be a complete sentence. + replacement: + Textual suggestion shown to the user about what alternative + functionality they can use. + gone_in: + The version of pip does this functionality should get removed in. + Raises an error if pip's current version is greater than or equal to + this. + feature_flag: + Command-line flag of the form --use-feature={feature_flag} for testing + upcoming functionality. + issue: + Issue number on the tracker that would serve as a useful place for + users to find related discussion and provide feedback. + """ + + # Determine whether or not the feature is already gone in this version. + is_gone = gone_in is not None and parse(current_version) >= parse(gone_in) + + message_parts = [ + (reason, f"{DEPRECATION_MSG_PREFIX}{{}}"), + ( + gone_in, + ( + "pip {} will enforce this behaviour change." + if not is_gone + else "Since pip {}, this is no longer supported." + ), + ), + ( + replacement, + "A possible replacement is {}.", + ), + ( + feature_flag, + ( + "You can use the flag --use-feature={} to test the upcoming behaviour." + if not is_gone + else None + ), + ), + ( + issue, + "Discussion can be found at https://github.com/pypa/pip/issues/{}", + ), + ] + + message = " ".join( + format_str.format(value) + for value, format_str in message_parts + if format_str is not None and value is not None + ) + + # Raise as an error if this behaviour is deprecated. + if is_gone: + raise PipDeprecationWarning(message) + + warnings.warn(message, category=PipDeprecationWarning, stacklevel=2) diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/direct_url_helpers.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/direct_url_helpers.py new file mode 100644 index 0000000000000000000000000000000000000000..66020d3964ad4d8bc55893380383b271642471f7 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/direct_url_helpers.py @@ -0,0 +1,87 @@ +from typing import Optional + +from pip._internal.models.direct_url import ArchiveInfo, DirectUrl, DirInfo, VcsInfo +from pip._internal.models.link import Link +from pip._internal.utils.urls import path_to_url +from pip._internal.vcs import vcs + + +def direct_url_as_pep440_direct_reference(direct_url: DirectUrl, name: str) -> str: + """Convert a DirectUrl to a pip requirement string.""" + direct_url.validate() # if invalid, this is a pip bug + requirement = name + " @ " + fragments = [] + if isinstance(direct_url.info, VcsInfo): + requirement += ( + f"{direct_url.info.vcs}+{direct_url.url}@{direct_url.info.commit_id}" + ) + elif isinstance(direct_url.info, ArchiveInfo): + requirement += direct_url.url + if direct_url.info.hash: + fragments.append(direct_url.info.hash) + else: + assert isinstance(direct_url.info, DirInfo) + requirement += direct_url.url + if direct_url.subdirectory: + fragments.append("subdirectory=" + direct_url.subdirectory) + if fragments: + requirement += "#" + "&".join(fragments) + return requirement + + +def direct_url_for_editable(source_dir: str) -> DirectUrl: + return DirectUrl( + url=path_to_url(source_dir), + info=DirInfo(editable=True), + ) + + +def direct_url_from_link( + link: Link, source_dir: Optional[str] = None, link_is_in_wheel_cache: bool = False +) -> DirectUrl: + if link.is_vcs: + vcs_backend = vcs.get_backend_for_scheme(link.scheme) + assert vcs_backend + url, requested_revision, _ = vcs_backend.get_url_rev_and_auth( + link.url_without_fragment + ) + # For VCS links, we need to find out and add commit_id. + if link_is_in_wheel_cache: + # If the requested VCS link corresponds to a cached + # wheel, it means the requested revision was an + # immutable commit hash, otherwise it would not have + # been cached. In that case we don't have a source_dir + # with the VCS checkout. + assert requested_revision + commit_id = requested_revision + else: + # If the wheel was not in cache, it means we have + # had to checkout from VCS to build and we have a source_dir + # which we can inspect to find out the commit id. + assert source_dir + commit_id = vcs_backend.get_revision(source_dir) + return DirectUrl( + url=url, + info=VcsInfo( + vcs=vcs_backend.name, + commit_id=commit_id, + requested_revision=requested_revision, + ), + subdirectory=link.subdirectory_fragment, + ) + elif link.is_existing_dir(): + return DirectUrl( + url=link.url_without_fragment, + info=DirInfo(), + subdirectory=link.subdirectory_fragment, + ) + else: + hash = None + hash_name = link.hash_name + if hash_name: + hash = f"{hash_name}={link.hash}" + return DirectUrl( + url=link.url_without_fragment, + info=ArchiveInfo(hash=hash), + subdirectory=link.subdirectory_fragment, + ) diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/egg_link.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/egg_link.py new file mode 100644 index 0000000000000000000000000000000000000000..4a384a63682ce53cafcf889551b13b9177a14e44 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/egg_link.py @@ -0,0 +1,80 @@ +import os +import re +import sys +from typing import List, Optional + +from pip._internal.locations import site_packages, user_site +from pip._internal.utils.virtualenv import ( + running_under_virtualenv, + virtualenv_no_global, +) + +__all__ = [ + "egg_link_path_from_sys_path", + "egg_link_path_from_location", +] + + +def _egg_link_names(raw_name: str) -> List[str]: + """ + Convert a Name metadata value to a .egg-link name, by applying + the same substitution as pkg_resources's safe_name function. + Note: we cannot use canonicalize_name because it has a different logic. + + We also look for the raw name (without normalization) as setuptools 69 changed + the way it names .egg-link files (https://github.com/pypa/setuptools/issues/4167). + """ + return [ + re.sub("[^A-Za-z0-9.]+", "-", raw_name) + ".egg-link", + f"{raw_name}.egg-link", + ] + + +def egg_link_path_from_sys_path(raw_name: str) -> Optional[str]: + """ + Look for a .egg-link file for project name, by walking sys.path. + """ + egg_link_names = _egg_link_names(raw_name) + for path_item in sys.path: + for egg_link_name in egg_link_names: + egg_link = os.path.join(path_item, egg_link_name) + if os.path.isfile(egg_link): + return egg_link + return None + + +def egg_link_path_from_location(raw_name: str) -> Optional[str]: + """ + Return the path for the .egg-link file if it exists, otherwise, None. + + There's 3 scenarios: + 1) not in a virtualenv + try to find in site.USER_SITE, then site_packages + 2) in a no-global virtualenv + try to find in site_packages + 3) in a yes-global virtualenv + try to find in site_packages, then site.USER_SITE + (don't look in global location) + + For #1 and #3, there could be odd cases, where there's an egg-link in 2 + locations. + + This method will just return the first one found. + """ + sites: List[str] = [] + if running_under_virtualenv(): + sites.append(site_packages) + if not virtualenv_no_global() and user_site: + sites.append(user_site) + else: + if user_site: + sites.append(user_site) + sites.append(site_packages) + + egg_link_names = _egg_link_names(raw_name) + for site in sites: + for egg_link_name in egg_link_names: + egglink = os.path.join(site, egg_link_name) + if os.path.isfile(egglink): + return egglink + return None diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/entrypoints.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/entrypoints.py new file mode 100644 index 0000000000000000000000000000000000000000..150136938548af6aa5ae1f716b330d0eb2d3e013 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/entrypoints.py @@ -0,0 +1,84 @@ +import itertools +import os +import shutil +import sys +from typing import List, Optional + +from pip._internal.cli.main import main +from pip._internal.utils.compat import WINDOWS + +_EXECUTABLE_NAMES = [ + "pip", + f"pip{sys.version_info.major}", + f"pip{sys.version_info.major}.{sys.version_info.minor}", +] +if WINDOWS: + _allowed_extensions = {"", ".exe"} + _EXECUTABLE_NAMES = [ + "".join(parts) + for parts in itertools.product(_EXECUTABLE_NAMES, _allowed_extensions) + ] + + +def _wrapper(args: Optional[List[str]] = None) -> int: + """Central wrapper for all old entrypoints. + + Historically pip has had several entrypoints defined. Because of issues + arising from PATH, sys.path, multiple Pythons, their interactions, and most + of them having a pip installed, users suffer every time an entrypoint gets + moved. + + To alleviate this pain, and provide a mechanism for warning users and + directing them to an appropriate place for help, we now define all of + our old entrypoints as wrappers for the current one. + """ + sys.stderr.write( + "WARNING: pip is being invoked by an old script wrapper. This will " + "fail in a future version of pip.\n" + "Please see https://github.com/pypa/pip/issues/5599 for advice on " + "fixing the underlying issue.\n" + "To avoid this problem you can invoke Python with '-m pip' instead of " + "running pip directly.\n" + ) + return main(args) + + +def get_best_invocation_for_this_pip() -> str: + """Try to figure out the best way to invoke pip in the current environment.""" + binary_directory = "Scripts" if WINDOWS else "bin" + binary_prefix = os.path.join(sys.prefix, binary_directory) + + # Try to use pip[X[.Y]] names, if those executables for this environment are + # the first on PATH with that name. + path_parts = os.path.normcase(os.environ.get("PATH", "")).split(os.pathsep) + exe_are_in_PATH = os.path.normcase(binary_prefix) in path_parts + if exe_are_in_PATH: + for exe_name in _EXECUTABLE_NAMES: + found_executable = shutil.which(exe_name) + binary_executable = os.path.join(binary_prefix, exe_name) + if ( + found_executable + and os.path.exists(binary_executable) + and os.path.samefile( + found_executable, + binary_executable, + ) + ): + return exe_name + + # Use the `-m` invocation, if there's no "nice" invocation. + return f"{get_best_invocation_for_this_python()} -m pip" + + +def get_best_invocation_for_this_python() -> str: + """Try to figure out the best way to invoke the current Python.""" + exe = sys.executable + exe_name = os.path.basename(exe) + + # Try to use the basename, if it's the first executable. + found_executable = shutil.which(exe_name) + if found_executable and os.path.samefile(found_executable, exe): + return exe_name + + # Use the full executable name, because we couldn't find something simpler. + return exe diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/filesystem.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/filesystem.py new file mode 100644 index 0000000000000000000000000000000000000000..22e356cdd75ae69c05c5488d701e978e01c9e7a3 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/filesystem.py @@ -0,0 +1,149 @@ +import fnmatch +import os +import os.path +import random +import sys +from contextlib import contextmanager +from tempfile import NamedTemporaryFile +from typing import Any, BinaryIO, Generator, List, Union, cast + +from pip._internal.utils.compat import get_path_uid +from pip._internal.utils.misc import format_size +from pip._internal.utils.retry import retry + + +def check_path_owner(path: str) -> bool: + # If we don't have a way to check the effective uid of this process, then + # we'll just assume that we own the directory. + if sys.platform == "win32" or not hasattr(os, "geteuid"): + return True + + assert os.path.isabs(path) + + previous = None + while path != previous: + if os.path.lexists(path): + # Check if path is writable by current user. + if os.geteuid() == 0: + # Special handling for root user in order to handle properly + # cases where users use sudo without -H flag. + try: + path_uid = get_path_uid(path) + except OSError: + return False + return path_uid == 0 + else: + return os.access(path, os.W_OK) + else: + previous, path = path, os.path.dirname(path) + return False # assume we don't own the path + + +@contextmanager +def adjacent_tmp_file(path: str, **kwargs: Any) -> Generator[BinaryIO, None, None]: + """Return a file-like object pointing to a tmp file next to path. + + The file is created securely and is ensured to be written to disk + after the context reaches its end. + + kwargs will be passed to tempfile.NamedTemporaryFile to control + the way the temporary file will be opened. + """ + with NamedTemporaryFile( + delete=False, + dir=os.path.dirname(path), + prefix=os.path.basename(path), + suffix=".tmp", + **kwargs, + ) as f: + result = cast(BinaryIO, f) + try: + yield result + finally: + result.flush() + os.fsync(result.fileno()) + + +replace = retry(stop_after_delay=1, wait=0.25)(os.replace) + + +# test_writable_dir and _test_writable_dir_win are copied from Flit, +# with the author's agreement to also place them under pip's license. +def test_writable_dir(path: str) -> bool: + """Check if a directory is writable. + + Uses os.access() on POSIX, tries creating files on Windows. + """ + # If the directory doesn't exist, find the closest parent that does. + while not os.path.isdir(path): + parent = os.path.dirname(path) + if parent == path: + break # Should never get here, but infinite loops are bad + path = parent + + if os.name == "posix": + return os.access(path, os.W_OK) + + return _test_writable_dir_win(path) + + +def _test_writable_dir_win(path: str) -> bool: + # os.access doesn't work on Windows: http://bugs.python.org/issue2528 + # and we can't use tempfile: http://bugs.python.org/issue22107 + basename = "accesstest_deleteme_fishfingers_custard_" + alphabet = "abcdefghijklmnopqrstuvwxyz0123456789" + for _ in range(10): + name = basename + "".join(random.choice(alphabet) for _ in range(6)) + file = os.path.join(path, name) + try: + fd = os.open(file, os.O_RDWR | os.O_CREAT | os.O_EXCL) + except FileExistsError: + pass + except PermissionError: + # This could be because there's a directory with the same name. + # But it's highly unlikely there's a directory called that, + # so we'll assume it's because the parent dir is not writable. + # This could as well be because the parent dir is not readable, + # due to non-privileged user access. + return False + else: + os.close(fd) + os.unlink(file) + return True + + # This should never be reached + raise OSError("Unexpected condition testing for writable directory") + + +def find_files(path: str, pattern: str) -> List[str]: + """Returns a list of absolute paths of files beneath path, recursively, + with filenames which match the UNIX-style shell glob pattern.""" + result: List[str] = [] + for root, _, files in os.walk(path): + matches = fnmatch.filter(files, pattern) + result.extend(os.path.join(root, f) for f in matches) + return result + + +def file_size(path: str) -> Union[int, float]: + # If it's a symlink, return 0. + if os.path.islink(path): + return 0 + return os.path.getsize(path) + + +def format_file_size(path: str) -> str: + return format_size(file_size(path)) + + +def directory_size(path: str) -> Union[int, float]: + size = 0.0 + for root, _dirs, files in os.walk(path): + for filename in files: + file_path = os.path.join(root, filename) + size += file_size(file_path) + return size + + +def format_directory_size(path: str) -> str: + return format_size(directory_size(path)) diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/filetypes.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/filetypes.py new file mode 100644 index 0000000000000000000000000000000000000000..5948570178f3e6e79d1ff574241d09d4d8ed78de --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/filetypes.py @@ -0,0 +1,27 @@ +"""Filetype information. +""" + +from typing import Tuple + +from pip._internal.utils.misc import splitext + +WHEEL_EXTENSION = ".whl" +BZ2_EXTENSIONS: Tuple[str, ...] = (".tar.bz2", ".tbz") +XZ_EXTENSIONS: Tuple[str, ...] = ( + ".tar.xz", + ".txz", + ".tlz", + ".tar.lz", + ".tar.lzma", +) +ZIP_EXTENSIONS: Tuple[str, ...] = (".zip", WHEEL_EXTENSION) +TAR_EXTENSIONS: Tuple[str, ...] = (".tar.gz", ".tgz", ".tar") +ARCHIVE_EXTENSIONS = ZIP_EXTENSIONS + BZ2_EXTENSIONS + TAR_EXTENSIONS + XZ_EXTENSIONS + + +def is_archive_file(name: str) -> bool: + """Return True if `name` is a considered as an archive file.""" + ext = splitext(name)[1].lower() + if ext in ARCHIVE_EXTENSIONS: + return True + return False diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/glibc.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/glibc.py new file mode 100644 index 0000000000000000000000000000000000000000..998868ff2a482648024c848c9650d584403cbc8a --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/glibc.py @@ -0,0 +1,101 @@ +import os +import sys +from typing import Optional, Tuple + + +def glibc_version_string() -> Optional[str]: + "Returns glibc version string, or None if not using glibc." + return glibc_version_string_confstr() or glibc_version_string_ctypes() + + +def glibc_version_string_confstr() -> Optional[str]: + "Primary implementation of glibc_version_string using os.confstr." + # os.confstr is quite a bit faster than ctypes.DLL. It's also less likely + # to be broken or missing. This strategy is used in the standard library + # platform module: + # https://github.com/python/cpython/blob/fcf1d003bf4f0100c9d0921ff3d70e1127ca1b71/Lib/platform.py#L175-L183 + if sys.platform == "win32": + return None + try: + gnu_libc_version = os.confstr("CS_GNU_LIBC_VERSION") + if gnu_libc_version is None: + return None + # os.confstr("CS_GNU_LIBC_VERSION") returns a string like "glibc 2.17": + _, version = gnu_libc_version.split() + except (AttributeError, OSError, ValueError): + # os.confstr() or CS_GNU_LIBC_VERSION not available (or a bad value)... + return None + return version + + +def glibc_version_string_ctypes() -> Optional[str]: + "Fallback implementation of glibc_version_string using ctypes." + + try: + import ctypes + except ImportError: + return None + + # ctypes.CDLL(None) internally calls dlopen(NULL), and as the dlopen + # manpage says, "If filename is NULL, then the returned handle is for the + # main program". This way we can let the linker do the work to figure out + # which libc our process is actually using. + # + # We must also handle the special case where the executable is not a + # dynamically linked executable. This can occur when using musl libc, + # for example. In this situation, dlopen() will error, leading to an + # OSError. Interestingly, at least in the case of musl, there is no + # errno set on the OSError. The single string argument used to construct + # OSError comes from libc itself and is therefore not portable to + # hard code here. In any case, failure to call dlopen() means we + # can't proceed, so we bail on our attempt. + try: + process_namespace = ctypes.CDLL(None) + except OSError: + return None + + try: + gnu_get_libc_version = process_namespace.gnu_get_libc_version + except AttributeError: + # Symbol doesn't exist -> therefore, we are not linked to + # glibc. + return None + + # Call gnu_get_libc_version, which returns a string like "2.5" + gnu_get_libc_version.restype = ctypes.c_char_p + version_str: str = gnu_get_libc_version() + # py2 / py3 compatibility: + if not isinstance(version_str, str): + version_str = version_str.decode("ascii") + + return version_str + + +# platform.libc_ver regularly returns completely nonsensical glibc +# versions. E.g. on my computer, platform says: +# +# ~$ python2.7 -c 'import platform; print(platform.libc_ver())' +# ('glibc', '2.7') +# ~$ python3.5 -c 'import platform; print(platform.libc_ver())' +# ('glibc', '2.9') +# +# But the truth is: +# +# ~$ ldd --version +# ldd (Debian GLIBC 2.22-11) 2.22 +# +# This is unfortunate, because it means that the linehaul data on libc +# versions that was generated by pip 8.1.2 and earlier is useless and +# misleading. Solution: instead of using platform, use our code that actually +# works. +def libc_ver() -> Tuple[str, str]: + """Try to determine the glibc version + + Returns a tuple of strings (lib, version) which default to empty strings + in case the lookup fails. + """ + glibc_version = glibc_version_string() + if glibc_version is None: + return ("", "") + else: + return ("glibc", glibc_version) diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/hashes.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/hashes.py new file mode 100644 index 0000000000000000000000000000000000000000..535e94fca0cc8b049673ee0d02dba259c68af76c --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/hashes.py @@ -0,0 +1,147 @@ +import hashlib +from typing import TYPE_CHECKING, BinaryIO, Dict, Iterable, List, NoReturn, Optional + +from pip._internal.exceptions import HashMismatch, HashMissing, InstallationError +from pip._internal.utils.misc import read_chunks + +if TYPE_CHECKING: + from hashlib import _Hash + + +# The recommended hash algo of the moment. Change this whenever the state of +# the art changes; it won't hurt backward compatibility. +FAVORITE_HASH = "sha256" + + +# Names of hashlib algorithms allowed by the --hash option and ``pip hash`` +# Currently, those are the ones at least as collision-resistant as sha256. +STRONG_HASHES = ["sha256", "sha384", "sha512"] + + +class Hashes: + """A wrapper that builds multiple hashes at once and checks them against + known-good values + + """ + + def __init__(self, hashes: Optional[Dict[str, List[str]]] = None) -> None: + """ + :param hashes: A dict of algorithm names pointing to lists of allowed + hex digests + """ + allowed = {} + if hashes is not None: + for alg, keys in hashes.items(): + # Make sure values are always sorted (to ease equality checks) + allowed[alg] = [k.lower() for k in sorted(keys)] + self._allowed = allowed + + def __and__(self, other: "Hashes") -> "Hashes": + if not isinstance(other, Hashes): + return NotImplemented + + # If either of the Hashes object is entirely empty (i.e. no hash + # specified at all), all hashes from the other object are allowed. + if not other: + return self + if not self: + return other + + # Otherwise only hashes that present in both objects are allowed. + new = {} + for alg, values in other._allowed.items(): + if alg not in self._allowed: + continue + new[alg] = [v for v in values if v in self._allowed[alg]] + return Hashes(new) + + @property + def digest_count(self) -> int: + return sum(len(digests) for digests in self._allowed.values()) + + def is_hash_allowed(self, hash_name: str, hex_digest: str) -> bool: + """Return whether the given hex digest is allowed.""" + return hex_digest in self._allowed.get(hash_name, []) + + def check_against_chunks(self, chunks: Iterable[bytes]) -> None: + """Check good hashes against ones built from iterable of chunks of + data. + + Raise HashMismatch if none match. + + """ + gots = {} + for hash_name in self._allowed.keys(): + try: + gots[hash_name] = hashlib.new(hash_name) + except (ValueError, TypeError): + raise InstallationError(f"Unknown hash name: {hash_name}") + + for chunk in chunks: + for hash in gots.values(): + hash.update(chunk) + + for hash_name, got in gots.items(): + if got.hexdigest() in self._allowed[hash_name]: + return + self._raise(gots) + + def _raise(self, gots: Dict[str, "_Hash"]) -> "NoReturn": + raise HashMismatch(self._allowed, gots) + + def check_against_file(self, file: BinaryIO) -> None: + """Check good hashes against a file-like object + + Raise HashMismatch if none match. + + """ + return self.check_against_chunks(read_chunks(file)) + + def check_against_path(self, path: str) -> None: + with open(path, "rb") as file: + return self.check_against_file(file) + + def has_one_of(self, hashes: Dict[str, str]) -> bool: + """Return whether any of the given hashes are allowed.""" + for hash_name, hex_digest in hashes.items(): + if self.is_hash_allowed(hash_name, hex_digest): + return True + return False + + def __bool__(self) -> bool: + """Return whether I know any known-good hashes.""" + return bool(self._allowed) + + def __eq__(self, other: object) -> bool: + if not isinstance(other, Hashes): + return NotImplemented + return self._allowed == other._allowed + + def __hash__(self) -> int: + return hash( + ",".join( + sorted( + ":".join((alg, digest)) + for alg, digest_list in self._allowed.items() + for digest in digest_list + ) + ) + ) + + +class MissingHashes(Hashes): + """A workalike for Hashes used when we're missing a hash for a requirement + + It computes the actual hash of the requirement and raises a HashMissing + exception showing it to the user. + + """ + + def __init__(self) -> None: + """Don't offer the ``hashes`` kwarg.""" + # Pass our favorite hash in to generate a "gotten hash". With the + # empty list, it will never match, so an error will always raise. + super().__init__(hashes={FAVORITE_HASH: []}) + + def _raise(self, gots: Dict[str, "_Hash"]) -> "NoReturn": + raise HashMissing(gots[FAVORITE_HASH].hexdigest()) diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/logging.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/logging.py new file mode 100644 index 0000000000000000000000000000000000000000..62035fc40eca1311704175d80a5c7082a166924f --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/logging.py @@ -0,0 +1,354 @@ +import contextlib +import errno +import logging +import logging.handlers +import os +import sys +import threading +from dataclasses import dataclass +from io import TextIOWrapper +from logging import Filter +from typing import Any, ClassVar, Generator, List, Optional, TextIO, Type + +from pip._vendor.rich.console import ( + Console, + ConsoleOptions, + ConsoleRenderable, + RenderableType, + RenderResult, + RichCast, +) +from pip._vendor.rich.highlighter import NullHighlighter +from pip._vendor.rich.logging import RichHandler +from pip._vendor.rich.segment import Segment +from pip._vendor.rich.style import Style + +from pip._internal.utils._log import VERBOSE, getLogger +from pip._internal.utils.compat import WINDOWS +from pip._internal.utils.deprecation import DEPRECATION_MSG_PREFIX +from pip._internal.utils.misc import ensure_dir + +_log_state = threading.local() +subprocess_logger = getLogger("pip.subprocessor") + + +class BrokenStdoutLoggingError(Exception): + """ + Raised if BrokenPipeError occurs for the stdout stream while logging. + """ + + +def _is_broken_pipe_error(exc_class: Type[BaseException], exc: BaseException) -> bool: + if exc_class is BrokenPipeError: + return True + + # On Windows, a broken pipe can show up as EINVAL rather than EPIPE: + # https://bugs.python.org/issue19612 + # https://bugs.python.org/issue30418 + if not WINDOWS: + return False + + return isinstance(exc, OSError) and exc.errno in (errno.EINVAL, errno.EPIPE) + + +@contextlib.contextmanager +def indent_log(num: int = 2) -> Generator[None, None, None]: + """ + A context manager which will cause the log output to be indented for any + log messages emitted inside it. + """ + # For thread-safety + _log_state.indentation = get_indentation() + _log_state.indentation += num + try: + yield + finally: + _log_state.indentation -= num + + +def get_indentation() -> int: + return getattr(_log_state, "indentation", 0) + + +class IndentingFormatter(logging.Formatter): + default_time_format = "%Y-%m-%dT%H:%M:%S" + + def __init__( + self, + *args: Any, + add_timestamp: bool = False, + **kwargs: Any, + ) -> None: + """ + A logging.Formatter that obeys the indent_log() context manager. + + :param add_timestamp: A bool indicating output lines should be prefixed + with their record's timestamp. + """ + self.add_timestamp = add_timestamp + super().__init__(*args, **kwargs) + + def get_message_start(self, formatted: str, levelno: int) -> str: + """ + Return the start of the formatted log message (not counting the + prefix to add to each line). + """ + if levelno < logging.WARNING: + return "" + if formatted.startswith(DEPRECATION_MSG_PREFIX): + # Then the message already has a prefix. We don't want it to + # look like "WARNING: DEPRECATION: ...." + return "" + if levelno < logging.ERROR: + return "WARNING: " + + return "ERROR: " + + def format(self, record: logging.LogRecord) -> str: + """ + Calls the standard formatter, but will indent all of the log message + lines by our current indentation level. + """ + formatted = super().format(record) + message_start = self.get_message_start(formatted, record.levelno) + formatted = message_start + formatted + + prefix = "" + if self.add_timestamp: + prefix = f"{self.formatTime(record)} " + prefix += " " * get_indentation() + formatted = "".join([prefix + line for line in formatted.splitlines(True)]) + return formatted + + +@dataclass +class IndentedRenderable: + renderable: RenderableType + indent: int + + def __rich_console__( + self, console: Console, options: ConsoleOptions + ) -> RenderResult: + segments = console.render(self.renderable, options) + lines = Segment.split_lines(segments) + for line in lines: + yield Segment(" " * self.indent) + yield from line + yield Segment("\n") + + +class PipConsole(Console): + def on_broken_pipe(self) -> None: + # Reraise the original exception, rich 13.8.0+ exits by default + # instead, preventing our handler from firing. + raise BrokenPipeError() from None + + +class RichPipStreamHandler(RichHandler): + KEYWORDS: ClassVar[Optional[List[str]]] = [] + + def __init__(self, stream: Optional[TextIO], no_color: bool) -> None: + super().__init__( + console=PipConsole(file=stream, no_color=no_color, soft_wrap=True), + show_time=False, + show_level=False, + show_path=False, + highlighter=NullHighlighter(), + ) + + # Our custom override on Rich's logger, to make things work as we need them to. + def emit(self, record: logging.LogRecord) -> None: + style: Optional[Style] = None + + # If we are given a diagnostic error to present, present it with indentation. + if getattr(record, "rich", False): + assert isinstance(record.args, tuple) + (rich_renderable,) = record.args + assert isinstance( + rich_renderable, (ConsoleRenderable, RichCast, str) + ), f"{rich_renderable} is not rich-console-renderable" + + renderable: RenderableType = IndentedRenderable( + rich_renderable, indent=get_indentation() + ) + else: + message = self.format(record) + renderable = self.render_message(record, message) + if record.levelno is not None: + if record.levelno >= logging.ERROR: + style = Style(color="red") + elif record.levelno >= logging.WARNING: + style = Style(color="yellow") + + try: + self.console.print(renderable, overflow="ignore", crop=False, style=style) + except Exception: + self.handleError(record) + + def handleError(self, record: logging.LogRecord) -> None: + """Called when logging is unable to log some output.""" + + exc_class, exc = sys.exc_info()[:2] + # If a broken pipe occurred while calling write() or flush() on the + # stdout stream in logging's Handler.emit(), then raise our special + # exception so we can handle it in main() instead of logging the + # broken pipe error and continuing. + if ( + exc_class + and exc + and self.console.file is sys.stdout + and _is_broken_pipe_error(exc_class, exc) + ): + raise BrokenStdoutLoggingError() + + return super().handleError(record) + + +class BetterRotatingFileHandler(logging.handlers.RotatingFileHandler): + def _open(self) -> TextIOWrapper: + ensure_dir(os.path.dirname(self.baseFilename)) + return super()._open() + + +class MaxLevelFilter(Filter): + def __init__(self, level: int) -> None: + self.level = level + + def filter(self, record: logging.LogRecord) -> bool: + return record.levelno < self.level + + +class ExcludeLoggerFilter(Filter): + """ + A logging Filter that excludes records from a logger (or its children). + """ + + def filter(self, record: logging.LogRecord) -> bool: + # The base Filter class allows only records from a logger (or its + # children). + return not super().filter(record) + + +def setup_logging(verbosity: int, no_color: bool, user_log_file: Optional[str]) -> int: + """Configures and sets up all of the logging + + Returns the requested logging level, as its integer value. + """ + + # Determine the level to be logging at. + if verbosity >= 2: + level_number = logging.DEBUG + elif verbosity == 1: + level_number = VERBOSE + elif verbosity == -1: + level_number = logging.WARNING + elif verbosity == -2: + level_number = logging.ERROR + elif verbosity <= -3: + level_number = logging.CRITICAL + else: + level_number = logging.INFO + + level = logging.getLevelName(level_number) + + # The "root" logger should match the "console" level *unless* we also need + # to log to a user log file. + include_user_log = user_log_file is not None + if include_user_log: + additional_log_file = user_log_file + root_level = "DEBUG" + else: + additional_log_file = "/dev/null" + root_level = level + + # Disable any logging besides WARNING unless we have DEBUG level logging + # enabled for vendored libraries. + vendored_log_level = "WARNING" if level in ["INFO", "ERROR"] else "DEBUG" + + # Shorthands for clarity + log_streams = { + "stdout": "ext://sys.stdout", + "stderr": "ext://sys.stderr", + } + handler_classes = { + "stream": "pip._internal.utils.logging.RichPipStreamHandler", + "file": "pip._internal.utils.logging.BetterRotatingFileHandler", + } + handlers = ["console", "console_errors", "console_subprocess"] + ( + ["user_log"] if include_user_log else [] + ) + + logging.config.dictConfig( + { + "version": 1, + "disable_existing_loggers": False, + "filters": { + "exclude_warnings": { + "()": "pip._internal.utils.logging.MaxLevelFilter", + "level": logging.WARNING, + }, + "restrict_to_subprocess": { + "()": "logging.Filter", + "name": subprocess_logger.name, + }, + "exclude_subprocess": { + "()": "pip._internal.utils.logging.ExcludeLoggerFilter", + "name": subprocess_logger.name, + }, + }, + "formatters": { + "indent": { + "()": IndentingFormatter, + "format": "%(message)s", + }, + "indent_with_timestamp": { + "()": IndentingFormatter, + "format": "%(message)s", + "add_timestamp": True, + }, + }, + "handlers": { + "console": { + "level": level, + "class": handler_classes["stream"], + "no_color": no_color, + "stream": log_streams["stdout"], + "filters": ["exclude_subprocess", "exclude_warnings"], + "formatter": "indent", + }, + "console_errors": { + "level": "WARNING", + "class": handler_classes["stream"], + "no_color": no_color, + "stream": log_streams["stderr"], + "filters": ["exclude_subprocess"], + "formatter": "indent", + }, + # A handler responsible for logging to the console messages + # from the "subprocessor" logger. + "console_subprocess": { + "level": level, + "class": handler_classes["stream"], + "stream": log_streams["stderr"], + "no_color": no_color, + "filters": ["restrict_to_subprocess"], + "formatter": "indent", + }, + "user_log": { + "level": "DEBUG", + "class": handler_classes["file"], + "filename": additional_log_file, + "encoding": "utf-8", + "delay": True, + "formatter": "indent_with_timestamp", + }, + }, + "root": { + "level": root_level, + "handlers": handlers, + }, + "loggers": {"pip._vendor": {"level": vendored_log_level}}, + } + ) + + return level_number diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/misc.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/misc.py new file mode 100644 index 0000000000000000000000000000000000000000..44f6a05fbdd7f7b5779141f53b25b523af7e15eb --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/misc.py @@ -0,0 +1,773 @@ +import errno +import getpass +import hashlib +import logging +import os +import posixpath +import shutil +import stat +import sys +import sysconfig +import urllib.parse +from dataclasses import dataclass +from functools import partial +from io import StringIO +from itertools import filterfalse, tee, zip_longest +from pathlib import Path +from types import FunctionType, TracebackType +from typing import ( + Any, + BinaryIO, + Callable, + Generator, + Iterable, + Iterator, + List, + Mapping, + Optional, + Sequence, + TextIO, + Tuple, + Type, + TypeVar, + Union, + cast, +) + +from pip._vendor.packaging.requirements import Requirement +from pip._vendor.pyproject_hooks import BuildBackendHookCaller + +from pip import __version__ +from pip._internal.exceptions import CommandError, ExternallyManagedEnvironment +from pip._internal.locations import get_major_minor_version +from pip._internal.utils.compat import WINDOWS +from pip._internal.utils.retry import retry +from pip._internal.utils.virtualenv import running_under_virtualenv + +__all__ = [ + "rmtree", + "display_path", + "backup_dir", + "ask", + "splitext", + "format_size", + "is_installable_dir", + "normalize_path", + "renames", + "get_prog", + "ensure_dir", + "remove_auth_from_url", + "check_externally_managed", + "ConfiguredBuildBackendHookCaller", +] + +logger = logging.getLogger(__name__) + +T = TypeVar("T") +ExcInfo = Tuple[Type[BaseException], BaseException, TracebackType] +VersionInfo = Tuple[int, int, int] +NetlocTuple = Tuple[str, Tuple[Optional[str], Optional[str]]] +OnExc = Callable[[FunctionType, Path, BaseException], Any] +OnErr = Callable[[FunctionType, Path, ExcInfo], Any] + +FILE_CHUNK_SIZE = 1024 * 1024 + + +def get_pip_version() -> str: + pip_pkg_dir = os.path.join(os.path.dirname(__file__), "..", "..") + pip_pkg_dir = os.path.abspath(pip_pkg_dir) + + return f"pip {__version__} from {pip_pkg_dir} (python {get_major_minor_version()})" + + +def normalize_version_info(py_version_info: Tuple[int, ...]) -> Tuple[int, int, int]: + """ + Convert a tuple of ints representing a Python version to one of length + three. + + :param py_version_info: a tuple of ints representing a Python version, + or None to specify no version. The tuple can have any length. + + :return: a tuple of length three if `py_version_info` is non-None. + Otherwise, return `py_version_info` unchanged (i.e. None). + """ + if len(py_version_info) < 3: + py_version_info += (3 - len(py_version_info)) * (0,) + elif len(py_version_info) > 3: + py_version_info = py_version_info[:3] + + return cast("VersionInfo", py_version_info) + + +def ensure_dir(path: str) -> None: + """os.path.makedirs without EEXIST.""" + try: + os.makedirs(path) + except OSError as e: + # Windows can raise spurious ENOTEMPTY errors. See #6426. + if e.errno != errno.EEXIST and e.errno != errno.ENOTEMPTY: + raise + + +def get_prog() -> str: + try: + prog = os.path.basename(sys.argv[0]) + if prog in ("__main__.py", "-c"): + return f"{sys.executable} -m pip" + else: + return prog + except (AttributeError, TypeError, IndexError): + pass + return "pip" + + +# Retry every half second for up to 3 seconds +@retry(stop_after_delay=3, wait=0.5) +def rmtree( + dir: str, ignore_errors: bool = False, onexc: Optional[OnExc] = None +) -> None: + if ignore_errors: + onexc = _onerror_ignore + if onexc is None: + onexc = _onerror_reraise + handler: OnErr = partial(rmtree_errorhandler, onexc=onexc) + if sys.version_info >= (3, 12): + # See https://docs.python.org/3.12/whatsnew/3.12.html#shutil. + shutil.rmtree(dir, onexc=handler) # type: ignore + else: + shutil.rmtree(dir, onerror=handler) # type: ignore + + +def _onerror_ignore(*_args: Any) -> None: + pass + + +def _onerror_reraise(*_args: Any) -> None: + raise # noqa: PLE0704 - Bare exception used to reraise existing exception + + +def rmtree_errorhandler( + func: FunctionType, + path: Path, + exc_info: Union[ExcInfo, BaseException], + *, + onexc: OnExc = _onerror_reraise, +) -> None: + """ + `rmtree` error handler to 'force' a file remove (i.e. like `rm -f`). + + * If a file is readonly then it's write flag is set and operation is + retried. + + * `onerror` is the original callback from `rmtree(... onerror=onerror)` + that is chained at the end if the "rm -f" still fails. + """ + try: + st_mode = os.stat(path).st_mode + except OSError: + # it's equivalent to os.path.exists + return + + if not st_mode & stat.S_IWRITE: + # convert to read/write + try: + os.chmod(path, st_mode | stat.S_IWRITE) + except OSError: + pass + else: + # use the original function to repeat the operation + try: + func(path) + return + except OSError: + pass + + if not isinstance(exc_info, BaseException): + _, exc_info, _ = exc_info + onexc(func, path, exc_info) + + +def display_path(path: str) -> str: + """Gives the display value for a given path, making it relative to cwd + if possible.""" + path = os.path.normcase(os.path.abspath(path)) + if path.startswith(os.getcwd() + os.path.sep): + path = "." + path[len(os.getcwd()) :] + return path + + +def backup_dir(dir: str, ext: str = ".bak") -> str: + """Figure out the name of a directory to back up the given dir to + (adding .bak, .bak2, etc)""" + n = 1 + extension = ext + while os.path.exists(dir + extension): + n += 1 + extension = ext + str(n) + return dir + extension + + +def ask_path_exists(message: str, options: Iterable[str]) -> str: + for action in os.environ.get("PIP_EXISTS_ACTION", "").split(): + if action in options: + return action + return ask(message, options) + + +def _check_no_input(message: str) -> None: + """Raise an error if no input is allowed.""" + if os.environ.get("PIP_NO_INPUT"): + raise Exception( + f"No input was expected ($PIP_NO_INPUT set); question: {message}" + ) + + +def ask(message: str, options: Iterable[str]) -> str: + """Ask the message interactively, with the given possible responses""" + while 1: + _check_no_input(message) + response = input(message) + response = response.strip().lower() + if response not in options: + print( + "Your response ({!r}) was not one of the expected responses: " + "{}".format(response, ", ".join(options)) + ) + else: + return response + + +def ask_input(message: str) -> str: + """Ask for input interactively.""" + _check_no_input(message) + return input(message) + + +def ask_password(message: str) -> str: + """Ask for a password interactively.""" + _check_no_input(message) + return getpass.getpass(message) + + +def strtobool(val: str) -> int: + """Convert a string representation of truth to true (1) or false (0). + + True values are 'y', 'yes', 't', 'true', 'on', and '1'; false values + are 'n', 'no', 'f', 'false', 'off', and '0'. Raises ValueError if + 'val' is anything else. + """ + val = val.lower() + if val in ("y", "yes", "t", "true", "on", "1"): + return 1 + elif val in ("n", "no", "f", "false", "off", "0"): + return 0 + else: + raise ValueError(f"invalid truth value {val!r}") + + +def format_size(bytes: float) -> str: + if bytes > 1000 * 1000: + return f"{bytes / 1000.0 / 1000:.1f} MB" + elif bytes > 10 * 1000: + return f"{int(bytes / 1000)} kB" + elif bytes > 1000: + return f"{bytes / 1000.0:.1f} kB" + else: + return f"{int(bytes)} bytes" + + +def tabulate(rows: Iterable[Iterable[Any]]) -> Tuple[List[str], List[int]]: + """Return a list of formatted rows and a list of column sizes. + + For example:: + + >>> tabulate([['foobar', 2000], [0xdeadbeef]]) + (['foobar 2000', '3735928559'], [10, 4]) + """ + rows = [tuple(map(str, row)) for row in rows] + sizes = [max(map(len, col)) for col in zip_longest(*rows, fillvalue="")] + table = [" ".join(map(str.ljust, row, sizes)).rstrip() for row in rows] + return table, sizes + + +def is_installable_dir(path: str) -> bool: + """Is path is a directory containing pyproject.toml or setup.py? + + If pyproject.toml exists, this is a PEP 517 project. Otherwise we look for + a legacy setuptools layout by identifying setup.py. We don't check for the + setup.cfg because using it without setup.py is only available for PEP 517 + projects, which are already covered by the pyproject.toml check. + """ + if not os.path.isdir(path): + return False + if os.path.isfile(os.path.join(path, "pyproject.toml")): + return True + if os.path.isfile(os.path.join(path, "setup.py")): + return True + return False + + +def read_chunks( + file: BinaryIO, size: int = FILE_CHUNK_SIZE +) -> Generator[bytes, None, None]: + """Yield pieces of data from a file-like object until EOF.""" + while True: + chunk = file.read(size) + if not chunk: + break + yield chunk + + +def normalize_path(path: str, resolve_symlinks: bool = True) -> str: + """ + Convert a path to its canonical, case-normalized, absolute version. + + """ + path = os.path.expanduser(path) + if resolve_symlinks: + path = os.path.realpath(path) + else: + path = os.path.abspath(path) + return os.path.normcase(path) + + +def splitext(path: str) -> Tuple[str, str]: + """Like os.path.splitext, but take off .tar too""" + base, ext = posixpath.splitext(path) + if base.lower().endswith(".tar"): + ext = base[-4:] + ext + base = base[:-4] + return base, ext + + +def renames(old: str, new: str) -> None: + """Like os.renames(), but handles renaming across devices.""" + # Implementation borrowed from os.renames(). + head, tail = os.path.split(new) + if head and tail and not os.path.exists(head): + os.makedirs(head) + + shutil.move(old, new) + + head, tail = os.path.split(old) + if head and tail: + try: + os.removedirs(head) + except OSError: + pass + + +def is_local(path: str) -> bool: + """ + Return True if path is within sys.prefix, if we're running in a virtualenv. + + If we're not in a virtualenv, all paths are considered "local." + + Caution: this function assumes the head of path has been normalized + with normalize_path. + """ + if not running_under_virtualenv(): + return True + return path.startswith(normalize_path(sys.prefix)) + + +def write_output(msg: Any, *args: Any) -> None: + logger.info(msg, *args) + + +class StreamWrapper(StringIO): + orig_stream: TextIO + + @classmethod + def from_stream(cls, orig_stream: TextIO) -> "StreamWrapper": + ret = cls() + ret.orig_stream = orig_stream + return ret + + # compileall.compile_dir() needs stdout.encoding to print to stdout + # type ignore is because TextIOBase.encoding is writeable + @property + def encoding(self) -> str: # type: ignore + return self.orig_stream.encoding + + +# Simulates an enum +def enum(*sequential: Any, **named: Any) -> Type[Any]: + enums = dict(zip(sequential, range(len(sequential))), **named) + reverse = {value: key for key, value in enums.items()} + enums["reverse_mapping"] = reverse + return type("Enum", (), enums) + + +def build_netloc(host: str, port: Optional[int]) -> str: + """ + Build a netloc from a host-port pair + """ + if port is None: + return host + if ":" in host: + # Only wrap host with square brackets when it is IPv6 + host = f"[{host}]" + return f"{host}:{port}" + + +def build_url_from_netloc(netloc: str, scheme: str = "https") -> str: + """ + Build a full URL from a netloc. + """ + if netloc.count(":") >= 2 and "@" not in netloc and "[" not in netloc: + # It must be a bare IPv6 address, so wrap it with brackets. + netloc = f"[{netloc}]" + return f"{scheme}://{netloc}" + + +def parse_netloc(netloc: str) -> Tuple[Optional[str], Optional[int]]: + """ + Return the host-port pair from a netloc. + """ + url = build_url_from_netloc(netloc) + parsed = urllib.parse.urlparse(url) + return parsed.hostname, parsed.port + + +def split_auth_from_netloc(netloc: str) -> NetlocTuple: + """ + Parse out and remove the auth information from a netloc. + + Returns: (netloc, (username, password)). + """ + if "@" not in netloc: + return netloc, (None, None) + + # Split from the right because that's how urllib.parse.urlsplit() + # behaves if more than one @ is present (which can be checked using + # the password attribute of urlsplit()'s return value). + auth, netloc = netloc.rsplit("@", 1) + pw: Optional[str] = None + if ":" in auth: + # Split from the left because that's how urllib.parse.urlsplit() + # behaves if more than one : is present (which again can be checked + # using the password attribute of the return value) + user, pw = auth.split(":", 1) + else: + user, pw = auth, None + + user = urllib.parse.unquote(user) + if pw is not None: + pw = urllib.parse.unquote(pw) + + return netloc, (user, pw) + + +def redact_netloc(netloc: str) -> str: + """ + Replace the sensitive data in a netloc with "****", if it exists. + + For example: + - "user:pass@example.com" returns "user:****@example.com" + - "accesstoken@example.com" returns "****@example.com" + """ + netloc, (user, password) = split_auth_from_netloc(netloc) + if user is None: + return netloc + if password is None: + user = "****" + password = "" + else: + user = urllib.parse.quote(user) + password = ":****" + return f"{user}{password}@{netloc}" + + +def _transform_url( + url: str, transform_netloc: Callable[[str], Tuple[Any, ...]] +) -> Tuple[str, NetlocTuple]: + """Transform and replace netloc in a url. + + transform_netloc is a function taking the netloc and returning a + tuple. The first element of this tuple is the new netloc. The + entire tuple is returned. + + Returns a tuple containing the transformed url as item 0 and the + original tuple returned by transform_netloc as item 1. + """ + purl = urllib.parse.urlsplit(url) + netloc_tuple = transform_netloc(purl.netloc) + # stripped url + url_pieces = (purl.scheme, netloc_tuple[0], purl.path, purl.query, purl.fragment) + surl = urllib.parse.urlunsplit(url_pieces) + return surl, cast("NetlocTuple", netloc_tuple) + + +def _get_netloc(netloc: str) -> NetlocTuple: + return split_auth_from_netloc(netloc) + + +def _redact_netloc(netloc: str) -> Tuple[str]: + return (redact_netloc(netloc),) + + +def split_auth_netloc_from_url( + url: str, +) -> Tuple[str, str, Tuple[Optional[str], Optional[str]]]: + """ + Parse a url into separate netloc, auth, and url with no auth. + + Returns: (url_without_auth, netloc, (username, password)) + """ + url_without_auth, (netloc, auth) = _transform_url(url, _get_netloc) + return url_without_auth, netloc, auth + + +def remove_auth_from_url(url: str) -> str: + """Return a copy of url with 'username:password@' removed.""" + # username/pass params are passed to subversion through flags + # and are not recognized in the url. + return _transform_url(url, _get_netloc)[0] + + +def redact_auth_from_url(url: str) -> str: + """Replace the password in a given url with ****.""" + return _transform_url(url, _redact_netloc)[0] + + +def redact_auth_from_requirement(req: Requirement) -> str: + """Replace the password in a given requirement url with ****.""" + if not req.url: + return str(req) + return str(req).replace(req.url, redact_auth_from_url(req.url)) + + +@dataclass(frozen=True) +class HiddenText: + secret: str + redacted: str + + def __repr__(self) -> str: + return f"" + + def __str__(self) -> str: + return self.redacted + + # This is useful for testing. + def __eq__(self, other: Any) -> bool: + if type(self) is not type(other): + return False + + # The string being used for redaction doesn't also have to match, + # just the raw, original string. + return self.secret == other.secret + + +def hide_value(value: str) -> HiddenText: + return HiddenText(value, redacted="****") + + +def hide_url(url: str) -> HiddenText: + redacted = redact_auth_from_url(url) + return HiddenText(url, redacted=redacted) + + +def protect_pip_from_modification_on_windows(modifying_pip: bool) -> None: + """Protection of pip.exe from modification on Windows + + On Windows, any operation modifying pip should be run as: + python -m pip ... + """ + pip_names = [ + "pip", + f"pip{sys.version_info.major}", + f"pip{sys.version_info.major}.{sys.version_info.minor}", + ] + + # See https://github.com/pypa/pip/issues/1299 for more discussion + should_show_use_python_msg = ( + modifying_pip and WINDOWS and os.path.basename(sys.argv[0]) in pip_names + ) + + if should_show_use_python_msg: + new_command = [sys.executable, "-m", "pip"] + sys.argv[1:] + raise CommandError( + "To modify pip, please run the following command:\n{}".format( + " ".join(new_command) + ) + ) + + +def check_externally_managed() -> None: + """Check whether the current environment is externally managed. + + If the ``EXTERNALLY-MANAGED`` config file is found, the current environment + is considered externally managed, and an ExternallyManagedEnvironment is + raised. + """ + if running_under_virtualenv(): + return + marker = os.path.join(sysconfig.get_path("stdlib"), "EXTERNALLY-MANAGED") + if not os.path.isfile(marker): + return + raise ExternallyManagedEnvironment.from_config(marker) + + +def is_console_interactive() -> bool: + """Is this console interactive?""" + return sys.stdin is not None and sys.stdin.isatty() + + +def hash_file(path: str, blocksize: int = 1 << 20) -> Tuple[Any, int]: + """Return (hash, length) for path using hashlib.sha256()""" + + h = hashlib.sha256() + length = 0 + with open(path, "rb") as f: + for block in read_chunks(f, size=blocksize): + length += len(block) + h.update(block) + return h, length + + +def pairwise(iterable: Iterable[Any]) -> Iterator[Tuple[Any, Any]]: + """ + Return paired elements. + + For example: + s -> (s0, s1), (s2, s3), (s4, s5), ... + """ + iterable = iter(iterable) + return zip_longest(iterable, iterable) + + +def partition( + pred: Callable[[T], bool], iterable: Iterable[T] +) -> Tuple[Iterable[T], Iterable[T]]: + """ + Use a predicate to partition entries into false entries and true entries, + like + + partition(is_odd, range(10)) --> 0 2 4 6 8 and 1 3 5 7 9 + """ + t1, t2 = tee(iterable) + return filterfalse(pred, t1), filter(pred, t2) + + +class ConfiguredBuildBackendHookCaller(BuildBackendHookCaller): + def __init__( + self, + config_holder: Any, + source_dir: str, + build_backend: str, + backend_path: Optional[str] = None, + runner: Optional[Callable[..., None]] = None, + python_executable: Optional[str] = None, + ): + super().__init__( + source_dir, build_backend, backend_path, runner, python_executable + ) + self.config_holder = config_holder + + def build_wheel( + self, + wheel_directory: str, + config_settings: Optional[Mapping[str, Any]] = None, + metadata_directory: Optional[str] = None, + ) -> str: + cs = self.config_holder.config_settings + return super().build_wheel( + wheel_directory, config_settings=cs, metadata_directory=metadata_directory + ) + + def build_sdist( + self, + sdist_directory: str, + config_settings: Optional[Mapping[str, Any]] = None, + ) -> str: + cs = self.config_holder.config_settings + return super().build_sdist(sdist_directory, config_settings=cs) + + def build_editable( + self, + wheel_directory: str, + config_settings: Optional[Mapping[str, Any]] = None, + metadata_directory: Optional[str] = None, + ) -> str: + cs = self.config_holder.config_settings + return super().build_editable( + wheel_directory, config_settings=cs, metadata_directory=metadata_directory + ) + + def get_requires_for_build_wheel( + self, config_settings: Optional[Mapping[str, Any]] = None + ) -> Sequence[str]: + cs = self.config_holder.config_settings + return super().get_requires_for_build_wheel(config_settings=cs) + + def get_requires_for_build_sdist( + self, config_settings: Optional[Mapping[str, Any]] = None + ) -> Sequence[str]: + cs = self.config_holder.config_settings + return super().get_requires_for_build_sdist(config_settings=cs) + + def get_requires_for_build_editable( + self, config_settings: Optional[Mapping[str, Any]] = None + ) -> Sequence[str]: + cs = self.config_holder.config_settings + return super().get_requires_for_build_editable(config_settings=cs) + + def prepare_metadata_for_build_wheel( + self, + metadata_directory: str, + config_settings: Optional[Mapping[str, Any]] = None, + _allow_fallback: bool = True, + ) -> str: + cs = self.config_holder.config_settings + return super().prepare_metadata_for_build_wheel( + metadata_directory=metadata_directory, + config_settings=cs, + _allow_fallback=_allow_fallback, + ) + + def prepare_metadata_for_build_editable( + self, + metadata_directory: str, + config_settings: Optional[Mapping[str, Any]] = None, + _allow_fallback: bool = True, + ) -> Optional[str]: + cs = self.config_holder.config_settings + return super().prepare_metadata_for_build_editable( + metadata_directory=metadata_directory, + config_settings=cs, + _allow_fallback=_allow_fallback, + ) + + +def warn_if_run_as_root() -> None: + """Output a warning for sudo users on Unix. + + In a virtual environment, sudo pip still writes to virtualenv. + On Windows, users may run pip as Administrator without issues. + This warning only applies to Unix root users outside of virtualenv. + """ + if running_under_virtualenv(): + return + if not hasattr(os, "getuid"): + return + # On Windows, there are no "system managed" Python packages. Installing as + # Administrator via pip is the correct way of updating system environments. + # + # We choose sys.platform over utils.compat.WINDOWS here to enable Mypy platform + # checks: https://mypy.readthedocs.io/en/stable/common_issues.html + if sys.platform == "win32" or sys.platform == "cygwin": + return + + if os.getuid() != 0: + return + + logger.warning( + "Running pip as the 'root' user can result in broken permissions and " + "conflicting behaviour with the system package manager, possibly " + "rendering your system unusable. " + "It is recommended to use a virtual environment instead: " + "https://pip.pypa.io/warnings/venv. " + "Use the --root-user-action option if you know what you are doing and " + "want to suppress this warning." + ) diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/packaging.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/packaging.py new file mode 100644 index 0000000000000000000000000000000000000000..caad70f7fd17593769cbb5db99035e8c21b21a58 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/packaging.py @@ -0,0 +1,58 @@ +import functools +import logging +import re +from typing import NewType, Optional, Tuple, cast + +from pip._vendor.packaging import specifiers, version +from pip._vendor.packaging.requirements import Requirement + +NormalizedExtra = NewType("NormalizedExtra", str) + +logger = logging.getLogger(__name__) + + +@functools.lru_cache(maxsize=32) +def check_requires_python( + requires_python: Optional[str], version_info: Tuple[int, ...] +) -> bool: + """ + Check if the given Python version matches a "Requires-Python" specifier. + + :param version_info: A 3-tuple of ints representing a Python + major-minor-micro version to check (e.g. `sys.version_info[:3]`). + + :return: `True` if the given Python version satisfies the requirement. + Otherwise, return `False`. + + :raises InvalidSpecifier: If `requires_python` has an invalid format. + """ + if requires_python is None: + # The package provides no information + return True + requires_python_specifier = specifiers.SpecifierSet(requires_python) + + python_version = version.parse(".".join(map(str, version_info))) + return python_version in requires_python_specifier + + +@functools.lru_cache(maxsize=2048) +def get_requirement(req_string: str) -> Requirement: + """Construct a packaging.Requirement object with caching""" + # Parsing requirement strings is expensive, and is also expected to happen + # with a low diversity of different arguments (at least relative the number + # constructed). This method adds a cache to requirement object creation to + # minimize repeated parsing of the same string to construct equivalent + # Requirement objects. + return Requirement(req_string) + + +def safe_extra(extra: str) -> NormalizedExtra: + """Convert an arbitrary string to a standard 'extra' name + + Any runs of non-alphanumeric characters are replaced with a single '_', + and the result is always lowercased. + + This function is duplicated from ``pkg_resources``. Note that this is not + the same to either ``canonicalize_name`` or ``_egg_link_name``. + """ + return cast(NormalizedExtra, re.sub("[^A-Za-z0-9.-]+", "_", extra).lower()) diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/retry.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/retry.py new file mode 100644 index 0000000000000000000000000000000000000000..abfe07286ea747f656ea73f5a6919f1d66215847 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/retry.py @@ -0,0 +1,42 @@ +import functools +from time import perf_counter, sleep +from typing import Callable, TypeVar + +from pip._vendor.typing_extensions import ParamSpec + +T = TypeVar("T") +P = ParamSpec("P") + + +def retry( + wait: float, stop_after_delay: float +) -> Callable[[Callable[P, T]], Callable[P, T]]: + """Decorator to automatically retry a function on error. + + If the function raises, the function is recalled with the same arguments + until it returns or the time limit is reached. When the time limit is + surpassed, the last exception raised is reraised. + + :param wait: The time to wait after an error before retrying, in seconds. + :param stop_after_delay: The time limit after which retries will cease, + in seconds. + """ + + def wrapper(func: Callable[P, T]) -> Callable[P, T]: + + @functools.wraps(func) + def retry_wrapped(*args: P.args, **kwargs: P.kwargs) -> T: + # The performance counter is monotonic on all platforms we care + # about and has much better resolution than time.monotonic(). + start_time = perf_counter() + while True: + try: + return func(*args, **kwargs) + except Exception: + if perf_counter() - start_time > stop_after_delay: + raise + sleep(wait) + + return retry_wrapped + + return wrapper diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/subprocess.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/subprocess.py new file mode 100644 index 0000000000000000000000000000000000000000..cb2e23f007aca75c7e96e37df42ac0df6f2591e1 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/subprocess.py @@ -0,0 +1,245 @@ +import logging +import os +import shlex +import subprocess +from typing import Any, Callable, Iterable, List, Literal, Mapping, Optional, Union + +from pip._vendor.rich.markup import escape + +from pip._internal.cli.spinners import SpinnerInterface, open_spinner +from pip._internal.exceptions import InstallationSubprocessError +from pip._internal.utils.logging import VERBOSE, subprocess_logger +from pip._internal.utils.misc import HiddenText + +CommandArgs = List[Union[str, HiddenText]] + + +def make_command(*args: Union[str, HiddenText, CommandArgs]) -> CommandArgs: + """ + Create a CommandArgs object. + """ + command_args: CommandArgs = [] + for arg in args: + # Check for list instead of CommandArgs since CommandArgs is + # only known during type-checking. + if isinstance(arg, list): + command_args.extend(arg) + else: + # Otherwise, arg is str or HiddenText. + command_args.append(arg) + + return command_args + + +def format_command_args(args: Union[List[str], CommandArgs]) -> str: + """ + Format command arguments for display. + """ + # For HiddenText arguments, display the redacted form by calling str(). + # Also, we don't apply str() to arguments that aren't HiddenText since + # this can trigger a UnicodeDecodeError in Python 2 if the argument + # has type unicode and includes a non-ascii character. (The type + # checker doesn't ensure the annotations are correct in all cases.) + return " ".join( + shlex.quote(str(arg)) if isinstance(arg, HiddenText) else shlex.quote(arg) + for arg in args + ) + + +def reveal_command_args(args: Union[List[str], CommandArgs]) -> List[str]: + """ + Return the arguments in their raw, unredacted form. + """ + return [arg.secret if isinstance(arg, HiddenText) else arg for arg in args] + + +def call_subprocess( + cmd: Union[List[str], CommandArgs], + show_stdout: bool = False, + cwd: Optional[str] = None, + on_returncode: 'Literal["raise", "warn", "ignore"]' = "raise", + extra_ok_returncodes: Optional[Iterable[int]] = None, + extra_environ: Optional[Mapping[str, Any]] = None, + unset_environ: Optional[Iterable[str]] = None, + spinner: Optional[SpinnerInterface] = None, + log_failed_cmd: Optional[bool] = True, + stdout_only: Optional[bool] = False, + *, + command_desc: str, +) -> str: + """ + Args: + show_stdout: if true, use INFO to log the subprocess's stderr and + stdout streams. Otherwise, use DEBUG. Defaults to False. + extra_ok_returncodes: an iterable of integer return codes that are + acceptable, in addition to 0. Defaults to None, which means []. + unset_environ: an iterable of environment variable names to unset + prior to calling subprocess.Popen(). + log_failed_cmd: if false, failed commands are not logged, only raised. + stdout_only: if true, return only stdout, else return both. When true, + logging of both stdout and stderr occurs when the subprocess has + terminated, else logging occurs as subprocess output is produced. + """ + if extra_ok_returncodes is None: + extra_ok_returncodes = [] + if unset_environ is None: + unset_environ = [] + # Most places in pip use show_stdout=False. What this means is-- + # + # - We connect the child's output (combined stderr and stdout) to a + # single pipe, which we read. + # - We log this output to stderr at DEBUG level as it is received. + # - If DEBUG logging isn't enabled (e.g. if --verbose logging wasn't + # requested), then we show a spinner so the user can still see the + # subprocess is in progress. + # - If the subprocess exits with an error, we log the output to stderr + # at ERROR level if it hasn't already been displayed to the console + # (e.g. if --verbose logging wasn't enabled). This way we don't log + # the output to the console twice. + # + # If show_stdout=True, then the above is still done, but with DEBUG + # replaced by INFO. + if show_stdout: + # Then log the subprocess output at INFO level. + log_subprocess: Callable[..., None] = subprocess_logger.info + used_level = logging.INFO + else: + # Then log the subprocess output using VERBOSE. This also ensures + # it will be logged to the log file (aka user_log), if enabled. + log_subprocess = subprocess_logger.verbose + used_level = VERBOSE + + # Whether the subprocess will be visible in the console. + showing_subprocess = subprocess_logger.getEffectiveLevel() <= used_level + + # Only use the spinner if we're not showing the subprocess output + # and we have a spinner. + use_spinner = not showing_subprocess and spinner is not None + + log_subprocess("Running command %s", command_desc) + env = os.environ.copy() + if extra_environ: + env.update(extra_environ) + for name in unset_environ: + env.pop(name, None) + try: + proc = subprocess.Popen( + # Convert HiddenText objects to the underlying str. + reveal_command_args(cmd), + stdin=subprocess.PIPE, + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT if not stdout_only else subprocess.PIPE, + cwd=cwd, + env=env, + errors="backslashreplace", + ) + except Exception as exc: + if log_failed_cmd: + subprocess_logger.critical( + "Error %s while executing command %s", + exc, + command_desc, + ) + raise + all_output = [] + if not stdout_only: + assert proc.stdout + assert proc.stdin + proc.stdin.close() + # In this mode, stdout and stderr are in the same pipe. + while True: + line: str = proc.stdout.readline() + if not line: + break + line = line.rstrip() + all_output.append(line + "\n") + + # Show the line immediately. + log_subprocess(line) + # Update the spinner. + if use_spinner: + assert spinner + spinner.spin() + try: + proc.wait() + finally: + if proc.stdout: + proc.stdout.close() + output = "".join(all_output) + else: + # In this mode, stdout and stderr are in different pipes. + # We must use communicate() which is the only safe way to read both. + out, err = proc.communicate() + # log line by line to preserve pip log indenting + for out_line in out.splitlines(): + log_subprocess(out_line) + all_output.append(out) + for err_line in err.splitlines(): + log_subprocess(err_line) + all_output.append(err) + output = out + + proc_had_error = proc.returncode and proc.returncode not in extra_ok_returncodes + if use_spinner: + assert spinner + if proc_had_error: + spinner.finish("error") + else: + spinner.finish("done") + if proc_had_error: + if on_returncode == "raise": + error = InstallationSubprocessError( + command_description=command_desc, + exit_code=proc.returncode, + output_lines=all_output if not showing_subprocess else None, + ) + if log_failed_cmd: + subprocess_logger.error("%s", error, extra={"rich": True}) + subprocess_logger.verbose( + "[bold magenta]full command[/]: [blue]%s[/]", + escape(format_command_args(cmd)), + extra={"markup": True}, + ) + subprocess_logger.verbose( + "[bold magenta]cwd[/]: %s", + escape(cwd or "[inherit]"), + extra={"markup": True}, + ) + + raise error + elif on_returncode == "warn": + subprocess_logger.warning( + 'Command "%s" had error code %s in %s', + command_desc, + proc.returncode, + cwd, + ) + elif on_returncode == "ignore": + pass + else: + raise ValueError(f"Invalid value: on_returncode={on_returncode!r}") + return output + + +def runner_with_spinner_message(message: str) -> Callable[..., None]: + """Provide a subprocess_runner that shows a spinner message. + + Intended for use with for BuildBackendHookCaller. Thus, the runner has + an API that matches what's expected by BuildBackendHookCaller.subprocess_runner. + """ + + def runner( + cmd: List[str], + cwd: Optional[str] = None, + extra_environ: Optional[Mapping[str, Any]] = None, + ) -> None: + with open_spinner(message) as spinner: + call_subprocess( + cmd, + command_desc=message, + cwd=cwd, + extra_environ=extra_environ, + spinner=spinner, + ) + + return runner diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/temp_dir.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/temp_dir.py new file mode 100644 index 0000000000000000000000000000000000000000..06668e8ab2dad131106cd9e4963d871cea147997 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/temp_dir.py @@ -0,0 +1,296 @@ +import errno +import itertools +import logging +import os.path +import tempfile +import traceback +from contextlib import ExitStack, contextmanager +from pathlib import Path +from typing import ( + Any, + Callable, + Dict, + Generator, + List, + Optional, + TypeVar, + Union, +) + +from pip._internal.utils.misc import enum, rmtree + +logger = logging.getLogger(__name__) + +_T = TypeVar("_T", bound="TempDirectory") + + +# Kinds of temporary directories. Only needed for ones that are +# globally-managed. +tempdir_kinds = enum( + BUILD_ENV="build-env", + EPHEM_WHEEL_CACHE="ephem-wheel-cache", + REQ_BUILD="req-build", +) + + +_tempdir_manager: Optional[ExitStack] = None + + +@contextmanager +def global_tempdir_manager() -> Generator[None, None, None]: + global _tempdir_manager + with ExitStack() as stack: + old_tempdir_manager, _tempdir_manager = _tempdir_manager, stack + try: + yield + finally: + _tempdir_manager = old_tempdir_manager + + +class TempDirectoryTypeRegistry: + """Manages temp directory behavior""" + + def __init__(self) -> None: + self._should_delete: Dict[str, bool] = {} + + def set_delete(self, kind: str, value: bool) -> None: + """Indicate whether a TempDirectory of the given kind should be + auto-deleted. + """ + self._should_delete[kind] = value + + def get_delete(self, kind: str) -> bool: + """Get configured auto-delete flag for a given TempDirectory type, + default True. + """ + return self._should_delete.get(kind, True) + + +_tempdir_registry: Optional[TempDirectoryTypeRegistry] = None + + +@contextmanager +def tempdir_registry() -> Generator[TempDirectoryTypeRegistry, None, None]: + """Provides a scoped global tempdir registry that can be used to dictate + whether directories should be deleted. + """ + global _tempdir_registry + old_tempdir_registry = _tempdir_registry + _tempdir_registry = TempDirectoryTypeRegistry() + try: + yield _tempdir_registry + finally: + _tempdir_registry = old_tempdir_registry + + +class _Default: + pass + + +_default = _Default() + + +class TempDirectory: + """Helper class that owns and cleans up a temporary directory. + + This class can be used as a context manager or as an OO representation of a + temporary directory. + + Attributes: + path + Location to the created temporary directory + delete + Whether the directory should be deleted when exiting + (when used as a contextmanager) + + Methods: + cleanup() + Deletes the temporary directory + + When used as a context manager, if the delete attribute is True, on + exiting the context the temporary directory is deleted. + """ + + def __init__( + self, + path: Optional[str] = None, + delete: Union[bool, None, _Default] = _default, + kind: str = "temp", + globally_managed: bool = False, + ignore_cleanup_errors: bool = True, + ): + super().__init__() + + if delete is _default: + if path is not None: + # If we were given an explicit directory, resolve delete option + # now. + delete = False + else: + # Otherwise, we wait until cleanup and see what + # tempdir_registry says. + delete = None + + # The only time we specify path is in for editables where it + # is the value of the --src option. + if path is None: + path = self._create(kind) + + self._path = path + self._deleted = False + self.delete = delete + self.kind = kind + self.ignore_cleanup_errors = ignore_cleanup_errors + + if globally_managed: + assert _tempdir_manager is not None + _tempdir_manager.enter_context(self) + + @property + def path(self) -> str: + assert not self._deleted, f"Attempted to access deleted path: {self._path}" + return self._path + + def __repr__(self) -> str: + return f"<{self.__class__.__name__} {self.path!r}>" + + def __enter__(self: _T) -> _T: + return self + + def __exit__(self, exc: Any, value: Any, tb: Any) -> None: + if self.delete is not None: + delete = self.delete + elif _tempdir_registry: + delete = _tempdir_registry.get_delete(self.kind) + else: + delete = True + + if delete: + self.cleanup() + + def _create(self, kind: str) -> str: + """Create a temporary directory and store its path in self.path""" + # We realpath here because some systems have their default tmpdir + # symlinked to another directory. This tends to confuse build + # scripts, so we canonicalize the path by traversing potential + # symlinks here. + path = os.path.realpath(tempfile.mkdtemp(prefix=f"pip-{kind}-")) + logger.debug("Created temporary directory: %s", path) + return path + + def cleanup(self) -> None: + """Remove the temporary directory created and reset state""" + self._deleted = True + if not os.path.exists(self._path): + return + + errors: List[BaseException] = [] + + def onerror( + func: Callable[..., Any], + path: Path, + exc_val: BaseException, + ) -> None: + """Log a warning for a `rmtree` error and continue""" + formatted_exc = "\n".join( + traceback.format_exception_only(type(exc_val), exc_val) + ) + formatted_exc = formatted_exc.rstrip() # remove trailing new line + if func in (os.unlink, os.remove, os.rmdir): + logger.debug( + "Failed to remove a temporary file '%s' due to %s.\n", + path, + formatted_exc, + ) + else: + logger.debug("%s failed with %s.", func.__qualname__, formatted_exc) + errors.append(exc_val) + + if self.ignore_cleanup_errors: + try: + # first try with @retry; retrying to handle ephemeral errors + rmtree(self._path, ignore_errors=False) + except OSError: + # last pass ignore/log all errors + rmtree(self._path, onexc=onerror) + if errors: + logger.warning( + "Failed to remove contents in a temporary directory '%s'.\n" + "You can safely remove it manually.", + self._path, + ) + else: + rmtree(self._path) + + +class AdjacentTempDirectory(TempDirectory): + """Helper class that creates a temporary directory adjacent to a real one. + + Attributes: + original + The original directory to create a temp directory for. + path + After calling create() or entering, contains the full + path to the temporary directory. + delete + Whether the directory should be deleted when exiting + (when used as a contextmanager) + + """ + + # The characters that may be used to name the temp directory + # We always prepend a ~ and then rotate through these until + # a usable name is found. + # pkg_resources raises a different error for .dist-info folder + # with leading '-' and invalid metadata + LEADING_CHARS = "-~.=%0123456789" + + def __init__(self, original: str, delete: Optional[bool] = None) -> None: + self.original = original.rstrip("/\\") + super().__init__(delete=delete) + + @classmethod + def _generate_names(cls, name: str) -> Generator[str, None, None]: + """Generates a series of temporary names. + + The algorithm replaces the leading characters in the name + with ones that are valid filesystem characters, but are not + valid package names (for both Python and pip definitions of + package). + """ + for i in range(1, len(name)): + for candidate in itertools.combinations_with_replacement( + cls.LEADING_CHARS, i - 1 + ): + new_name = "~" + "".join(candidate) + name[i:] + if new_name != name: + yield new_name + + # If we make it this far, we will have to make a longer name + for i in range(len(cls.LEADING_CHARS)): + for candidate in itertools.combinations_with_replacement( + cls.LEADING_CHARS, i + ): + new_name = "~" + "".join(candidate) + name + if new_name != name: + yield new_name + + def _create(self, kind: str) -> str: + root, name = os.path.split(self.original) + for candidate in self._generate_names(name): + path = os.path.join(root, candidate) + try: + os.mkdir(path) + except OSError as ex: + # Continue if the name exists already + if ex.errno != errno.EEXIST: + raise + else: + path = os.path.realpath(path) + break + else: + # Final fallback on the default behavior. + path = os.path.realpath(tempfile.mkdtemp(prefix=f"pip-{kind}-")) + + logger.debug("Created temporary directory: %s", path) + return path diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/unpacking.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/unpacking.py new file mode 100644 index 0000000000000000000000000000000000000000..87a6d19ab5a9f9f305cbb45f62b8f918fc867946 --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/unpacking.py @@ -0,0 +1,337 @@ +"""Utilities related archives. +""" + +import logging +import os +import shutil +import stat +import sys +import tarfile +import zipfile +from typing import Iterable, List, Optional +from zipfile import ZipInfo + +from pip._internal.exceptions import InstallationError +from pip._internal.utils.filetypes import ( + BZ2_EXTENSIONS, + TAR_EXTENSIONS, + XZ_EXTENSIONS, + ZIP_EXTENSIONS, +) +from pip._internal.utils.misc import ensure_dir + +logger = logging.getLogger(__name__) + + +SUPPORTED_EXTENSIONS = ZIP_EXTENSIONS + TAR_EXTENSIONS + +try: + import bz2 # noqa + + SUPPORTED_EXTENSIONS += BZ2_EXTENSIONS +except ImportError: + logger.debug("bz2 module is not available") + +try: + # Only for Python 3.3+ + import lzma # noqa + + SUPPORTED_EXTENSIONS += XZ_EXTENSIONS +except ImportError: + logger.debug("lzma module is not available") + + +def current_umask() -> int: + """Get the current umask which involves having to set it temporarily.""" + mask = os.umask(0) + os.umask(mask) + return mask + + +def split_leading_dir(path: str) -> List[str]: + path = path.lstrip("/").lstrip("\\") + if "/" in path and ( + ("\\" in path and path.find("/") < path.find("\\")) or "\\" not in path + ): + return path.split("/", 1) + elif "\\" in path: + return path.split("\\", 1) + else: + return [path, ""] + + +def has_leading_dir(paths: Iterable[str]) -> bool: + """Returns true if all the paths have the same leading path name + (i.e., everything is in one subdirectory in an archive)""" + common_prefix = None + for path in paths: + prefix, rest = split_leading_dir(path) + if not prefix: + return False + elif common_prefix is None: + common_prefix = prefix + elif prefix != common_prefix: + return False + return True + + +def is_within_directory(directory: str, target: str) -> bool: + """ + Return true if the absolute path of target is within the directory + """ + abs_directory = os.path.abspath(directory) + abs_target = os.path.abspath(target) + + prefix = os.path.commonprefix([abs_directory, abs_target]) + return prefix == abs_directory + + +def _get_default_mode_plus_executable() -> int: + return 0o777 & ~current_umask() | 0o111 + + +def set_extracted_file_to_default_mode_plus_executable(path: str) -> None: + """ + Make file present at path have execute for user/group/world + (chmod +x) is no-op on windows per python docs + """ + os.chmod(path, _get_default_mode_plus_executable()) + + +def zip_item_is_executable(info: ZipInfo) -> bool: + mode = info.external_attr >> 16 + # if mode and regular file and any execute permissions for + # user/group/world? + return bool(mode and stat.S_ISREG(mode) and mode & 0o111) + + +def unzip_file(filename: str, location: str, flatten: bool = True) -> None: + """ + Unzip the file (with path `filename`) to the destination `location`. All + files are written based on system defaults and umask (i.e. permissions are + not preserved), except that regular file members with any execute + permissions (user, group, or world) have "chmod +x" applied after being + written. Note that for windows, any execute changes using os.chmod are + no-ops per the python docs. + """ + ensure_dir(location) + zipfp = open(filename, "rb") + try: + zip = zipfile.ZipFile(zipfp, allowZip64=True) + leading = has_leading_dir(zip.namelist()) and flatten + for info in zip.infolist(): + name = info.filename + fn = name + if leading: + fn = split_leading_dir(name)[1] + fn = os.path.join(location, fn) + dir = os.path.dirname(fn) + if not is_within_directory(location, fn): + message = ( + "The zip file ({}) has a file ({}) trying to install " + "outside target directory ({})" + ) + raise InstallationError(message.format(filename, fn, location)) + if fn.endswith("/") or fn.endswith("\\"): + # A directory + ensure_dir(fn) + else: + ensure_dir(dir) + # Don't use read() to avoid allocating an arbitrarily large + # chunk of memory for the file's content + fp = zip.open(name) + try: + with open(fn, "wb") as destfp: + shutil.copyfileobj(fp, destfp) + finally: + fp.close() + if zip_item_is_executable(info): + set_extracted_file_to_default_mode_plus_executable(fn) + finally: + zipfp.close() + + +def untar_file(filename: str, location: str) -> None: + """ + Untar the file (with path `filename`) to the destination `location`. + All files are written based on system defaults and umask (i.e. permissions + are not preserved), except that regular file members with any execute + permissions (user, group, or world) have "chmod +x" applied on top of the + default. Note that for windows, any execute changes using os.chmod are + no-ops per the python docs. + """ + ensure_dir(location) + if filename.lower().endswith(".gz") or filename.lower().endswith(".tgz"): + mode = "r:gz" + elif filename.lower().endswith(BZ2_EXTENSIONS): + mode = "r:bz2" + elif filename.lower().endswith(XZ_EXTENSIONS): + mode = "r:xz" + elif filename.lower().endswith(".tar"): + mode = "r" + else: + logger.warning( + "Cannot determine compression type for file %s", + filename, + ) + mode = "r:*" + + tar = tarfile.open(filename, mode, encoding="utf-8") # type: ignore + try: + leading = has_leading_dir([member.name for member in tar.getmembers()]) + + # PEP 706 added `tarfile.data_filter`, and made some other changes to + # Python's tarfile module (see below). The features were backported to + # security releases. + try: + data_filter = tarfile.data_filter + except AttributeError: + _untar_without_filter(filename, location, tar, leading) + else: + default_mode_plus_executable = _get_default_mode_plus_executable() + + if leading: + # Strip the leading directory from all files in the archive, + # including hardlink targets (which are relative to the + # unpack location). + for member in tar.getmembers(): + name_lead, name_rest = split_leading_dir(member.name) + member.name = name_rest + if member.islnk(): + lnk_lead, lnk_rest = split_leading_dir(member.linkname) + if lnk_lead == name_lead: + member.linkname = lnk_rest + + def pip_filter(member: tarfile.TarInfo, path: str) -> tarfile.TarInfo: + orig_mode = member.mode + try: + try: + member = data_filter(member, location) + except tarfile.LinkOutsideDestinationError: + if sys.version_info[:3] in { + (3, 8, 17), + (3, 9, 17), + (3, 10, 12), + (3, 11, 4), + }: + # The tarfile filter in specific Python versions + # raises LinkOutsideDestinationError on valid input + # (https://github.com/python/cpython/issues/107845) + # Ignore the error there, but do use the + # more lax `tar_filter` + member = tarfile.tar_filter(member, location) + else: + raise + except tarfile.TarError as exc: + message = "Invalid member in the tar file {}: {}" + # Filter error messages mention the member name. + # No need to add it here. + raise InstallationError( + message.format( + filename, + exc, + ) + ) + if member.isfile() and orig_mode & 0o111: + member.mode = default_mode_plus_executable + else: + # See PEP 706 note above. + # The PEP changed this from `int` to `Optional[int]`, + # where None means "use the default". Mypy doesn't + # know this yet. + member.mode = None # type: ignore [assignment] + return member + + tar.extractall(location, filter=pip_filter) + + finally: + tar.close() + + +def _untar_without_filter( + filename: str, + location: str, + tar: tarfile.TarFile, + leading: bool, +) -> None: + """Fallback for Python without tarfile.data_filter""" + for member in tar.getmembers(): + fn = member.name + if leading: + fn = split_leading_dir(fn)[1] + path = os.path.join(location, fn) + if not is_within_directory(location, path): + message = ( + "The tar file ({}) has a file ({}) trying to install " + "outside target directory ({})" + ) + raise InstallationError(message.format(filename, path, location)) + if member.isdir(): + ensure_dir(path) + elif member.issym(): + try: + tar._extract_member(member, path) + except Exception as exc: + # Some corrupt tar files seem to produce this + # (specifically bad symlinks) + logger.warning( + "In the tar file %s the member %s is invalid: %s", + filename, + member.name, + exc, + ) + continue + else: + try: + fp = tar.extractfile(member) + except (KeyError, AttributeError) as exc: + # Some corrupt tar files seem to produce this + # (specifically bad symlinks) + logger.warning( + "In the tar file %s the member %s is invalid: %s", + filename, + member.name, + exc, + ) + continue + ensure_dir(os.path.dirname(path)) + assert fp is not None + with open(path, "wb") as destfp: + shutil.copyfileobj(fp, destfp) + fp.close() + # Update the timestamp (useful for cython compiled files) + tar.utime(member, path) + # member have any execute permissions for user/group/world? + if member.mode & 0o111: + set_extracted_file_to_default_mode_plus_executable(path) + + +def unpack_file( + filename: str, + location: str, + content_type: Optional[str] = None, +) -> None: + filename = os.path.realpath(filename) + if ( + content_type == "application/zip" + or filename.lower().endswith(ZIP_EXTENSIONS) + or zipfile.is_zipfile(filename) + ): + unzip_file(filename, location, flatten=not filename.endswith(".whl")) + elif ( + content_type == "application/x-gzip" + or tarfile.is_tarfile(filename) + or filename.lower().endswith(TAR_EXTENSIONS + BZ2_EXTENSIONS + XZ_EXTENSIONS) + ): + untar_file(filename, location) + else: + # FIXME: handle? + # FIXME: magic signatures? + logger.critical( + "Cannot unpack file %s (downloaded from %s, content-type: %s); " + "cannot detect archive format", + filename, + location, + content_type, + ) + raise InstallationError(f"Cannot determine archive format of {location}") diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/urls.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/urls.py new file mode 100644 index 0000000000000000000000000000000000000000..9f34f882a1a6b7bf8e8ec5eb42c5d28f2c4e30aa --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/urls.py @@ -0,0 +1,55 @@ +import os +import string +import urllib.parse +import urllib.request + +from .compat import WINDOWS + + +def path_to_url(path: str) -> str: + """ + Convert a path to a file: URL. The path will be made absolute and have + quoted path parts. + """ + path = os.path.normpath(os.path.abspath(path)) + url = urllib.parse.urljoin("file:", urllib.request.pathname2url(path)) + return url + + +def url_to_path(url: str) -> str: + """ + Convert a file: URL to a path. + """ + assert url.startswith( + "file:" + ), f"You can only turn file: urls into filenames (not {url!r})" + + _, netloc, path, _, _ = urllib.parse.urlsplit(url) + + if not netloc or netloc == "localhost": + # According to RFC 8089, same as empty authority. + netloc = "" + elif WINDOWS: + # If we have a UNC path, prepend UNC share notation. + netloc = "\\\\" + netloc + else: + raise ValueError( + f"non-local file URIs are not supported on this platform: {url!r}" + ) + + path = urllib.request.url2pathname(netloc + path) + + # On Windows, urlsplit parses the path as something like "/C:/Users/foo". + # This creates issues for path-related functions like io.open(), so we try + # to detect and strip the leading slash. + if ( + WINDOWS + and not netloc # Not UNC. + and len(path) >= 3 + and path[0] == "/" # Leading slash to strip. + and path[1] in string.ascii_letters # Drive letter. + and path[2:4] in (":", ":/") # Colon + end of string, or colon + absolute path. + ): + path = path[1:] + + return path diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/virtualenv.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/virtualenv.py new file mode 100644 index 0000000000000000000000000000000000000000..882e36f5c1de19a8200000c216cf80119b37c96d --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/virtualenv.py @@ -0,0 +1,104 @@ +import logging +import os +import re +import site +import sys +from typing import List, Optional + +logger = logging.getLogger(__name__) +_INCLUDE_SYSTEM_SITE_PACKAGES_REGEX = re.compile( + r"include-system-site-packages\s*=\s*(?Ptrue|false)" +) + + +def _running_under_venv() -> bool: + """Checks if sys.base_prefix and sys.prefix match. + + This handles PEP 405 compliant virtual environments. + """ + return sys.prefix != getattr(sys, "base_prefix", sys.prefix) + + +def _running_under_legacy_virtualenv() -> bool: + """Checks if sys.real_prefix is set. + + This handles virtual environments created with pypa's virtualenv. + """ + # pypa/virtualenv case + return hasattr(sys, "real_prefix") + + +def running_under_virtualenv() -> bool: + """True if we're running inside a virtual environment, False otherwise.""" + return _running_under_venv() or _running_under_legacy_virtualenv() + + +def _get_pyvenv_cfg_lines() -> Optional[List[str]]: + """Reads {sys.prefix}/pyvenv.cfg and returns its contents as list of lines + + Returns None, if it could not read/access the file. + """ + pyvenv_cfg_file = os.path.join(sys.prefix, "pyvenv.cfg") + try: + # Although PEP 405 does not specify, the built-in venv module always + # writes with UTF-8. (pypa/pip#8717) + with open(pyvenv_cfg_file, encoding="utf-8") as f: + return f.read().splitlines() # avoids trailing newlines + except OSError: + return None + + +def _no_global_under_venv() -> bool: + """Check `{sys.prefix}/pyvenv.cfg` for system site-packages inclusion + + PEP 405 specifies that when system site-packages are not supposed to be + visible from a virtual environment, `pyvenv.cfg` must contain the following + line: + + include-system-site-packages = false + + Additionally, log a warning if accessing the file fails. + """ + cfg_lines = _get_pyvenv_cfg_lines() + if cfg_lines is None: + # We're not in a "sane" venv, so assume there is no system + # site-packages access (since that's PEP 405's default state). + logger.warning( + "Could not access 'pyvenv.cfg' despite a virtual environment " + "being active. Assuming global site-packages is not accessible " + "in this environment." + ) + return True + + for line in cfg_lines: + match = _INCLUDE_SYSTEM_SITE_PACKAGES_REGEX.match(line) + if match is not None and match.group("value") == "false": + return True + return False + + +def _no_global_under_legacy_virtualenv() -> bool: + """Check if "no-global-site-packages.txt" exists beside site.py + + This mirrors logic in pypa/virtualenv for determining whether system + site-packages are visible in the virtual environment. + """ + site_mod_dir = os.path.dirname(os.path.abspath(site.__file__)) + no_global_site_packages_file = os.path.join( + site_mod_dir, + "no-global-site-packages.txt", + ) + return os.path.exists(no_global_site_packages_file) + + +def virtualenv_no_global() -> bool: + """Returns a boolean, whether running in venv with no system site-packages.""" + # PEP 405 compliance needs to be checked first since virtualenv >=20 would + # return True for both checks, but is only able to use the PEP 405 config. + if _running_under_venv(): + return _no_global_under_venv() + + if _running_under_legacy_virtualenv(): + return _no_global_under_legacy_virtualenv() + + return False diff --git a/llava/lib/python3.10/site-packages/pip/_internal/utils/wheel.py b/llava/lib/python3.10/site-packages/pip/_internal/utils/wheel.py new file mode 100644 index 0000000000000000000000000000000000000000..f85aee8a3f925ad831431de5251c4e9daa6877ea --- /dev/null +++ b/llava/lib/python3.10/site-packages/pip/_internal/utils/wheel.py @@ -0,0 +1,134 @@ +"""Support functions for working with wheel files. +""" + +import logging +from email.message import Message +from email.parser import Parser +from typing import Tuple +from zipfile import BadZipFile, ZipFile + +from pip._vendor.packaging.utils import canonicalize_name + +from pip._internal.exceptions import UnsupportedWheel + +VERSION_COMPATIBLE = (1, 0) + + +logger = logging.getLogger(__name__) + + +def parse_wheel(wheel_zip: ZipFile, name: str) -> Tuple[str, Message]: + """Extract information from the provided wheel, ensuring it meets basic + standards. + + Returns the name of the .dist-info directory and the parsed WHEEL metadata. + """ + try: + info_dir = wheel_dist_info_dir(wheel_zip, name) + metadata = wheel_metadata(wheel_zip, info_dir) + version = wheel_version(metadata) + except UnsupportedWheel as e: + raise UnsupportedWheel(f"{name} has an invalid wheel, {e}") + + check_compatibility(version, name) + + return info_dir, metadata + + +def wheel_dist_info_dir(source: ZipFile, name: str) -> str: + """Returns the name of the contained .dist-info directory. + + Raises AssertionError or UnsupportedWheel if not found, >1 found, or + it doesn't match the provided name. + """ + # Zip file path separators must be / + subdirs = {p.split("/", 1)[0] for p in source.namelist()} + + info_dirs = [s for s in subdirs if s.endswith(".dist-info")] + + if not info_dirs: + raise UnsupportedWheel(".dist-info directory not found") + + if len(info_dirs) > 1: + raise UnsupportedWheel( + "multiple .dist-info directories found: {}".format(", ".join(info_dirs)) + ) + + info_dir = info_dirs[0] + + info_dir_name = canonicalize_name(info_dir) + canonical_name = canonicalize_name(name) + if not info_dir_name.startswith(canonical_name): + raise UnsupportedWheel( + f".dist-info directory {info_dir!r} does not start with {canonical_name!r}" + ) + + return info_dir + + +def read_wheel_metadata_file(source: ZipFile, path: str) -> bytes: + try: + return source.read(path) + # BadZipFile for general corruption, KeyError for missing entry, + # and RuntimeError for password-protected files + except (BadZipFile, KeyError, RuntimeError) as e: + raise UnsupportedWheel(f"could not read {path!r} file: {e!r}") + + +def wheel_metadata(source: ZipFile, dist_info_dir: str) -> Message: + """Return the WHEEL metadata of an extracted wheel, if possible. + Otherwise, raise UnsupportedWheel. + """ + path = f"{dist_info_dir}/WHEEL" + # Zip file path separators must be / + wheel_contents = read_wheel_metadata_file(source, path) + + try: + wheel_text = wheel_contents.decode() + except UnicodeDecodeError as e: + raise UnsupportedWheel(f"error decoding {path!r}: {e!r}") + + # FeedParser (used by Parser) does not raise any exceptions. The returned + # message may have .defects populated, but for backwards-compatibility we + # currently ignore them. + return Parser().parsestr(wheel_text) + + +def wheel_version(wheel_data: Message) -> Tuple[int, ...]: + """Given WHEEL metadata, return the parsed Wheel-Version. + Otherwise, raise UnsupportedWheel. + """ + version_text = wheel_data["Wheel-Version"] + if version_text is None: + raise UnsupportedWheel("WHEEL is missing Wheel-Version") + + version = version_text.strip() + + try: + return tuple(map(int, version.split("."))) + except ValueError: + raise UnsupportedWheel(f"invalid Wheel-Version: {version!r}") + + +def check_compatibility(version: Tuple[int, ...], name: str) -> None: + """Raises errors or warns if called with an incompatible Wheel-Version. + + pip should refuse to install a Wheel-Version that's a major series + ahead of what it's compatible with (e.g 2.0 > 1.1); and warn when + installing a version only minor version ahead (e.g 1.2 > 1.1). + + version: a 2-tuple representing a Wheel-Version (Major, Minor) + name: name of wheel or package to raise exception about + + :raises UnsupportedWheel: when an incompatible Wheel-Version is given + """ + if version[0] > VERSION_COMPATIBLE[0]: + raise UnsupportedWheel( + "{}'s Wheel-Version ({}) is not compatible with this version " + "of pip".format(name, ".".join(map(str, version))) + ) + elif version > VERSION_COMPATIBLE: + logger.warning( + "Installing from a newer Wheel-Version (%s)", + ".".join(map(str, version)), + ) diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/aiosignal/__pycache__/__init__.cpython-310.pyc b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/aiosignal/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..098ae17d35eb426bf2c4238f7e78ad031e26f21b Binary files /dev/null and b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/aiosignal/__pycache__/__init__.cpython-310.pyc differ diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/__init__.py b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..fe4aa581635bb30ee4e880366b1bbab6227fb148 --- /dev/null +++ b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/__init__.py @@ -0,0 +1,276 @@ +import asyncio +import enum +import sys +from types import TracebackType +from typing import Optional, Type, final + + +__version__ = "5.0.1" + + +__all__ = ("timeout", "timeout_at", "Timeout") + + +def timeout(delay: Optional[float]) -> "Timeout": + """timeout context manager. + + Useful in cases when you want to apply timeout logic around block + of code or in cases when asyncio.wait_for is not suitable. For example: + + >>> async with timeout(0.001): + ... async with aiohttp.get('https://github.com') as r: + ... await r.text() + + + delay - value in seconds or None to disable timeout logic + """ + loop = asyncio.get_running_loop() + if delay is not None: + deadline = loop.time() + delay # type: Optional[float] + else: + deadline = None + return Timeout(deadline, loop) + + +def timeout_at(deadline: Optional[float]) -> "Timeout": + """Schedule the timeout at absolute time. + + deadline argument points on the time in the same clock system + as loop.time(). + + Please note: it is not POSIX time but a time with + undefined starting base, e.g. the time of the system power on. + + >>> async with timeout_at(loop.time() + 10): + ... async with aiohttp.get('https://github.com') as r: + ... await r.text() + + + """ + loop = asyncio.get_running_loop() + return Timeout(deadline, loop) + + +class _State(enum.Enum): + INIT = "INIT" + ENTER = "ENTER" + TIMEOUT = "TIMEOUT" + EXIT = "EXIT" + + +if sys.version_info >= (3, 11): + + class _Expired: + __slots__ = ("_val",) + + def __init__(self, val: bool) -> None: + self._val = val + + def __call__(self) -> bool: + return self._val + + def __bool__(self) -> bool: + return self._val + + def __repr__(self) -> str: + return repr(self._val) + + def __str__(self) -> str: + return str(self._val) + + @final + class Timeout(asyncio.Timeout): # type: ignore[misc] + # Supports full asyncio.Timeout API. + # Also provides several asyncio_timeout specific methods + # for backward compatibility. + def __init__( + self, deadline: Optional[float], loop: asyncio.AbstractEventLoop + ) -> None: + super().__init__(deadline) + + @property + def expired(self) -> _Expired: + # a hacky property hat can provide both roles: + # timeout.expired() from asyncio + # timeout.expired from asyncio_timeout + return _Expired(super().expired()) + + @property + def deadline(self) -> Optional[float]: + return self.when() + + def reject(self) -> None: + """Reject scheduled timeout if any.""" + # cancel is maybe better name but + # task.cancel() raises CancelledError in asyncio world. + self.reschedule(None) + + def shift(self, delay: float) -> None: + """Advance timeout on delay seconds. + + The delay can be negative. + + Raise RuntimeError if shift is called when deadline is not scheduled + """ + deadline = self.when() + if deadline is None: + raise RuntimeError("cannot shift timeout if deadline is not scheduled") + self.reschedule(deadline + delay) + + def update(self, deadline: float) -> None: + """Set deadline to absolute value. + + deadline argument points on the time in the same clock system + as loop.time(). + + If new deadline is in the past the timeout is raised immediately. + + Please note: it is not POSIX time but a time with + undefined starting base, e.g. the time of the system power on. + """ + self.reschedule(deadline) + +else: + + @final + class Timeout: + # Internal class, please don't instantiate it directly + # Use timeout() and timeout_at() public factories instead. + # + # Implementation note: `async with timeout()` is preferred + # over `with timeout()`. + # While technically the Timeout class implementation + # doesn't need to be async at all, + # the `async with` statement explicitly points that + # the context manager should be used from async function context. + # + # This design allows to avoid many silly misusages. + # + # TimeoutError is raised immediately when scheduled + # if the deadline is passed. + # The purpose is to time out as soon as possible + # without waiting for the next await expression. + + __slots__ = ("_deadline", "_loop", "_state", "_timeout_handler", "_task") + + def __init__( + self, deadline: Optional[float], loop: asyncio.AbstractEventLoop + ) -> None: + self._loop = loop + self._state = _State.INIT + + self._task: Optional["asyncio.Task[object]"] = None + self._timeout_handler = None # type: Optional[asyncio.Handle] + if deadline is None: + self._deadline = None # type: Optional[float] + else: + self.update(deadline) + + async def __aenter__(self) -> "Timeout": + self._do_enter() + return self + + async def __aexit__( + self, + exc_type: Optional[Type[BaseException]], + exc_val: Optional[BaseException], + exc_tb: Optional[TracebackType], + ) -> Optional[bool]: + self._do_exit(exc_type) + return None + + @property + def expired(self) -> bool: + """Is timeout expired during execution?""" + return self._state == _State.TIMEOUT + + @property + def deadline(self) -> Optional[float]: + return self._deadline + + def reject(self) -> None: + """Reject scheduled timeout if any.""" + # cancel is maybe better name but + # task.cancel() raises CancelledError in asyncio world. + if self._state not in (_State.INIT, _State.ENTER): + raise RuntimeError(f"invalid state {self._state.value}") + self._reject() + + def _reject(self) -> None: + self._task = None + if self._timeout_handler is not None: + self._timeout_handler.cancel() + self._timeout_handler = None + + def shift(self, delay: float) -> None: + """Advance timeout on delay seconds. + + The delay can be negative. + + Raise RuntimeError if shift is called when deadline is not scheduled + """ + deadline = self._deadline + if deadline is None: + raise RuntimeError("cannot shift timeout if deadline is not scheduled") + self.update(deadline + delay) + + def update(self, deadline: float) -> None: + """Set deadline to absolute value. + + deadline argument points on the time in the same clock system + as loop.time(). + + If new deadline is in the past the timeout is raised immediately. + + Please note: it is not POSIX time but a time with + undefined starting base, e.g. the time of the system power on. + """ + if self._state == _State.EXIT: + raise RuntimeError("cannot reschedule after exit from context manager") + if self._state == _State.TIMEOUT: + raise RuntimeError("cannot reschedule expired timeout") + if self._timeout_handler is not None: + self._timeout_handler.cancel() + self._deadline = deadline + if self._state != _State.INIT: + self._reschedule() + + def _reschedule(self) -> None: + assert self._state == _State.ENTER + deadline = self._deadline + if deadline is None: + return + + now = self._loop.time() + if self._timeout_handler is not None: + self._timeout_handler.cancel() + + self._task = asyncio.current_task() + if deadline <= now: + self._timeout_handler = self._loop.call_soon(self._on_timeout) + else: + self._timeout_handler = self._loop.call_at(deadline, self._on_timeout) + + def _do_enter(self) -> None: + if self._state != _State.INIT: + raise RuntimeError(f"invalid state {self._state.value}") + self._state = _State.ENTER + self._reschedule() + + def _do_exit(self, exc_type: Optional[Type[BaseException]]) -> None: + if exc_type is asyncio.CancelledError and self._state == _State.TIMEOUT: + assert self._task is not None + self._timeout_handler = None + self._task = None + raise asyncio.TimeoutError + # timeout has not expired + self._state = _State.EXIT + self._reject() + return None + + def _on_timeout(self) -> None: + assert self._task is not None + self._task.cancel() + self._state = _State.TIMEOUT + # drop the reference early + self._timeout_handler = None diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/__pycache__/__init__.cpython-310.pyc b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..d3a5b55b475fcb4812e769bcdc87869dda98d7b6 Binary files /dev/null and b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/__pycache__/__init__.cpython-310.pyc differ diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/py.typed b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..3b94f915737aba1f12a0f067fdba3726bfe02df5 --- /dev/null +++ b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/async_timeout/py.typed @@ -0,0 +1 @@ +Placeholder diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/INSTALLER b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68 --- /dev/null +++ b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/INSTALLER @@ -0,0 +1 @@ +pip diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/LICENSE b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..8727172ae058e56805bd8ed0f988b6788711dcfd --- /dev/null +++ b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/LICENSE @@ -0,0 +1,13 @@ + Copyright 2016 Andrew Svetlov and aio-libs contributors + + 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. diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/METADATA b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..93f85177b97ec6be66b1ed74fc74cac756d1f72f --- /dev/null +++ b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/METADATA @@ -0,0 +1,140 @@ +Metadata-Version: 2.1 +Name: multidict +Version: 6.1.0 +Summary: multidict implementation +Home-page: https://github.com/aio-libs/multidict +Author: Andrew Svetlov +Author-email: andrew.svetlov@gmail.com +License: Apache 2 +Project-URL: Chat: Matrix, https://matrix.to/#/#aio-libs:matrix.org +Project-URL: Chat: Matrix Space, https://matrix.to/#/#aio-libs-space:matrix.org +Project-URL: CI: GitHub, https://github.com/aio-libs/multidict/actions +Project-URL: Code of Conduct, https://github.com/aio-libs/.github/blob/master/CODE_OF_CONDUCT.md +Project-URL: Coverage: codecov, https://codecov.io/github/aio-libs/multidict +Project-URL: Docs: Changelog, https://multidict.aio-libs.org/en/latest/changes/ +Project-URL: Docs: RTD, https://multidict.aio-libs.org +Project-URL: GitHub: issues, https://github.com/aio-libs/multidict/issues +Project-URL: GitHub: repo, https://github.com/aio-libs/multidict +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: Apache Software License +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 +Requires-Python: >=3.8 +Description-Content-Type: text/x-rst +License-File: LICENSE +Requires-Dist: typing-extensions >=4.1.0 ; python_version < "3.11" + +========= +multidict +========= + +.. image:: https://github.com/aio-libs/multidict/actions/workflows/ci-cd.yml/badge.svg + :target: https://github.com/aio-libs/multidict/actions + :alt: GitHub status for master branch + +.. image:: https://codecov.io/gh/aio-libs/multidict/branch/master/graph/badge.svg + :target: https://codecov.io/gh/aio-libs/multidict + :alt: Coverage metrics + +.. image:: https://img.shields.io/pypi/v/multidict.svg + :target: https://pypi.org/project/multidict + :alt: PyPI + +.. image:: https://readthedocs.org/projects/multidict/badge/?version=latest + :target: https://multidict.aio-libs.org + :alt: Read The Docs build status badge + +.. image:: https://img.shields.io/pypi/pyversions/multidict.svg + :target: https://pypi.org/project/multidict + :alt: Python versions + +.. image:: https://img.shields.io/matrix/aio-libs:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat + :target: https://matrix.to/#/%23aio-libs:matrix.org + :alt: Matrix Room — #aio-libs:matrix.org + +.. image:: https://img.shields.io/matrix/aio-libs-space:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs-space%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat + :target: https://matrix.to/#/%23aio-libs-space:matrix.org + :alt: Matrix Space — #aio-libs-space:matrix.org + +Multidict is dict-like collection of *key-value pairs* where key +might occur more than once in the container. + +Introduction +------------ + +*HTTP Headers* and *URL query string* require specific data structure: +*multidict*. It behaves mostly like a regular ``dict`` but it may have +several *values* for the same *key* and *preserves insertion ordering*. + +The *key* is ``str`` (or ``istr`` for case-insensitive dictionaries). + +``multidict`` has four multidict classes: +``MultiDict``, ``MultiDictProxy``, ``CIMultiDict`` +and ``CIMultiDictProxy``. + +Immutable proxies (``MultiDictProxy`` and +``CIMultiDictProxy``) provide a dynamic view for the +proxied multidict, the view reflects underlying collection changes. They +implement the ``collections.abc.Mapping`` interface. + +Regular mutable (``MultiDict`` and ``CIMultiDict``) classes +implement ``collections.abc.MutableMapping`` and allows them to change +their own content. + + +*Case insensitive* (``CIMultiDict`` and +``CIMultiDictProxy``) assume the *keys* are case +insensitive, e.g.:: + + >>> dct = CIMultiDict(key='val') + >>> 'Key' in dct + True + >>> dct['Key'] + 'val' + +*Keys* should be ``str`` or ``istr`` instances. + +The library has optional C Extensions for speed. + + +License +------- + +Apache 2 + +Library Installation +-------------------- + +.. code-block:: bash + + $ pip install multidict + +The library is Python 3 only! + +PyPI contains binary wheels for Linux, Windows and MacOS. If you want to install +``multidict`` on another operating system (or *Alpine Linux* inside a Docker) the +tarball will be used to compile the library from source. It requires a C compiler and +Python headers to be installed. + +To skip the compilation, please use the `MULTIDICT_NO_EXTENSIONS` environment variable, +e.g.: + +.. code-block:: bash + + $ MULTIDICT_NO_EXTENSIONS=1 pip install multidict + +Please note, the pure Python (uncompiled) version is about 20-50 times slower depending on +the usage scenario!!! + + + +Changelog +--------- +See `RTD page `_. diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/WHEEL b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..b6e74d77e356914988458dc5fed01455b694f089 --- /dev/null +++ b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/WHEEL @@ -0,0 +1,6 @@ +Wheel-Version: 1.0 +Generator: setuptools (74.1.2) +Root-Is-Purelib: false +Tag: cp310-cp310-manylinux_2_17_x86_64 +Tag: cp310-cp310-manylinux2014_x86_64 + diff --git a/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/top_level.txt b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..afcecdff08229f3faf1ecef41cf814c26c207f5c --- /dev/null +++ b/minigpt2/lib/python3.10/site-packages/ray/_private/runtime_env/agent/thirdparty_files/multidict-6.1.0.dist-info/top_level.txt @@ -0,0 +1 @@ +multidict diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_mode_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_mode_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f382aaa5c83d2c3fcf5e10b46e9abe43480f3dc2 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_mode_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _convolution_mode { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::string_view, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_convolution_mode") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_convolution_mode(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, str padding, SymInt[] dilation, SymInt groups) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..6f7a6f9e8df01408265b8b9cbb6b7a6e2c379817 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) +inline ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false) { + return at::_ops::_ctc_loss::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); +} + +// aten::_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) +inline ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, bool zero_infinity=false) { + return at::_ops::_ctc_loss_Tensor::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); +} + +// aten::_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _ctc_loss_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false) { + return at::_ops::_ctc_loss_out::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); +} +// aten::_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _ctc_loss_outf(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_ctc_loss_out::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); +} + +// aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _ctc_loss_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, bool zero_infinity=false) { + return at::_ops::_ctc_loss_Tensor_out::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); +} +// aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _ctc_loss_outf(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_ctc_loss_Tensor_out::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h new file mode 100644 index 0000000000000000000000000000000000000000..e57cb446c33e8083bad4e0ce672ae88e0f0ae660 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h @@ -0,0 +1,113 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template ::value>> + at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, scale, zero_point, memory_format); +} +namespace symint { + template ::value>> + at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, scale, zero_point, memory_format); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized_symint(c10::SymIntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template ::value>> + at::Tensor _empty_affine_quantized(c10::SymIntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(size, dtype, layout, device, pin_memory, scale, zero_point, memory_format); +} +namespace symint { + template ::value>> + at::Tensor _empty_affine_quantized(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(size, dtype, layout, device, pin_memory, scale, zero_point, memory_format); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_symint_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & _empty_affine_quantized_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_symint_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & _empty_affine_quantized_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); + } +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f3cd6728a550d3bddc18143858bb2f70ce18b7bd --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h @@ -0,0 +1,34 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0fac6dcbaa297209ac500d7c32d0b7a76db1bdef --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_norm_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_norm.Scalar(Tensor[] self, Scalar ord=2, ScalarType? dtype=None) -> Tensor[]") + static ::std::vector call(at::TensorList self, const at::Scalar & ord, ::std::optional dtype); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & ord, ::std::optional dtype); +}; + +struct TORCH_API _foreach_norm_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, ::std::optional, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, ScalarType? dtype=None, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, const at::Scalar & ord, ::std::optional dtype, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & ord, ::std::optional dtype, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5f92492099af308f36e7b7e2107e77779f8e9af1 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _int_mm_cpu(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _int_mm_out_cpu(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor _int_mm_cuda(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _int_mm_out_cuda(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1c4237d61256b1f4e22b4423483c40d8cefecc02 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _is_all_true { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_is_all_true") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_is_all_true(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mask_projection.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mask_projection.h new file mode 100644 index 0000000000000000000000000000000000000000..5fc8235cdffc1e38db5df6140b9fd3d374c6124d --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mask_projection.h @@ -0,0 +1,34 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_mask_projection.out(Tensor self, Tensor mask, bool accumulate_matches=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_mask_projection_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, bool accumulate_matches=false) { + return at::_ops::_sparse_mask_projection_out::call(self, mask, accumulate_matches, out); +} +// aten::_sparse_mask_projection.out(Tensor self, Tensor mask, bool accumulate_matches=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_mask_projection_outf(const at::Tensor & self, const at::Tensor & mask, bool accumulate_matches, at::Tensor & out) { + return at::_ops::_sparse_mask_projection_out::call(self, mask, accumulate_matches, out); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/amin_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/amin_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1f4c90e3063b8855836d18776a514be2cd99f738 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/amin_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_amin_out : public at::meta::structured_amin { +void impl(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/atan2_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/atan2_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13cbec1d1cca1273d8aa4db730f0a37a4100ca40 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/atan2_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor atan2(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & atan2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & atan2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & atan2_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..fc919ed41bb7e376f36373f6b8371c03a162a0e6 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::col_indices_copy(Tensor self) -> Tensor +inline at::Tensor col_indices_copy(const at::Tensor & self) { + return at::_ops::col_indices_copy::call(self); +} + +// aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & col_indices_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::col_indices_copy_out::call(self, out); +} +// aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & col_indices_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::col_indices_copy_out::call(self, out); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/combinations_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/combinations_native.h new file mode 100644 index 0000000000000000000000000000000000000000..19a66c44ef26352d236e5a49103faf3af61ba348 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/combinations_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor combinations(const at::Tensor & self, int64_t r=2, bool with_replacement=false); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/conv_depthwise3d.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/conv_depthwise3d.h new file mode 100644 index 0000000000000000000000000000000000000000..d35cd816d380b3746b0956602c88233b31e9c8fc --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/conv_depthwise3d.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::conv_depthwise3d(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias, SymInt[3] stride, SymInt[3] padding, SymInt[3] dilation) -> Tensor +inline at::Tensor conv_depthwise3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation) { + return at::_ops::conv_depthwise3d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation)); +} +namespace symint { + template ::value>> + at::Tensor conv_depthwise3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation) { + return at::_ops::conv_depthwise3d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation)); + } +} + +// aten::conv_depthwise3d(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias, SymInt[3] stride, SymInt[3] padding, SymInt[3] dilation) -> Tensor +inline at::Tensor conv_depthwise3d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation) { + return at::_ops::conv_depthwise3d::call(self, weight, kernel_size, bias, stride, padding, dilation); +} +namespace symint { + template ::value>> + at::Tensor conv_depthwise3d(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation) { + return at::_ops::conv_depthwise3d::call(self, weight, kernel_size, bias, stride, padding, dilation); + } +} + +// aten::conv_depthwise3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias, SymInt[3] stride, SymInt[3] padding, SymInt[3] dilation, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & conv_depthwise3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation) { + return at::_ops::conv_depthwise3d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template ::value>> + at::Tensor & conv_depthwise3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation) { + return at::_ops::conv_depthwise3d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::conv_depthwise3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias, SymInt[3] stride, SymInt[3] padding, SymInt[3] dilation, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & conv_depthwise3d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, at::Tensor & out) { + return at::_ops::conv_depthwise3d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template ::value>> + at::Tensor & conv_depthwise3d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, at::Tensor & out) { + return at::_ops::conv_depthwise3d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::conv_depthwise3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias, SymInt[3] stride, SymInt[3] padding, SymInt[3] dilation, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & conv_depthwise3d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation) { + return at::_ops::conv_depthwise3d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); +} +namespace symint { + template ::value>> + at::Tensor & conv_depthwise3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation) { + return at::_ops::conv_depthwise3d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); + } +} + +// aten::conv_depthwise3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias, SymInt[3] stride, SymInt[3] padding, SymInt[3] dilation, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & conv_depthwise3d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out) { + return at::_ops::conv_depthwise3d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); +} +namespace symint { + template ::value>> + at::Tensor & conv_depthwise3d_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out) { + return at::_ops::conv_depthwise3d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); + } +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_is_acceptable_compositeimplicitautograd_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_is_acceptable_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e0b13b069df5a602472531615f2def9c416e6c5a --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_is_acceptable_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API bool cudnn_is_acceptable(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_scatter_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_scatter_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9cf848832b94612a4882b7205ce03aa12e0009d2 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_scatter_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & diagonal_scatter_out(const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +TORCH_API at::Tensor diagonal_scatter(const at::Tensor & self, const at::Tensor & src, int64_t offset=0, int64_t dim1=0, int64_t dim2=1); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/dropout.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..d793b9847414c3f93fa0359e04cfa412745b667d --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/dropout.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::dropout(Tensor input, float p, bool train) -> Tensor +inline at::Tensor dropout(const at::Tensor & input, double p, bool train) { + return at::_ops::dropout::call(input, p, train); +} + +// aten::dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) +inline at::Tensor & dropout_(at::Tensor & self, double p, bool train) { + return at::_ops::dropout_::call(self, p, train); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/expm1_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/expm1_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ffd715868252dc0618251228f98a0df97f9b1303 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/expm1_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API expm1 { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::expm1") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "expm1(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API expm1_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::expm1_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "expm1_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API expm1_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::expm1") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cb1fe3d859e3f9a1c7b0abe0d041c18465a77ff1 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fake_quantize_per_channel_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ecc15bf7ab06a46aa2e290a333d93d0d41671a92 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor fmax(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmax_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/hypot_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/hypot_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..07a16a1ec721476c56cd6ce5b97f3a86f4d707a8 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/hypot_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor hypot(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & hypot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & hypot_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & hypot_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/istft.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/istft.h new file mode 100644 index 0000000000000000000000000000000000000000..4536becb8c4b47b7c5169daa0bfd3c86841191f3 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/istft.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::istft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, bool normalized=False, bool? onesided=None, int? length=None, bool return_complex=False) -> Tensor +inline at::Tensor istft(const at::Tensor & self, int64_t n_fft, ::std::optional hop_length=::std::nullopt, ::std::optional win_length=::std::nullopt, const ::std::optional & window={}, bool center=true, bool normalized=false, ::std::optional onesided=::std::nullopt, ::std::optional length=::std::nullopt, bool return_complex=false) { + return at::_ops::istft::call(self, n_fft, hop_length, win_length, window, center, normalized, onesided, length, return_complex); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_meta.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..8b179792fbe945e165f982a4efc0d29db988f41b --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_logaddexp2 : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..beecb029885332b7bdb25df4d73c4e4a14034d34 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::logit_backward.grad_input(Tensor grad_output, Tensor self, float? eps=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & logit_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::logit_backward_grad_input::call(grad_output, self, eps, grad_input); +} +// aten::logit_backward.grad_input(Tensor grad_output, Tensor self, float? eps=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & logit_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps, at::Tensor & grad_input) { + return at::_ops::logit_backward_grad_input::call(grad_output, self, eps, grad_input); +} + +// aten::logit_backward(Tensor grad_output, Tensor self, float? eps=None) -> Tensor +inline at::Tensor logit_backward(const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::logit_backward::call(grad_output, self, eps); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/maximum_compositeexplicitautogradnonfunctional_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/maximum_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bc26d25fb1ba658adf0ad9aad3d5c2f5a0c1f349 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/maximum_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor maximum(const at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..825327a26d6be139f928edb7f8adbbae4abbaa81 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor miopen_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cb61999b69974a3a0b4bde958da544af84d851a2 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & mkldnn_max_pool2d_out(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +TORCH_API at::Tensor mkldnn_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..51c913e158a8a772e3b70738364eae52f7f1eb22 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple mps_convolution_backward_out_symint(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/numpy_T_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/numpy_T_native.h new file mode 100644 index 0000000000000000000000000000000000000000..be123b40e0873f77378f8e545ecffc2671729137 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/numpy_T_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor numpy_T(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/one_hot_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/one_hot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f26843c9183189eb2966f6722df11fa8b0c34617 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/one_hot_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor one_hot(const at::Tensor & self, int64_t num_classes=-1); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/randint_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/randint_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cd5393fa3de3fc9ccbffc1cfa0ee43dd0ea7c8d7 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/randint_ops.h @@ -0,0 +1,105 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API randint { + using schema = at::Tensor (c10::SymInt, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randint(SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randint_generator { + using schema = at::Tensor (c10::SymInt, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randint.generator(SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randint_low { + using schema = at::Tensor (c10::SymInt, c10::SymInt, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "low") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randint.low(SymInt low, SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randint_low_generator { + using schema = at::Tensor (c10::SymInt, c10::SymInt, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "low_generator") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randint.low_generator(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randint_out { + using schema = at::Tensor & (c10::SymInt, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randint.out(SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out); +}; + +struct TORCH_API randint_generator_out { + using schema = at::Tensor & (c10::SymInt, c10::SymIntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randint.generator_out(SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API randint_low_out { + using schema = at::Tensor & (c10::SymInt, c10::SymInt, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "low_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randint.low_out(SymInt low, SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out); +}; + +struct TORCH_API randint_low_generator_out { + using schema = at::Tensor & (c10::SymInt, c10::SymInt, c10::SymIntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "low_generator_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randint.low_generator_out(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad1d_compositeexplicitautogradnonfunctional_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad1d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b79f15be13172a8f59ddd505115fa1cafdf49339 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad1d_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor reflection_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad3d_backward_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad3d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..de8337e6364af2fc66c1834def206fecc3da2690 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad3d_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor replication_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad3d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +TORCH_API at::Tensor & replication_pad3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/select_backward_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/select_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bd04dbd616c6f10b298381d63952ec87f7a96499 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/select_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API select_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, int64_t, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::select_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index); +}; + +struct TORCH_API select_backward_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, int64_t, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::select_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9737573bbc6051fae997e72a8b33091af803e354 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor slow_conv_transpose3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor slow_conv_transpose3d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_transpose3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor & slow_conv_transpose3d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out); +TORCH_API at::Tensor & slow_conv_transpose3d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_transpose3d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/softplus_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/softplus_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e7b8d071054b8dfcf0fd54188b13920b1cceff69 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/softplus_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_softplus_out : public at::meta::structured_softplus { +void impl(const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_compositeexplicitautograd_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..446a4de530b1c65fabcc5f03c88dcbbbfbcfb387 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor special_chebyshev_polynomial_t(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_t_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_t_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_chebyshev_polynomial_t(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_t_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_ndtr_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_ndtr_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37eb5d53d7c05ed26a683676d6fe6aa4be741937 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_ndtr_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_log_ndtr(const at::Tensor & self); +TORCH_API at::Tensor & special_log_ndtr_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_log_ndtr_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_ndtr_meta_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_ndtr_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..72d601723e994852ecb2c272013519ae272b1ff5 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_ndtr_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor special_log_ndtr(const at::Tensor & self); +TORCH_API at::Tensor & special_log_ndtr_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_log_ndtr_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_meta.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..c630d89f26cb41477f7938b49269e4469b9bc93a --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_modified_bessel_k1 : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t.h new file mode 100644 index 0000000000000000000000000000000000000000..17bbbe29e746cb39870f744ae9ff3f5323d7a101 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_shifted_chebyshev_polynomial_t(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_t(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_t::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_t.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_t(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_t_x_scalar::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_t.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_t(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_shifted_chebyshev_polynomial_t_n_scalar::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_t.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_t_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_t.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_t_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_t_out::call(x, n, out); +} + +// aten::special_shifted_chebyshev_polynomial_t.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_t_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_t_x_scalar_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_t.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_t_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_t_x_scalar_out::call(x, n, out); +} + +// aten::special_shifted_chebyshev_polynomial_t.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_shifted_chebyshev_polynomial_t_n_scalar_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_t.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_t_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_t_n_scalar_out::call(x, n, out); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_meta.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..8603be519b88c663c83bd4fb7f8de5edf1dd940e --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_shifted_chebyshev_polynomial_w : public TensorIteratorBase { + + + void meta(const at::Tensor & x, const at::Tensor & n); +}; + +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_zeta_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_zeta_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..862c8ee75d249bbdd7f511b190cb07a244feb207 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_zeta_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_zeta(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & special_zeta_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & special_zeta_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/threshold_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/threshold_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..72e37ccd2b5ca05e96d857585f13b3789e4be55f --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/threshold_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor threshold(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +TORCH_API at::Tensor & threshold_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +TORCH_API at::Tensor & threshold_outf(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & threshold_(at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); + +} // namespace cpu +} // namespace at