CUDA Setup failed despite GPU being available. Please run the following command to get more information:
이 오류에 한정함.
맨 처음 실행하는 셀을 코드 표시를 눌러 나타난 코드를 아래 해놓은 코드로 교체하면 됨.
import osimport timefrom subprocess import getoutputfrom IPython.utils import capturefrom google.colab import drive
%store -r
# root_dirroot_dir = "/content"deps_dir = os.path.join(root_dir, "deps")repo_dir = os.path.join(root_dir, "kohya-trainer")training_dir = os.path.join(root_dir, "LoRA")pretrained_model = os.path.join(root_dir, "pretrained_model")vae_dir = os.path.join(root_dir, "vae")config_dir = os.path.join(training_dir, "config")
# repo_diraccelerate_config = os.path.join(repo_dir, "accelerate_config/config.yaml")tools_dir = os.path.join(repo_dir, "tools")finetune_dir = os.path.join(repo_dir, "finetune")
for store in [ "root_dir", "deps_dir", "repo_dir", "training_dir", "pretrained_model", "vae_dir", "accelerate_config", "tools_dir", "finetune_dir", "config_dir",]: with capture.capture_output() as cap: %store {store} del cap
repo_url = "https://github.com/Linaqruf/kohya-trainer"bitsandytes_main_py = "/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py"branch = "" # @param {type: "string"}install_xformers = True # @param {'type':'boolean'}mount_drive = True # @param {type: "boolean"}verbose = False # @param {type: "boolean"}
def read_file(filename): with open(filename, "r") as f: contents = f.read() return contents
def write_file(filename, contents): with open(filename, "w") as f: f.write(contents)
def clone_repo(url): if not os.path.exists(repo_dir): os.chdir(root_dir) !git clone {url} {repo_dir} else: os.chdir(repo_dir) !git pull origin {branch} if branch else !git pull
def install_dependencies(): s = getoutput('nvidia-smi')
if 'T4' in s: !sed -i "s@cpu@cuda@" library/model_util.py
!pip install {'-q' if not verbose else ''} --upgrade -r requirements.txt !pip install {'-q' if not verbose else ''} torch==2.0.0+cu122 torchvision==0.15.1+cu122 torchaudio==2.0.1+cu122 torchtext==0.15.1 torchdata==0.6.0 --extra-index-url https://download.pytorch.org/whl/cu122 -U
if install_xformers: !pip install {'-q' if not verbose else ''} xformers==0.0.19 triton==2.0.0 -U
from accelerate.utils import write_basic_config
if not os.path.exists(accelerate_config): write_basic_config(save_location=accelerate_config)
def remove_bitsandbytes_message(filename): welcome_message = """def evaluate_cuda_setup(): print('') print('='*35 + 'BUG REPORT' + '='*35) print('Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues') print('For effortless bug reporting copy-paste your error into this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link') print('='*80)"""
new_welcome_message = """def evaluate_cuda_setup(): import os if 'BITSANDBYTES_NOWELCOME' not in os.environ or str(os.environ['BITSANDBYTES_NOWELCOME']) == '0': print('') print('=' * 35 + 'BUG REPORT' + '=' * 35) print('Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues') print('For effortless bug reporting copy-paste your error into this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link') print('To hide this message, set the BITSANDBYTES_NOWELCOME variable like so: export BITSANDBYTES_NOWELCOME=1') print('=' * 80)"""
contents = read_file(filename) new_contents = contents.replace(welcome_message, new_welcome_message) write_file(filename, new_contents)
def main(): os.chdir(root_dir)
if mount_drive: if not os.path.exists("/content/drive"): drive.mount("/content/drive")
for dir in [ deps_dir, training_dir, config_dir, pretrained_model, vae_dir ]: os.makedirs(dir, exist_ok=True)
clone_repo(repo_url)
if branch: os.chdir(repo_dir) status = os.system(f"git checkout {branch}") if status != 0: raise Exception("Failed to checkout branch or commit")
os.chdir(repo_dir)
!apt install aria2 {'-qq' if not verbose else ''}
install_dependencies() time.sleep(3)
remove_bitsandbytes_message(bitsandytes_main_py)
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" os.environ["BITSANDBYTES_NOWELCOME"] = "1" os.environ["SAFETENSORS_FAST_GPU"] = "1"
cuda_path = "/usr/local/cuda-12.2/targets/x86_64-linux/lib/" ld_library_path = os.environ.get("LD_LIBRARY_PATH", "") os.environ["LD_LIBRARY_PATH"] = f"{ld_library_path}:{cuda_path}"
main()
%store -r
# root_dirroot_dir = "/content"deps_dir = os.path.join(root_dir, "deps")repo_dir = os.path.join(root_dir, "kohya-trainer")training_dir = os.path.join(root_dir, "LoRA")pretrained_model = os.path.join(root_dir, "pretrained_model")vae_dir = os.path.join(root_dir, "vae")config_dir = os.path.join(training_dir, "config")
# repo_diraccelerate_config = os.path.join(repo_dir, "accelerate_config/config.yaml")tools_dir = os.path.join(repo_dir, "tools")finetune_dir = os.path.join(repo_dir, "finetune")
for store in [ "root_dir", "deps_dir", "repo_dir", "training_dir", "pretrained_model", "vae_dir", "accelerate_config", "tools_dir", "finetune_dir", "config_dir",]: with capture.capture_output() as cap: %store {store} del cap
repo_url = "https://github.com/Linaqruf/kohya-trainer"bitsandytes_main_py = "/usr/local/lib/python3.10/dist-packages/bitsandbytes/cuda_setup/main.py"branch = "" # @param {type: "string"}install_xformers = True # @param {'type':'boolean'}mount_drive = True # @param {type: "boolean"}verbose = False # @param {type: "boolean"}
def read_file(filename): with open(filename, "r") as f: contents = f.read() return contents
def write_file(filename, contents): with open(filename, "w") as f: f.write(contents)
def clone_repo(url): if not os.path.exists(repo_dir): os.chdir(root_dir) !git clone {url} {repo_dir} else: os.chdir(repo_dir) !git pull origin {branch} if branch else !git pull
def install_dependencies(): s = getoutput('nvidia-smi')
if 'T4' in s: !sed -i "s@cpu@cuda@" library/model_util.py
!pip install {'-q' if not verbose else ''} --upgrade -r requirements.txt !pip install {'-q' if not verbose else ''} torch==2.0.0+cu122 torchvision==0.15.1+cu122 torchaudio==2.0.1+cu122 torchtext==0.15.1 torchdata==0.6.0 --extra-index-url https://download.pytorch.org/whl/cu122 -U
if install_xformers: !pip install {'-q' if not verbose else ''} xformers==0.0.19 triton==2.0.0 -U
from accelerate.utils import write_basic_config
if not os.path.exists(accelerate_config): write_basic_config(save_location=accelerate_config)
def remove_bitsandbytes_message(filename): welcome_message = """def evaluate_cuda_setup(): print('') print('='*35 + 'BUG REPORT' + '='*35) print('Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues') print('For effortless bug reporting copy-paste your error into this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link') print('='*80)"""
new_welcome_message = """def evaluate_cuda_setup(): import os if 'BITSANDBYTES_NOWELCOME' not in os.environ or str(os.environ['BITSANDBYTES_NOWELCOME']) == '0': print('') print('=' * 35 + 'BUG REPORT' + '=' * 35) print('Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues') print('For effortless bug reporting copy-paste your error into this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link') print('To hide this message, set the BITSANDBYTES_NOWELCOME variable like so: export BITSANDBYTES_NOWELCOME=1') print('=' * 80)"""
contents = read_file(filename) new_contents = contents.replace(welcome_message, new_welcome_message) write_file(filename, new_contents)
def main(): os.chdir(root_dir)
if mount_drive: if not os.path.exists("/content/drive"): drive.mount("/content/drive")
for dir in [ deps_dir, training_dir, config_dir, pretrained_model, vae_dir ]: os.makedirs(dir, exist_ok=True)
clone_repo(repo_url)
if branch: os.chdir(repo_dir) status = os.system(f"git checkout {branch}") if status != 0: raise Exception("Failed to checkout branch or commit")
os.chdir(repo_dir)
!apt install aria2 {'-qq' if not verbose else ''}
install_dependencies() time.sleep(3)
remove_bitsandbytes_message(bitsandytes_main_py)
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" os.environ["BITSANDBYTES_NOWELCOME"] = "1" os.environ["SAFETENSORS_FAST_GPU"] = "1"
cuda_path = "/usr/local/cuda-12.2/targets/x86_64-linux/lib/" ld_library_path = os.environ.get("LD_LIBRARY_PATH", "") os.environ["LD_LIBRARY_PATH"] = f"{ld_library_path}:{cuda_path}"
main()
