/
install_win.py
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install_win.py
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import subprocess
import platform
import sys
import re
import os
always_clear_pip = False
always_download_models = False
requirements_file_path = "requirements.txt"
log_file_path = "log_install_python.txt"
with open(log_file_path, 'w', encoding='utf-8') as log_file:
log_file.write("Starting installation script...\n")
def printl(message, log_file=log_file_path, noprint=False):
if not noprint:
print(message)
with open(log_file, "a", encoding='utf-8') as file:
file.write(message + "\n")
def check_python_version():
if sys.version_info[:3] != (3, 10, 9):
ask_exit(
"This script requires Python 3.10.9.\n"
"Your version: " + ".".join(map(str, sys.version_info[:3]))+ "\n",
"Do you want to proceed anyway? (yes/no): "
)
else:
printl("Python version 3.10.9 detected.")
return sys.version_info[:3]
def ask_exit(
main_text,
input_text="Do you want to try anyway? (yes/no): "
):
printl(main_text)
choice = input(input_text)
# Check user's decision
if choice.lower() not in ['yes', 'y']:
printl("Installation aborted.")
sys.exit()
def ask(
main_text,
input_text="Do you want to try anyway? (yes/no): "
):
printl(main_text)
choice = input(input_text)
return choice.lower() in ['yes', 'y']
def check_platform():
printl("Checking platform...")
# Check if the current platform is Windows
if platform.system() != "Windows":
# Display a warning message if not on Windows
ask_exit(
"Warning: This installation script is designed for Windows platforms.",
"Do you want to proceed despite being on a non-Windows platform? (yes/no): "
)
else:
printl(" Windows platform detected.")
def check_cuda():
printl("Checking CUDA Toolkit...")
try:
# Execute nvcc to get CUDA version
nvcc_output = subprocess.check_output("nvcc --version", shell=True).decode()
# Use regular expression to extract version number
match = re.search(r"release (\d+\.\d+)", nvcc_output)
if match:
cuda_version = match.group(1)
if cuda_version == "11.8":
printl(f" CUDA Toolkit version {cuda_version} detected.")
else:
ask_exit(
f"CUDA Toolkit version {cuda_version} detected.\n"
"- Version 11.8 is strongly recommended.\n"
" https://developer.nvidia.com/cuda-11-8-0-download-archive",
"Do you want to continue with a different version of CUDA? (yes/no): "
)
return cuda_version
else:
ask_exit(
"CUDA Toolkit version 11.8 could not be detected.\n"
"- Version 11.8 is strongly recommended.\n"
" https://developer.nvidia.com/cuda-11-8-0-download-archive",
"Do you want to proceed despite CUDA 11.8 was not detected? (yes/no): "
)
return "11.8"
except subprocess.CalledProcessError:
ask_exit(
"CUDA Toolkit version 11.8 could not be detected.\n"
"- Version 11.8 is strongly recommended.\n"
" https://developer.nvidia.com/cuda-11-8-0-download-archive",
"Do you want to proceed despite CUDA 11.8 was not detected? (yes/no): "
)
return "11.8"
def check_cudnn():
printl("Checking cuDNN...")
# Typical paths where cuDNN might be installed
cudnn_paths = [
r"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin",
r"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\include",
r"C:\tools\cuda\bin",
r"C:\tools\cuda\include"
]
cudnn_h_found = False
cudnn_dll_found = False
# Check if cuDNN files exist in the typical paths
for path in cudnn_paths:
if os.path.exists(os.path.join(path, "cudnn.h")):
cudnn_h_found = True
# Check for the existence of the cuDNN library file (dll)
# The file name can vary based on the cuDNN version
# Here we are checking for version 7 as an example
if any(os.path.exists(os.path.join(path, f)) for f in ["cudnn64_7.dll", "cudnn64_8.dll"]):
cudnn_dll_found = True
if cudnn_h_found and cudnn_dll_found:
printl(" cuDNN installation detected.")
else:
ask_exit(
"cuDNN installation not found.\n"
"- Version 8.7.0 for CUDA 11.8 is recommended.\n"
" https://developer.nvidia.com/rdp/cudnn-archive",
"Do you want to despite cuDNN installation was not detected? (yes/no): "
)
def check_ffmpeg():
printl("Checking FFmpeg...")
try:
# Execute ffmpeg to check its presence
subprocess.check_output("ffmpeg -version", shell=True)
printl(" FFmpeg installation detected.")
except subprocess.CalledProcessError:
ask_exit(
"FFmpeg not found. It is required for video processing.\n"
"Please install FFmpeg.",
"Do you want to continue without FFmpeg? (yes/no): "
)
def install_library(library):
try:
# Run pip install and capture the output and error
result = subprocess.run([sys.executable, "-m", "pip", "install", library], capture_output=True, text=True)
# Check if the installation was successful or if the package is already installed
if f"Requirement already satisfied: {library}" in result.stdout:
printl(f"Already installed {library}")
printl(f" {result.stdout}", noprint=True)
elif "Successfully installed" in result.stdout:
printl(f"Successfully installed {library}")
printl(f" {result.stdout}", noprint=True)
else:
printl(f" {result.stdout}", noprint=True)
ask_exit(
f"Failed to install {library}. Error: {result.stderr}",
f"Do you want to continue installation without verified installation of {library}? (yes/no): "
)
except subprocess.CalledProcessError as e:
ask_exit(
f"Installation failed for {library}. Error: {e}",
f"Do you want to continue installation without verified installation of {library}? (yes/no): "
)
def install_libraries_from_requirements(file_path):
try:
with open(file_path, 'r') as file:
libraries = file.readlines()
for library in libraries:
library = library.strip()
if library and not library.startswith('#'): # Skip empty lines and comments
install_library(library)
except FileNotFoundError:
printl(f"The file {file_path} was not found. Please ensure it's in the correct path.")
def purge_pip_cache():
try:
subprocess.check_call([sys.executable, "-m", "pip", "cache", "purge"])
printl("Pip cache cleared successfully.")
except subprocess.CalledProcessError as e:
printl(f"Failed to clear pip cache. Error: {e}")
def install_deepspeed(deepspeed_version, cuda_version, python_version):
# Mapping of Deepspeed version, CUDA version, and Python version to wheel URL
wheel_urls = {
("0.11.2", "11.8", (3, 10)): "https://github.com/daswer123/deepspeed-windows/releases/download/11.2/deepspeed-0.11.2+cuda118-cp310-cp310-win_amd64.whl",
("0.11.2", "12.1", (3, 10)): "https://github.com/daswer123/deepspeed-windows/releases/download/11.2/deepspeed-0.11.2+cuda121-cp310-cp310-win_amd64.whl",
("0.11.2", "11.8", (3, 11)): "https://github.com/daswer123/deepspeed-windows/releases/download/11.2/deepspeed-0.11.2+cuda118-cp311-cp311-win_amd64.whl",
("0.11.2", "12.1", (3, 11)): "https://github.com/daswer123/deepspeed-windows/releases/download/11.2/deepspeed-0.11.2+cuda121-cp311-cp311-win_amd64.whl",
("0.12.6", "11.8", (3, 10)): "https://github.com/daswer123/deepspeed-windows/releases/download/12.6/deepspeed-0.12.6+cu118-cp310-cp310-win_amd64.whl",
("0.12.6", "12.1", (3, 10)): "https://github.com/daswer123/deepspeed-windows/releases/download/12.6/deepspeed-0.12.6+cu121-cp310-cp310-win_amd64.whl",
("0.12.6", "11.8", (3, 11)): "https://github.com/daswer123/deepspeed-windows/releases/download/12.6/deepspeed-0.12.6+cu118-cp311-cp311-win_amd64.whl",
("0.12.6", "12.1", (3, 11)): "https://github.com/daswer123/deepspeed-windows/releases/download/12.6/deepspeed-0.12.6+cu121-cp311-cp311-win_amd64.whl",
("0.13.1", "11.8", (3, 10)): "https://github.com/daswer123/deepspeed-windows/releases/download/13.1/deepspeed-0.13.1+cu118-cp310-cp310-win_amd64.whl",
("0.13.1", "12.1", (3, 10)): "https://github.com/daswer123/deepspeed-windows/releases/download/13.1/deepspeed-0.13.1+cu121-cp310-cp310-win_amd64.whl",
("0.13.1", "11.8", (3, 11)): "https://github.com/daswer123/deepspeed-windows/releases/download/13.1/deepspeed-0.13.1+cu118-cp311-cp311-win_amd64.whl",
("0.13.1", "12.1", (3, 11)): "https://github.com/daswer123/deepspeed-windows/releases/download/13.1/deepspeed-0.13.1+cu121-cp311-cp311-win_amd64.whl"
}
# Constructing the key for the mapping
key = (deepspeed_version, cuda_version, (python_version[0], python_version[1]))
# Get the wheel URL from the mapping
wheel_url = wheel_urls.get(key)
if wheel_url:
# Install the wheel using pip
install_library(wheel_url)
else:
printl(f"No matching wheel found for Deepspeed version {deepspeed_version}, CUDA version {cuda_version}, Python version {python_version[0]}.{python_version[1]}")
printl("Trying to install deepspeed with pip ...")
install_library("deepspeed")
def install_llama_cpp_python(cuda_version):
printl("Installing llama-cpp-python...")
try:
# Set environment variables if necessary
os.environ['CMAKE_ARGS'] = '-DLLAMA_CUBLAS=on'
os.environ['FORCE_CMAKE'] = '1'
# Perform installation with pip
subprocess.check_call([sys.executable, "-m", "pip", "install", "llama-cpp-python", "--force-reinstall", "--upgrade", "--no-cache-dir", "--verbose"])
printl("Successfully installed llama-cpp-python.")
except subprocess.CalledProcessError as e:
printl(f"Failed to install llama-cpp-python. Error: {e}")
printl(f"You may need to copy MSBuildExtensions files for CUDA {cuda_version}.")
printl(f"Copy all four MSBuildExtensions files from:\n"
f"C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v{cuda_version}\\extras\\visual_studio_integration\\MSBuildExtensions\n"
f"to\n"
f"C:\\Program Files (x86)\\Microsoft Visual Studio\\2022\\BuildTools\\MSBuild\\Microsoft\\VC\\v170\\BuildCustomizations\n"
f"before restarting the installation script or manually executing the following command:\n"
f"pip install llama-cpp-python --force-reinstall --upgrade --no-cache-dir --verbose")
ask_exit("Do you want to continue without a verified installation of llama-cpp-python? (yes/no): ")
def install_pytorch_torchaudio(cuda_version):
printl("Installing PyTorch and Torchaudio...")
torch_wheels = {
"11.8": "torch==2.1.2+cu118 torchaudio==2.1.2+cu118",
"12.1": "torch==2.1.2+cu121 torchaudio==2.1.2+cu121",
}
torch_wheel = torch_wheels.get(cuda_version)
if torch_wheel:
# Install the wheel using pip
packages = torch_wheel.split()
try:
subprocess.check_call([sys.executable, "-m", "pip", "install", *packages, "--index-url", "https://download.pytorch.org/whl/cu" + cuda_version.replace('.', '')])
# subprocess.check_call([sys.executable, "-m", "pip", "install", torch_wheel, "--index-url", "https://download.pytorch.org/whl/cu" + cuda_version.replace('.', '')])
printl(f"Successfully installed PyTorch and Torchaudio for CUDA {cuda_version}.")
except subprocess.CalledProcessError as e:
printl(f"Failed to install PyTorch and Torchaudio. Error: {e}")
ask_exit(
f"Failed to install PyTorch and Torchaudio. Error: {e}",
"Do you want to continue without a verified installation of PyTorch and Torchaudio? (yes/no): ")
else:
printl(f"No matching wheels found for CUDA version {cuda_version}.")
ask_exit(
f"No matching wheels found for CUDA version {cuda_version}.",
"Do you want to continue without a verified installation of PyTorch and Torchaudio? (yes/no): ")
def detect_vram():
import pynvml
pynvml.nvmlInit()
device_count = pynvml.nvmlDeviceGetCount()
vram_values = []
for i in range(device_count):
handle = pynvml.nvmlDeviceGetHandleByIndex(i)
info = pynvml.nvmlDeviceGetMemoryInfo(handle)
vram_mb = info.total / 1024**2
vram_values.append(vram_mb)
print(f"GPU: {i}, VRAM: {vram_mb}MB")
pynvml.nvmlShutdown()
if vram_values:
return max(vram_values)
else:
return 0
def download_models():
try:
subprocess.run(['python', 'download_models.py'])
except subprocess.CalledProcessError as e:
printl(f"Failed to download pre-trained models. Error: {e}")
ask_exit("Do you want to continue without downloading pre-trained models? (yes/no): ")
if __name__ == "__main__":
perform_download = always_download_models or \
ask("Do you want to download pre-trained llm (OpenHermes-2.5-Mistral-7B-GGUF), xtts and rvc models (recommended for tts rvc post processing)?",
"Please enter yes or no: ")
clear_pip = always_clear_pip or \
ask("Do you want to clear the pip cache? This can resolve some installation issues.", "Please enter yes or no: ")
printl("\nChecking system requirements ...")
python_version = check_python_version()
check_platform()
cuda_version = check_cuda()
check_cudnn()
check_ffmpeg()
printl("System requirements check passed.\n")
if clear_pip:
purge_pip_cache()
printl("\nInstalling required libraries ...")
install_libraries_from_requirements(requirements_file_path)
printl("\nInstalling torch with CUDA ...")
install_pytorch_torchaudio(cuda_version)
printl("\nInstalling required deepspeed ...")
install_deepspeed("0.11.2", cuda_version, python_version)
printl("\nInstalling required llama.cpp ...")
install_llama_cpp_python(cuda_version)
printl("\nSetting numpy version ...")
install_library("numpy==1.23.5")
if perform_download:
download_models()
# vram_mb = detect_vram()