kara-audio (GPL-3)

kara-audio.py

import argparse
import hashlib
import os
import platform
import signal
import site
import subprocess
import sys
from pathlib import Path


# Define the required PyTorch version
TORCH_VERSION = "2.2.1"
TORCHVISION_VERSION = "0.17.1"
TORCHAUDIO_VERSION = "2.2.1"


# Environment
script_dir = os.getcwd()
conda_env_path = os.path.join(script_dir, "installer_files", "env")
app_model_path = os.path.join(script_dir, "model")

    

def signal_handler(sig, frame):
    sys.exit(0)


signal.signal(signal.SIGINT, signal_handler)


def is_linux():
    return sys.platform.startswith("linux")


def is_windows():
    return sys.platform.startswith("win")


def is_macos():
    return sys.platform.startswith("darwin")


def is_x86_64():
    return platform.machine() == "x86_64"


def cpu_has_avx2():
    try:
        import cpuinfo

        info = cpuinfo.get_cpu_info()
        if 'avx2' in info['flags']:
            return True
        else:
            return False
    except:
        return True


def cpu_has_amx():
    try:
        import cpuinfo

        info = cpuinfo.get_cpu_info()
        if 'amx' in info['flags']:
            return True
        else:
            return False
    except:
        return True


def torch_version():
    site_packages_path = None
    for sitedir in site.getsitepackages():
        if "site-packages" in sitedir and conda_env_path in sitedir:
            site_packages_path = sitedir
            break

    if site_packages_path:
        torch_version_file = open(os.path.join(site_packages_path, 'torch', 'version.py')).read().splitlines()
        torver = [line for line in torch_version_file if line.startswith('__version__')][0].split('__version__ = ')[1].strip("'")
    else:
        from torch import __version__ as torver

    return torver    

def update_pytorch():
    print_big_message("Checking for PyTorch updates")

    torver = torch_version()
    is_cuda = '+cu' in torver
    is_cuda118 = '+cu118' in torver  # 2.1.0+cu118
    is_rocm = '+rocm' in torver  # 2.0.1+rocm5.4.2
    is_intel = '+cxx11' in torver  # 2.0.1a0+cxx11.abi
    is_cpu = '+cpu' in torver  # 2.0.1+cpu

    install_pytorch = f"python -m pip install --upgrade torch=={TORCH_VERSION} torchvision=={TORCHVISION_VERSION} torchaudio=={TORCHAUDIO_VERSION} "

    if is_cuda118:
        install_pytorch += "--index-url https://download.pytorch.org/whl/cu118"
    elif is_cuda:
        install_pytorch += "--index-url https://download.pytorch.org/whl/cu121"
    elif is_cpu:
        install_pytorch += "--index-url https://download.pytorch.org/whl/cpu"
    elif is_intel:
        if is_linux():
            install_pytorch = "python -m pip install --upgrade torch==2.1.0a0 torchvision==0.16.0a0 torchaudio==2.1.0a0 intel-extension-for-pytorch==2.1.10+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/"
        else:
            install_pytorch = "python -m pip install --upgrade torch==2.1.0a0 torchvision==0.16.0a0 torchaudio==2.1.0a0 intel-extension-for-pytorch==2.1.10 --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/"

    run_cmd(f"{install_pytorch}", assert_success=True, environment=True)


# ABUS   
# conda search -c conda-forge cudnn
def update_cudnn():
    print_big_message("Checking for cuDNN updates")
       
    torver = torch_version()
    is_cuda = '+cu' in torver
    is_cuda118 = '+cu118' in torver  # 2.1.0+cu118
    is_rocm = '+rocm' in torver  # 2.0.1+rocm5.4.2
    is_intel = '+cxx11' in torver  # 2.0.1a0+cxx11.abi
    is_cpu = '+cpu' in torver  # 2.0.1+cpu
    
    
    # onnxruntime
    run_cmd(f"python -m pip uninstall --yes onnxruntime", environment=True)
    run_cmd(f"python -m pip uninstall --yes onnxruntime-gpu", environment=True)    
    if is_cuda:
        run_cmd(f"python -m pip install nvidia-cudnn-cu12", assert_success=True, environment=True)
        run_cmd(f"python -m pip install --upgrade onnxruntime-gpu", environment=True)
        set_cudnn_env()
    elif is_cuda118:
        run_cmd(f"python -m pip install nvidia-cudnn-cu11", assert_success=True, environment=True)
        run_cmd(f"python -m pip install --upgrade onnxruntime-gpu", environment=True)        
        set_cudnn_env()
    else:
        run_cmd(f"python -m pip install --upgrade onnxruntime", environment=True)
        
    # nomkl
    run_cmd(f'conda install --yes nomkl --channel conda-forge', environment=True)
    

def set_cudnn_env():
    import os
    import nvidia.cudnn.lib
    # import nvidia.cublas.lib

    cudnn_path = os.path.dirname(nvidia.cudnn.lib.__file__) 
    # cublas_path = os.path.dirname(nvidia.cublas.lib.__file__)
    # cmd = f"conda env config vars set LD_LIBRARY_PATH='{cublas_path}':'{cudnn_path}'"
    
    cmd = f"conda env config vars set LD_LIBRARY_PATH='{cudnn_path}'"    
    run_cmd(cmd, environment=True)
    
             
    
def is_installed():
    site_packages_path = None
    for sitedir in site.getsitepackages():
        if "site-packages" in sitedir and conda_env_path in sitedir:
            site_packages_path = sitedir
            break

    if site_packages_path:
        return os.path.isfile(os.path.join(site_packages_path, 'torch', '__init__.py'))
    else:
        return os.path.isdir(conda_env_path)


def check_env():
    # If we have access to conda, we are probably in an environment
    conda_exist = run_cmd("conda", environment=True, capture_output=True).returncode == 0
    if not conda_exist:
        print("Conda is not installed. Exiting...")
        sys.exit(1)

    # Ensure this is a new environment and not the base environment
    if os.environ["CONDA_DEFAULT_ENV"] == "base":
        print("Create an environment for this project and activate it. Exiting...")
        sys.exit(1)


def clear_cache():
    print("clear_cache?? no...")
    # run_cmd("conda clean -a -y", environment=True)
    # run_cmd("python -m pip cache purge", environment=True)


def print_big_message(message):
    message = message.strip()
    lines = message.split('\n')
    print("\n\n*******************************************************************")
    for line in lines:
        print("*", line)

    print("*******************************************************************\n\n")


def calculate_file_hash(file_path):
    p = os.path.join(script_dir, file_path)
    if os.path.isfile(p):
        with open(p, 'rb') as f:
            return hashlib.sha256(f.read()).hexdigest()
    else:
        return ''    
    
    
def run_cmd(cmd, assert_success=False, environment=False, capture_output=False, env=None):
    # Use the conda environment
    if environment:
        if is_windows():
            conda_bat_path = os.path.join(script_dir, "installer_files", "conda", "condabin", "conda.bat")
            cmd = f'"{conda_bat_path}" activate "{conda_env_path}" >nul && {cmd}'
        else:
            conda_sh_path = os.path.join(script_dir, "installer_files", "conda", "etc", "profile.d", "conda.sh")
            cmd = f'. "{conda_sh_path}" && conda activate "{conda_env_path}" && {cmd}'

    # Run shell commands
    result = subprocess.run(cmd, shell=True, capture_output=capture_output, env=env)

    # Assert the command ran successfully
    if assert_success and result.returncode != 0:
        print(f"Command '{cmd}' failed with exit status code '{str(result.returncode)}'.\n\nExiting now.\nTry running the start/update script again.")
        sys.exit(1)

    return result    


def generate_alphabetic_sequence(index):
    result = ''
    while index >= 0:
        index, remainder = divmod(index, 26)
        result = chr(ord('A') + remainder) + result
        index -= 1

    return result


def get_user_choice(question, options_dict):
    print()
    print(question)
    print()

    for key, value in options_dict.items():
        print(f"{key}) {value}")

    print()

    choice = input("Input> ").upper()
    while choice not in options_dict.keys():
        print("Invalid choice. Please try again.")
        choice = input("Input> ").upper()

    return choice



def install_webui():

    # Ask the user for the GPU vendor
    if "GPU_CHOICE" in os.environ:
        choice = os.environ["GPU_CHOICE"].upper()
        print_big_message(f"Selected GPU choice \"{choice}\" based on the GPU_CHOICE environment variable.")
    else:
        choice = get_user_choice(
            "What is your GPU?",
            {
                'A': 'NVIDIA GTX, RTX, Tesla',
                'B': 'Intel Arc (IPEX)',
                'C': 'CPU (I want to run models in CPU mode)'
            },
        )

    gpu_choice_to_name = {
        "A": "NVIDIA",
        "B": "INTEL",
        "C": "CPU"
    }

    selected_gpu = gpu_choice_to_name[choice]
    
    
    # Find the Pytorch installation command
    install_pytorch = f"python -m pip install torch=={TORCH_VERSION} torchvision=={TORCHVISION_VERSION} torchaudio=={TORCHAUDIO_VERSION} "

    if selected_gpu == "NVIDIA":
        # if is_cuda118 == 'Y':
        #     print("PyTorch CUDA 11.8")
        #     install_pytorch += "--index-url https://download.pytorch.org/whl/cu118"
        # else:
        print("PyTorch CUDA 12.1")            
        install_pytorch += "--index-url https://download.pytorch.org/whl/cu121"
    elif selected_gpu == "INTEL":
        if is_linux():
            install_pytorch = "python -m pip install torch==2.1.0a0 torchvision==0.16.0a0 torchaudio==2.1.0a0 intel-extension-for-pytorch==2.1.10+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/"
        else:
            install_pytorch = "python -m pip install torch==2.1.0a0 torchvision==0.16.0a0 torchaudio==2.1.0a0 intel-extension-for-pytorch==2.1.10 --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/"

    # Install Git and then Pytorch
    print_big_message("Installing PyTorch.")
    run_cmd(f"conda install -y -k ninja git && {install_pytorch} && python -m pip install py-cpuinfo==9.0.0", assert_success=True, environment=True)

    if selected_gpu == "INTEL":
        # Install oneAPI dependencies via conda
        print_big_message("Installing Intel oneAPI runtime libraries.")
        run_cmd("conda install -y -c intel dpcpp-cpp-rt=2024.0 mkl-dpcpp=2024.0")
        # Install libuv required by Intel-patched torch
        run_cmd("conda install -y libuv")


    # Install the webui requirements
    update_requirements(initial_installation=True)

    # cudnn & onnxruntime
    update_cudnn()
    
    
    clear_cache()    

    
   
# ABUS    
def update_requirements(initial_installation=False, pull=True):

    # Update PyTorch
    if not initial_installation:
        update_pytorch()

    # Detect the PyTorch version
    torver = torch_version()
    is_cuda = '+cu' in torver
    is_cuda118 = '+cu118' in torver  # 2.1.0+cu118
    is_rocm = '+rocm' in torver  # 2.0.1+rocm5.4.2
    is_intel = '+cxx11' in torver  # 2.0.1a0+cxx11.abi
    is_cpu = '+cpu' in torver  # 2.0.1+cpu


    requirements_file = "requirements.txt"
    print_big_message(f"Installing webui requirements from file: {requirements_file}")
    print(f"TORCH: {torver}\n")

    # Prepare the requirements file
    textgen_requirements = open(requirements_file).read().splitlines()
    if is_cuda118:
        textgen_requirements = [req.replace('+cu121', '+cu118').replace('+cu122', '+cu118') for req in textgen_requirements]

    with open('temp_requirements.txt', 'w') as file:
        file.write('\n'.join(textgen_requirements))

    # Workaround for git+ packages not updating properly.
    git_requirements = [req for req in textgen_requirements if req.startswith("git+")]
    for req in git_requirements:
        url = req.replace("git+", "")
        package_name = url.split("/")[-1].split("@")[0].rstrip(".git")
        run_cmd(f"python -m pip uninstall -y {package_name}", environment=True)
        print(f"Uninstalled {package_name}")

    # Install/update the project requirements
    run_cmd("python -m pip install -r temp_requirements.txt --upgrade", assert_success=True, environment=True)
    os.remove('temp_requirements.txt')
    
    # cudnn
    # if is_cuda118:
    #     run_cmd("conda install -c conda-forge cudnn=8.4.1.50=hf5f08ae_0", assert_success=True, environment=True)
    #     run_cmd(f"python -m pip uninstall -y onnxruntime", environment=True)
    #     run_cmd(f"python -m pip install -y onnxruntime-gpu==1.17.1", environment=True)

    # Check for '+cu' or '+rocm' in version string to determine if torch uses CUDA or ROCm. Check for pytorch-cuda as well for backwards compatibility
    if not any((is_cuda, is_rocm)) and run_cmd("conda list -f pytorch-cuda | grep pytorch-cuda", environment=True, capture_output=True).returncode == 1:
        clear_cache()
        return

    # clear_cache()    

                
# ABUS - start web ui
def launch_webui():
    print("Start the program...")
    run_cmd(f"python app/abus_app_kara.py", environment=True)    



if __name__ == "__main__":
    # Verifies we are in a conda environment
    check_env()

    parser = argparse.ArgumentParser(add_help=False)
    parser.add_argument('--update-wizard', action='store_true', help='Launch a menu with update options.')
    args, _ = parser.parse_known_args()

    if not is_installed():
        install_webui()
        os.chdir(script_dir)

    if os.environ.get("LAUNCH_AFTER_INSTALL", "").lower() in ("no", "n", "false", "0", "f", "off"):
        print_big_message("Will now exit due to LAUNCH_AFTER_INSTALL.")
        sys.exit()


    # Workaround for llama-cpp-python loading paths in CUDA env vars even if they do not exist
    conda_path_bin = os.path.join(conda_env_path, "bin")
    if not os.path.exists(conda_path_bin):
        os.mkdir(conda_path_bin)    

    # Launch the webui
    launch_webui()