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setup.py
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setup.py
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#!/usr/bin/env python3
""" Install packages for faceswap.py """
# pylint:disable=too-many-lines
import logging
import ctypes
import json
import locale
import platform
import operator
import os
import re
import sys
import typing as T
from shutil import which
from subprocess import list2cmdline, PIPE, Popen, run, STDOUT
from pkg_resources import parse_requirements
from lib.logger import log_setup
logger = logging.getLogger(__name__)
backend_type: T.TypeAlias = T.Literal['nvidia', 'apple_silicon', 'directml', 'cpu', 'rocm', "all"]
_INSTALL_FAILED = False
# Packages that are explicitly required for setup.py
_INSTALLER_REQUIREMENTS: list[tuple[str, str]] = [("pexpect>=4.8.0", "!Windows"),
("pywinpty==2.0.2", "Windows")]
# Conda packages that are required for a specific backend
# TODO zlib-wapi is required on some Windows installs where cuDNN complains:
# Could not locate zlibwapi.dll. Please make sure it is in your library path!
# This only seems to occur on Anaconda cuDNN not conda-forge
_BACKEND_SPECIFIC_CONDA: dict[backend_type, list[str]] = {
"nvidia": ["cudatoolkit", "cudnn", "zlib-wapi"],
"apple_silicon": ["libblas"]}
# Packages that should only be installed through pip
_FORCE_PIP: dict[backend_type, list[str]] = {
"nvidia": ["tensorflow"],
"all": [
"tensorflow-cpu", # conda-forge leads to flatbuffer errors because of mixed sources
"imageio-ffmpeg"]} # 17/11/23 Conda forge uses incorrect ffmpeg, so fallback to pip
# Revisions of tensorflow GPU and cuda/cudnn requirements. These relate specifically to the
# Tensorflow builds available from pypi
_TENSORFLOW_REQUIREMENTS = {">=2.10.0,<2.11.0": [">=11.2,<11.3", ">=8.1,<8.2"]}
# ROCm min/max version requirements for Tensorflow
_TENSORFLOW_ROCM_REQUIREMENTS = {">=2.10.0,<2.11.0": ((5, 2, 0), (5, 4, 0))}
# TODO tensorflow-metal versioning
# Mapping of Python packages to their conda names if different from pip or in non-default channel
_CONDA_MAPPING: dict[str, tuple[str, str]] = {
"cudatoolkit": ("cudatoolkit", "conda-forge"),
"cudnn": ("cudnn", "conda-forge"),
"fastcluster": ("fastcluster", "conda-forge"),
"ffmpy": ("ffmpy", "conda-forge"),
# "imageio-ffmpeg": ("imageio-ffmpeg", "conda-forge"),
"nvidia-ml-py": ("nvidia-ml-py", "conda-forge"),
"tensorflow-deps": ("tensorflow-deps", "apple"),
"libblas": ("libblas", "conda-forge"),
"zlib-wapi": ("zlib-wapi", "conda-forge"),
"xorg-libxft": ("xorg-libxft", "conda-forge")}
# Force output to utf-8
sys.stdout.reconfigure(encoding="utf-8", errors="replace") # type:ignore[attr-defined]
class Environment():
""" The current install environment
Parameters
----------
updater: bool, Optional
``True`` if the script is being called by Faceswap's internal updater. ``False`` if full
setup is running. Default: ``False``
"""
_backends = (("nvidia", "apple_silicon", "directml", "rocm", "cpu"))
def __init__(self, updater: bool = False) -> None:
self.updater = updater
# Flag that setup is being run by installer so steps can be skipped
self.is_installer: bool = False
self.backend: backend_type | None = None
self.enable_docker: bool = False
self.cuda_cudnn = ["", ""]
self.rocm_version: tuple[int, ...] = (0, 0, 0)
self._process_arguments()
self._check_permission()
self._check_system()
self._check_python()
self._output_runtime_info()
self._check_pip()
self._upgrade_pip()
self._set_env_vars()
@property
def encoding(self) -> str:
""" Get system encoding """
return locale.getpreferredencoding()
@property
def os_version(self) -> tuple[str, str]:
""" Get OS Version """
return platform.system(), platform.release()
@property
def py_version(self) -> tuple[str, str]:
""" Get Python Version """
return platform.python_version(), platform.architecture()[0]
@property
def is_conda(self) -> bool:
""" Check whether using Conda """
return ("conda" in sys.version.lower() or
os.path.exists(os.path.join(sys.prefix, 'conda-meta')))
@property
def is_admin(self) -> bool:
""" Check whether user is admin """
try:
retval = os.getuid() == 0 # type: ignore
except AttributeError:
retval = ctypes.windll.shell32.IsUserAnAdmin() != 0 # type: ignore
return retval
@property
def cuda_version(self) -> str:
""" str: The detected globally installed Cuda Version """
return self.cuda_cudnn[0]
@property
def cudnn_version(self) -> str:
""" str: The detected globally installed cuDNN Version """
return self.cuda_cudnn[1]
@property
def is_virtualenv(self) -> bool:
""" Check whether this is a virtual environment """
if not self.is_conda:
retval = (hasattr(sys, "real_prefix") or
(hasattr(sys, "base_prefix") and sys.base_prefix != sys.prefix))
else:
prefix = os.path.dirname(sys.prefix)
retval = os.path.basename(prefix) == "envs"
return retval
def _process_arguments(self) -> None:
""" Process any cli arguments and dummy in cli arguments if calling from updater. """
args = [arg for arg in sys.argv] # pylint:disable=unnecessary-comprehension
if self.updater:
from lib.utils import get_backend # pylint:disable=import-outside-toplevel
args.append(f"--{get_backend()}")
logger.debug(args)
for arg in args:
if arg == "--installer":
self.is_installer = True
if not self.backend and (arg.startswith("--") and
arg.replace("--", "") in self._backends):
self.backend = arg.replace("--", "").lower() # type:ignore
def _check_permission(self) -> None:
""" Check for Admin permissions """
if self.updater:
return
if self.is_admin:
logger.info("Running as Root/Admin")
else:
logger.info("Running without root/admin privileges")
def _check_system(self) -> None:
""" Check the system """
if not self.updater:
logger.info("The tool provides tips for installation and installs required python "
"packages")
logger.info("Setup in %s %s", self.os_version[0], self.os_version[1])
if not self.updater and not self.os_version[0] in ["Windows", "Linux", "Darwin"]:
logger.error("Your system %s is not supported!", self.os_version[0])
sys.exit(1)
if self.os_version[0].lower() == "darwin" and platform.machine() == "arm64":
self.backend = "apple_silicon"
if not self.updater and not self.is_conda:
logger.error("Setting up Faceswap for Apple Silicon outside of a Conda "
"environment is unsupported")
sys.exit(1)
def _check_python(self) -> None:
""" Check python and virtual environment status """
logger.info("Installed Python: %s %s", self.py_version[0], self.py_version[1])
if self.updater:
return
if not ((3, 10) <= sys.version_info < (3, 11) and self.py_version[1] == "64bit"):
logger.error("Please run this script with Python version 3.10 64bit and try "
"again.")
sys.exit(1)
def _output_runtime_info(self) -> None:
""" Output run time info """
if self.is_conda:
logger.info("Running in Conda")
if self.is_virtualenv:
logger.info("Running in a Virtual Environment")
logger.info("Encoding: %s", self.encoding)
def _check_pip(self) -> None:
""" Check installed pip version """
if self.updater:
return
try:
import pip # noqa pylint:disable=unused-import,import-outside-toplevel
except ImportError:
logger.error("Import pip failed. Please Install python3-pip and try again")
sys.exit(1)
def _upgrade_pip(self) -> None:
""" Upgrade pip to latest version """
if not self.is_conda:
# Don't do this with Conda, as we must use Conda version of pip
logger.info("Upgrading pip...")
pipexe = [sys.executable, "-m", "pip"]
pipexe.extend(["install", "--no-cache-dir", "-qq", "--upgrade"])
if not self.is_admin and not self.is_virtualenv:
pipexe.append("--user")
pipexe.append("pip")
run(pipexe, check=True)
import pip # pylint:disable=import-outside-toplevel
pip_version = pip.__version__
logger.info("Installed pip: %s", pip_version)
def set_config(self) -> None:
""" Set the backend in the faceswap config file """
config = {"backend": self.backend}
pypath = os.path.dirname(os.path.realpath(__file__))
config_file = os.path.join(pypath, "config", ".faceswap")
with open(config_file, "w", encoding="utf8") as cnf:
json.dump(config, cnf)
logger.info("Faceswap config written to: %s", config_file)
def _set_env_vars(self) -> None:
""" There are some foibles under Conda which need to be worked around in different
situations.
Linux:
Update the LD_LIBRARY_PATH environment variable when activating a conda environment
and revert it when deactivating.
Notes
-----
From Tensorflow 2.7, installing Cuda Toolkit from conda-forge and tensorflow from pip
causes tensorflow to not be able to locate shared libs and hence not use the GPU.
We update the environment variable for all instances using Conda as it shouldn't hurt
anything and may help avoid conflicts with globally installed Cuda
"""
if not self.is_conda:
return
linux_update = self.os_version[0].lower() == "linux" and self.backend == "nvidia"
if not linux_update:
return
conda_prefix = os.environ["CONDA_PREFIX"]
activate_folder = os.path.join(conda_prefix, "etc", "conda", "activate.d")
deactivate_folder = os.path.join(conda_prefix, "etc", "conda", "deactivate.d")
os.makedirs(activate_folder, exist_ok=True)
os.makedirs(deactivate_folder, exist_ok=True)
activate_script = os.path.join(conda_prefix, activate_folder, "env_vars.sh")
deactivate_script = os.path.join(conda_prefix, deactivate_folder, "env_vars.sh")
if os.path.isfile(activate_script):
# Only create file if it does not already exist. There may be instances where people
# have created their own scripts, but these should be few and far between and those
# people should already know what they are doing.
return
conda_libs = os.path.join(conda_prefix, "lib")
activate = ["#!/bin/sh\n\n",
"export OLD_LD_LIBRARY_PATH=${LD_LIBRARY_PATH}\n",
f"export LD_LIBRARY_PATH='{conda_libs}':${{LD_LIBRARY_PATH}}\n"]
deactivate = ["#!/bin/sh\n\n",
"export LD_LIBRARY_PATH=${OLD_LD_LIBRARY_PATH}\n",
"unset OLD_LD_LIBRARY_PATH\n"]
logger.info("Cuda search path set to '%s'", conda_libs)
with open(activate_script, "w", encoding="utf8") as afile:
afile.writelines(activate)
with open(deactivate_script, "w", encoding="utf8") as afile:
afile.writelines(deactivate)
class Packages():
""" Holds information about installed and required packages.
Handles updating dependencies based on running platform/backend
Parameters
----------
environment: :class:`Environment`
Environment class holding information about the running system
"""
def __init__(self, environment: Environment) -> None:
self._env = environment
# Default TK has bad fonts under Linux. There is a better build in Conda-Forge, so set
# channel accordingly
tk_channel = "conda-forge" if self._env.os_version[0].lower() == "linux" else "default"
self._conda_required_packages: list[tuple[list[str] | str, str]] = [("tk", tk_channel),
("git", "default")]
self._update_backend_specific_conda()
self._installed_packages = self._get_installed_packages()
self._conda_installed_packages = self._get_installed_conda_packages()
self._required_packages: list[tuple[str, list[tuple[str, str]]]] = []
self._missing_packages: list[tuple[str, list[tuple[str, str]]]] = []
self._conda_missing_packages: list[tuple[list[str] | str, str]] = []
@property
def prerequisites(self) -> list[tuple[str, list[tuple[str, str]]]]:
""" list: Any required packages that the installer needs prior to installing the faceswap
environment on the specific platform that are not already installed """
all_installed = self._all_installed_packages
candidates = self._format_requirements(
[pkg for pkg, plat in _INSTALLER_REQUIREMENTS
if self._env.os_version[0] == plat or (plat[0] == "!" and
self._env.os_version[0] != plat[1:])])
retval = [(pkg, spec) for pkg, spec in candidates
if pkg not in all_installed or (
pkg in all_installed and
not self._validate_spec(spec, all_installed.get(pkg, ""))
)]
return retval
@property
def packages_need_install(self) -> bool:
"""bool: ``True`` if there are packages available that need to be installed """
return bool(self._missing_packages or self._conda_missing_packages)
@property
def to_install(self) -> list[tuple[str, list[tuple[str, str]]]]:
""" list: The required packages that need to be installed """
return self._missing_packages
@property
def to_install_conda(self) -> list[tuple[list[str] | str, str]]:
""" list: The required conda packages that need to be installed """
return self._conda_missing_packages
@property
def _all_installed_packages(self) -> dict[str, str]:
""" dict[str, str]: The package names and version string for all installed packages across
pip and conda """
return {**self._installed_packages, **self._conda_installed_packages}
def _update_backend_specific_conda(self) -> None:
""" Add backend specific packages to Conda required packages """
assert self._env.backend is not None
to_add = _BACKEND_SPECIFIC_CONDA.get(self._env.backend)
if not to_add:
logger.debug("No backend packages to add for '%s'. All optional packages: %s",
self._env.backend, _BACKEND_SPECIFIC_CONDA)
return
combined_cuda = []
for pkg in to_add:
pkg, channel = _CONDA_MAPPING.get(pkg, (pkg, ""))
if pkg == "zlib-wapi" and self._env.os_version[0].lower() != "windows":
# TODO move this front and center
continue
if pkg in ("cudatoolkit", "cudnn"): # TODO Handle multiple cuda/cudnn requirements
idx = 0 if pkg == "cudatoolkit" else 1
pkg = f"{pkg}{list(_TENSORFLOW_REQUIREMENTS.values())[0][idx]}"
combined_cuda.append(pkg)
continue
self._conda_required_packages.append((pkg, channel))
logger.info("Adding conda required package '%s' for backend '%s')",
pkg, self._env.backend)
if combined_cuda:
self._conda_required_packages.append((combined_cuda, channel))
logger.info("Adding conda required package '%s' for backend '%s')",
combined_cuda, self._env.backend)
@classmethod
def _format_requirements(cls, packages: list[str]
) -> list[tuple[str, list[tuple[str, str]]]]:
""" Parse a list of requirements.txt formatted package strings to a list of pkgresource
formatted requirements """
return [(package.unsafe_name, package.specs)
for package in parse_requirements(packages)
if package.marker is None or package.marker.evaluate()]
@classmethod
def _validate_spec(cls,
required: list[tuple[str, str]],
existing: str) -> bool:
""" Validate whether the required specification for a package is met by the installed
version.
required: list[tuple[str, str]]
The required package version spec to check
existing: str
The version of the installed package
Returns
-------
bool
``True`` if the required specification is met by the existing specification
"""
ops = {"==": operator.eq, ">=": operator.ge, "<=": operator.le,
">": operator.gt, "<": operator.lt}
if not required:
return True
return all(ops[spec[0]]([int(s) for s in existing.split(".")],
[int(s) for s in spec[1].split(".")])
for spec in required)
def _get_installed_packages(self) -> dict[str, str]:
""" Get currently installed packages and add to :attr:`_installed_packages`
Returns
-------
dict[str, str]
The installed package name and version string
"""
installed_packages = {}
with Popen(f"\"{sys.executable}\" -m pip freeze --local", shell=True, stdout=PIPE) as chk:
installed = chk.communicate()[0].decode(self._env.encoding,
errors="ignore").splitlines()
for pkg in installed:
if "==" not in pkg:
continue
item = pkg.split("==")
installed_packages[item[0]] = item[1]
logger.debug(installed_packages)
return installed_packages
def _get_installed_conda_packages(self) -> dict[str, str]:
""" Get currently installed conda packages
Returns
-------
dict[str, str]
The installed package name and version string
"""
if not self._env.is_conda:
return {}
chk = os.popen("conda list").read()
installed = [re.sub(" +", " ", line.strip())
for line in chk.splitlines() if not line.startswith("#")]
retval = {}
for pkg in installed:
item = pkg.split(" ")
retval[item[0]] = item[1]
logger.debug(retval)
return retval
def get_required_packages(self) -> None:
""" Load the requirements from the backend specific requirements list """
req_files = ["_requirements_base.txt", f"requirements_{self._env.backend}.txt"]
pypath = os.path.dirname(os.path.realpath(__file__))
requirements = []
for req_file in req_files:
requirements_file = os.path.join(pypath, "requirements", req_file)
with open(requirements_file, encoding="utf8") as req:
for package in req.readlines():
package = package.strip()
if package and (not package.startswith(("#", "-r"))):
requirements.append(package)
self._required_packages = self._format_requirements(requirements)
logger.debug(self._required_packages)
def _update_tf_dep_nvidia(self) -> None:
""" Update the Tensorflow dependency for global Cuda installs """
if self._env.is_conda: # Conda handles Cuda and cuDNN so nothing to do here
return
tf_ver = None
cuda_inst = self._env.cuda_version
cudnn_inst = self._env.cudnn_version
if len(cudnn_inst) == 1: # Sometimes only major version is reported
cudnn_inst = f"{cudnn_inst}.0"
for key, val in _TENSORFLOW_REQUIREMENTS.items():
cuda_req = next(parse_requirements(f"cuda{val[0]}")).specs
cudnn_req = next(parse_requirements(f"cudnn{val[1]}")).specs
if (self._validate_spec(cuda_req, cuda_inst)
and self._validate_spec(cudnn_req, cudnn_inst)):
tf_ver = key
break
if tf_ver:
# Remove the version of tensorflow in requirements file and add the correct version
# that corresponds to the installed Cuda/cuDNN versions
self._required_packages = [pkg for pkg in self._required_packages
if pkg[0] != "tensorflow"]
tf_ver = f"tensorflow{tf_ver}"
self._required_packages.append(("tensorflow", next(parse_requirements(tf_ver)).specs))
return
logger.warning(
"The minimum Tensorflow requirement is 2.10 \n"
"Tensorflow currently has no official prebuild for your CUDA, cuDNN combination.\n"
"Either install a combination that Tensorflow supports or build and install your own "
"tensorflow.\r\n"
"CUDA Version: %s\r\n"
"cuDNN Version: %s\r\n"
"Help:\n"
"Building Tensorflow: https://www.tensorflow.org/install/install_sources\r\n"
"Tensorflow supported versions: "
"https://www.tensorflow.org/install/source#tested_build_configurations",
self._env.cuda_version, self._env.cudnn_version)
custom_tf = input("Location of custom tensorflow wheel (leave blank to manually "
"install): ")
if not custom_tf:
return
custom_tf = os.path.realpath(os.path.expanduser(custom_tf))
global _INSTALL_FAILED # pylint:disable=global-statement
if not os.path.isfile(custom_tf):
logger.error("%s not found", custom_tf)
_INSTALL_FAILED = True
elif os.path.splitext(custom_tf)[1] != ".whl":
logger.error("%s is not a valid pip wheel", custom_tf)
_INSTALL_FAILED = True
elif custom_tf:
self._required_packages.append((custom_tf, [(custom_tf, "")]))
def _update_tf_dep_rocm(self) -> None:
""" Update the Tensorflow dependency for global ROCm installs """
if not any(self._env.rocm_version): # ROCm was not found and the install will be aborted
return
global _INSTALL_FAILED # pylint:disable=global-statement
candidates = [key for key, val in _TENSORFLOW_ROCM_REQUIREMENTS.items()
if val[0] <= self._env.rocm_version <= val[1]]
if not candidates:
_INSTALL_FAILED = True
logger.error("No matching Tensorflow candidates found for ROCm %s in %s",
".".join(str(v) for v in self._env.rocm_version),
_TENSORFLOW_ROCM_REQUIREMENTS)
return
# set tf_ver to the minimum and maximum compatible range
tf_ver = f"{candidates[0].split(',')[0]},{candidates[-1].split(',')[-1]}"
# Remove the version of tensorflow-rocm in requirements file and add the correct version
# that corresponds to the installed ROCm version
self._required_packages = [pkg for pkg in self._required_packages
if not pkg[0].startswith("tensorflow-rocm")]
tf_ver = f"tensorflow-rocm{tf_ver}"
self._required_packages.append(("tensorflow-rocm",
next(parse_requirements(tf_ver)).specs))
def update_tf_dep(self) -> None:
""" Update Tensorflow Dependency.
Selects a compatible version of Tensorflow for a globally installed GPU library
"""
if self._env.backend == "nvidia":
self._update_tf_dep_nvidia()
if self._env.backend == "rocm":
self._update_tf_dep_rocm()
def _check_conda_missing_dependencies(self) -> None:
""" Check for conda missing dependencies and add to :attr:`_conda_missing_packages` """
if not self._env.is_conda:
return
for pkg in self._conda_required_packages:
reqs = next(parse_requirements(pkg[0])) # TODO Handle '=' vs '==' for conda
key = reqs.unsafe_name
specs = reqs.specs
if pkg[0] == "tk" and self._env.os_version[0].lower() == "linux":
# Default tk has bad fonts under Linux. We pull in an explicit build from
# Conda-Forge that is compiled with better fonts.
# Ref: https://github.com/ContinuumIO/anaconda-issues/issues/6833
newpkg = (f"{pkg[0]}=*=xft_*", pkg[1]) # Swap out package for explicit XFT version
self._conda_missing_packages.append(newpkg)
# We also need to bring in xorg-libxft incase libXft does not exist on host system
self._conda_missing_packages.append(_CONDA_MAPPING["xorg-libxft"])
continue
if key not in self._conda_installed_packages:
self._conda_missing_packages.append(pkg)
continue
if not self._validate_spec(specs, self._conda_installed_packages[key]):
self._conda_missing_packages.append(pkg)
logger.debug(self._conda_missing_packages)
def check_missing_dependencies(self) -> None:
""" Check for missing dependencies and add to :attr:`_missing_packages` """
for key, specs in self._required_packages:
if self._env.is_conda: # Get Conda alias for Key
key = _CONDA_MAPPING.get(key, (key, None))[0]
if key not in self._all_installed_packages:
# Add not installed packages to missing packages list
self._missing_packages.append((key, specs))
continue
if not self._validate_spec(specs, self._all_installed_packages.get(key, "")):
self._missing_packages.append((key, specs))
logger.debug(self._missing_packages)
self._check_conda_missing_dependencies()
class Checks(): # pylint:disable=too-few-public-methods
""" Pre-installation checks
Parameters
----------
environment: :class:`Environment`
Environment class holding information about the running system
"""
def __init__(self, environment: Environment) -> None:
self._env: Environment = environment
self._tips: Tips = Tips()
# Checks not required for installer
if self._env.is_installer:
return
# Checks not required for Apple Silicon
if self._env.backend == "apple_silicon":
return
self._user_input()
self._check_cuda()
self._check_rocm()
if self._env.os_version[0] == "Windows":
self._tips.pip()
def _rocm_ask_enable(self) -> None:
""" Set backend to 'rocm' if OS is Linux and ROCm support required """
if self._env.os_version[0] != "Linux":
return
logger.info("ROCm support:\r\nIf you are using an AMD GPU, then select 'yes'."
"\r\nCPU/non-AMD GPU users should answer 'no'.\r\n")
i = input("Enable ROCm Support? [y/N] ")
if i in ("Y", "y"):
logger.info("ROCm Support Enabled")
self._env.backend = "rocm"
def _directml_ask_enable(self) -> None:
""" Set backend to 'directml' if OS is Windows and DirectML support required """
if self._env.os_version[0] != "Windows":
return
logger.info("DirectML support:\r\nIf you are using an AMD or Intel GPU, then select 'yes'."
"\r\nNvidia users should answer 'no'.")
i = input("Enable DirectML Support? [y/N] ")
if i in ("Y", "y"):
logger.info("DirectML Support Enabled")
self._env.backend = "directml"
def _user_input(self) -> None:
""" Get user input for AMD/DirectML/ROCm/Cuda/Docker """
self._directml_ask_enable()
self._rocm_ask_enable()
if not self._env.backend:
self._docker_ask_enable()
self._cuda_ask_enable()
if self._env.os_version[0] != "Linux" and (self._env.enable_docker
and self._env.backend == "nvidia"):
self._docker_confirm()
if self._env.enable_docker:
self._docker_tips()
self._env.set_config()
sys.exit(0)
def _docker_ask_enable(self) -> None:
""" Enable or disable Docker """
i = input("Enable Docker? [y/N] ")
if i in ("Y", "y"):
logger.info("Docker Enabled")
self._env.enable_docker = True
else:
logger.info("Docker Disabled")
self._env.enable_docker = False
def _docker_confirm(self) -> None:
""" Warn if nvidia-docker on non-Linux system """
logger.warning("Nvidia-Docker is only supported on Linux.\r\n"
"Only CPU is supported in Docker for your system")
self._docker_ask_enable()
if self._env.enable_docker:
logger.warning("CUDA Disabled")
self._env.backend = "cpu"
def _docker_tips(self) -> None:
""" Provide tips for Docker use """
if self._env.backend != "nvidia":
self._tips.docker_no_cuda()
else:
self._tips.docker_cuda()
def _cuda_ask_enable(self) -> None:
""" Enable or disable CUDA """
i = input("Enable CUDA? [Y/n] ")
if i in ("", "Y", "y"):
logger.info("CUDA Enabled")
self._env.backend = "nvidia"
def _check_cuda(self) -> None:
""" Check for Cuda and cuDNN Locations. """
if self._env.backend != "nvidia":
logger.debug("Skipping Cuda checks as not enabled")
return
if self._env.is_conda:
logger.info("Skipping Cuda/cuDNN checks for Conda install")
return
if self._env.os_version[0] in ("Linux", "Windows"):
global _INSTALL_FAILED # pylint:disable=global-statement
check = CudaCheck()
if check.cuda_version:
self._env.cuda_cudnn[0] = check.cuda_version
logger.info("CUDA version: %s", self._env.cuda_version)
else:
logger.error("CUDA not found. Install and try again.\n"
"Recommended version: CUDA 10.1 cuDNN 7.6\n"
"CUDA: https://developer.nvidia.com/cuda-downloads\n"
"cuDNN: https://developer.nvidia.com/rdp/cudnn-download")
_INSTALL_FAILED = True
return
if check.cudnn_version:
self._env.cuda_cudnn[1] = ".".join(check.cudnn_version.split(".")[:2])
logger.info("cuDNN version: %s", self._env.cudnn_version)
else:
logger.error("cuDNN not found. See "
"https://github.com/deepfakes/faceswap/blob/master/INSTALL.md#"
"cudnn for instructions")
_INSTALL_FAILED = True
return
# If we get here we're on MacOS
self._tips.macos()
logger.warning("Cannot find CUDA on macOS")
self._env.cuda_cudnn[0] = input("Manually specify CUDA version: ")
def _check_rocm(self) -> None:
""" Check for ROCm version """
if self._env.backend != "rocm" or self._env.os_version[0] != "Linux":
logger.info("Skipping ROCm checks as not enabled")
return
global _INSTALL_FAILED # pylint:disable=global-statement
check = ROCmCheck()
str_min = ".".join(str(v) for v in check.version_min)
str_max = ".".join(str(v) for v in check.version_max)
if check.is_valid:
self._env.rocm_version = check.rocm_version
logger.info("ROCm version: %s", ".".join(str(v) for v in self._env.rocm_version))
else:
if check.rocm_version:
msg = f"Incompatible ROCm version: {'.'.join(str(v) for v in check.rocm_version)}"
else:
msg = "ROCm not found"
logger.error("%s.\n"
"A compatible version of ROCm must be installed to proceed.\n"
"ROCm versions between %s and %s are supported.\n"
"ROCm install guide: https://docs.amd.com/bundle/ROCm_Installation_Guide"
"v5.0/page/Overview_of_ROCm_Installation_Methods.html",
msg,
str_min,
str_max)
_INSTALL_FAILED = True
def _check_ld_config(lib: str) -> str:
""" Locate a library in ldconfig
Parameters
----------
lib: str The library to locate
Returns
-------
str
The library from ldconfig, or empty string if not found
"""
retval = ""
ldconfig = which("ldconfig")
if not ldconfig:
return retval
retval = next((line.decode("utf-8", errors="replace").strip()
for line in run([ldconfig, "-p"],
capture_output=True,
check=False).stdout.splitlines()
if lib.encode("utf-8") in line), "")
if retval or (not retval and not os.environ.get("LD_LIBRARY_PATH")):
return retval
for path in os.environ["LD_LIBRARY_PATH"].split(":"):
if not path or not os.path.exists(path):
continue
retval = next((fname.strip() for fname in reversed(os.listdir(path))
if lib in fname), "")
if retval:
break
return retval
class ROCmCheck(): # pylint:disable=too-few-public-methods
""" Find the location of system installed ROCm on Linux """
def __init__(self) -> None:
self.version_min = min(v[0] for v in _TENSORFLOW_ROCM_REQUIREMENTS.values())
self.version_max = max(v[1] for v in _TENSORFLOW_ROCM_REQUIREMENTS.values())
self.rocm_version: tuple[int, ...] = (0, 0, 0)
if platform.system() == "Linux":
self._rocm_check()
@property
def is_valid(self):
""" bool: `True` if ROCm has been detected and is between the minimum and maximum
compatible versions otherwise ``False`` """
return self.version_min <= self.rocm_version <= self.version_max
def _rocm_check(self) -> None:
""" Attempt to locate the installed ROCm version from the dynamic link loader. If not found
with ldconfig then attempt to find it in LD_LIBRARY_PATH. If found, set the
:attr:`rocm_version` to the discovered version
"""
chk = _check_ld_config("librocm-core.so.")
if not chk:
return
rocm_vers = chk.strip()
version = re.search(r"rocm\-(\d+\.\d+\.\d+)", rocm_vers)
if version is None:
return
try:
self.rocm_version = tuple(int(v) for v in version.groups()[0].split("."))
except ValueError:
return
class CudaCheck(): # pylint:disable=too-few-public-methods
""" Find the location of system installed Cuda and cuDNN on Windows and Linux. """
def __init__(self) -> None:
self.cuda_path: str | None = None
self.cuda_version: str | None = None
self.cudnn_version: str | None = None
self._os: str = platform.system().lower()
self._cuda_keys: list[str] = [key
for key in os.environ
if key.lower().startswith("cuda_path_v")]
self._cudnn_header_files: list[str] = ["cudnn_version.h", "cudnn.h"]
logger.debug("cuda keys: %s, cudnn header files: %s",
self._cuda_keys, self._cudnn_header_files)
if self._os in ("windows", "linux"):
self._cuda_check()
self._cudnn_check()
def _cuda_check(self) -> None:
""" Obtain the location and version of Cuda and populate :attr:`cuda_version` and
:attr:`cuda_path`
Initially just calls `nvcc -V` to get the installed version of Cuda currently in use.
If this fails, drills down to more OS specific checking methods.
"""
with Popen("nvcc -V", shell=True, stdout=PIPE, stderr=PIPE) as chk:
stdout, stderr = chk.communicate()
if not stderr:
version = re.search(r".*release (?P<cuda>\d+\.\d+)",
stdout.decode(locale.getpreferredencoding(), errors="ignore"))
if version is not None:
self.cuda_version = version.groupdict().get("cuda", None)
path = which("nvcc")
if path:
path = path.split("\n")[0] # Split multiple entries and take first found
while True: # Get Cuda root folder
path, split = os.path.split(path)
if split == "bin":
break
self.cuda_path = path
return
# Failed to load nvcc, manual check
getattr(self, f"_cuda_check_{self._os}")()
logger.debug("Cuda Version: %s, Cuda Path: %s", self.cuda_version, self.cuda_path)
def _cuda_check_linux(self) -> None:
""" For Linux check the dynamic link loader for libcudart. If not found with ldconfig then
attempt to find it in LD_LIBRARY_PATH. """
chk = _check_ld_config("libcudart.so.")
if not chk: # Cuda not found
return
cudavers = chk.strip().replace("libcudart.so.", "")
self.cuda_version = cudavers[:cudavers.find(" ")] if " " in cudavers else cudavers
cuda_path = chk[chk.find("=>") + 3:chk.find("targets") - 1]
if os.path.exists(cuda_path):
self.cuda_path = cuda_path
def _cuda_check_windows(self) -> None:
""" Check Windows CUDA Version and path from Environment Variables"""
if not self._cuda_keys: # Cuda environment variable not found
return
self.cuda_version = self._cuda_keys[0].lower().replace("cuda_path_v", "").replace("_", ".")
self.cuda_path = os.environ[self._cuda_keys[0][0]]
def _cudnn_check_files(self) -> bool:
""" Check header files for cuDNN version """
cudnn_checkfiles = getattr(self, f"_get_checkfiles_{self._os}")()
cudnn_checkfile = next((hdr for hdr in cudnn_checkfiles if os.path.isfile(hdr)), None)
logger.debug("cudnn checkfiles: %s", cudnn_checkfile)
if not cudnn_checkfile:
return False
found = 0
with open(cudnn_checkfile, "r", encoding="utf8") as ofile:
for line in ofile:
if line.lower().startswith("#define cudnn_major"):
major = line[line.rfind(" ") + 1:].strip()
found += 1
elif line.lower().startswith("#define cudnn_minor"):
minor = line[line.rfind(" ") + 1:].strip()
found += 1
elif line.lower().startswith("#define cudnn_patchlevel"):
patchlevel = line[line.rfind(" ") + 1:].strip()
found += 1
if found == 3:
break
if found != 3: # Full version not determined
return False
self.cudnn_version = ".".join([str(major), str(minor), str(patchlevel)])
logger.debug("cudnn version: %s", self.cudnn_version)
return True
def _cudnn_check(self) -> None:
""" Check Linux or Windows cuDNN Version from cudnn.h and add to :attr:`cudnn_version`. """
if self._cudnn_check_files():
return
if self._os == "windows":
return
chk = _check_ld_config("libcudnn.so.")
if not chk:
return
cudnnvers = chk.strip().replace("libcudnn.so.", "").split()[0]
if not cudnnvers:
return
self.cudnn_version = cudnnvers
logger.debug("cudnn version: %s", self.cudnn_version)
def _get_checkfiles_linux(self) -> list[str]:
""" Return the the files to check for cuDNN locations for Linux by querying
the dynamic link loader.
Returns
-------
list
List of header file locations to scan for cuDNN versions
"""
chk = _check_ld_config("libcudnn.so.")
chk = chk.strip().replace("libcudnn.so.", "")
if not chk:
return []
cudnn_vers = chk[0]
header_files = [f"cudnn_v{cudnn_vers}.h"] + self._cudnn_header_files
cudnn_path = os.path.realpath(chk[chk.find("=>") + 3:chk.find("libcudnn") - 1])
cudnn_path = cudnn_path.replace("lib", "include")
cudnn_checkfiles = [os.path.join(cudnn_path, header) for header in header_files]
return cudnn_checkfiles
def _get_checkfiles_windows(self) -> list[str]:
""" Return the check-file locations for Windows. Just looks inside the include folder of
the discovered :attr:`cuda_path`
Returns
-------
list
List of header file locations to scan for cuDNN versions
"""
# TODO A more reliable way of getting the windows location
if not self.cuda_path or not os.path.exists(self.cuda_path):
return []
scandir = os.path.join(self.cuda_path, "include")
cudnn_checkfiles = [os.path.join(scandir, header) for header in self._cudnn_header_files]
return cudnn_checkfiles