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import ctypes as ct |
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import torch |
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from pathlib import Path |
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from warnings import warn |
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class CUDASetup(object): |
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_instance = None |
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def __init__(self): |
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raise RuntimeError("Call get_instance() instead") |
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def generate_instructions(self): |
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if self.cuda is None: |
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self.add_log_entry('CUDA SETUP: Problem: The main issue seems to be that the main CUDA library was not detected.') |
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self.add_log_entry('CUDA SETUP: Solution 1): Your paths are probably not up-to-date. You can update them via: sudo ldconfig.') |
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self.add_log_entry('CUDA SETUP: Solution 2): If you do not have sudo rights, you can do the following:') |
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self.add_log_entry('CUDA SETUP: Solution 2a): Find the cuda library via: find / -name libcuda.so 2>/dev/null') |
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self.add_log_entry('CUDA SETUP: Solution 2b): Once the library is found add it to the LD_LIBRARY_PATH: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:FOUND_PATH_FROM_2a') |
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self.add_log_entry('CUDA SETUP: Solution 2c): For a permanent solution add the export from 2b into your .bashrc file, located at ~/.bashrc') |
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return |
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if self.cudart_path is None: |
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self.add_log_entry('CUDA SETUP: Problem: The main issue seems to be that the main CUDA runtime library was not detected.') |
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self.add_log_entry('CUDA SETUP: Solution 1: To solve the issue the libcudart.so location needs to be added to the LD_LIBRARY_PATH variable') |
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self.add_log_entry('CUDA SETUP: Solution 1a): Find the cuda runtime library via: find / -name libcudart.so 2>/dev/null') |
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self.add_log_entry('CUDA SETUP: Solution 1b): Once the library is found add it to the LD_LIBRARY_PATH: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:FOUND_PATH_FROM_1a') |
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self.add_log_entry('CUDA SETUP: Solution 1c): For a permanent solution add the export from 1b into your .bashrc file, located at ~/.bashrc') |
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self.add_log_entry('CUDA SETUP: Solution 2: If no library was found in step 1a) you need to install CUDA.') |
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self.add_log_entry('CUDA SETUP: Solution 2a): Download CUDA install script: wget https://github.com/TimDettmers/bitsandbytes/blob/main/cuda_install.sh') |
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self.add_log_entry('CUDA SETUP: Solution 2b): Install desired CUDA version to desired location. The syntax is bash cuda_install.sh CUDA_VERSION PATH_TO_INSTALL_INTO.') |
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self.add_log_entry('CUDA SETUP: Solution 2b): For example, "bash cuda_install.sh 113 ~/local/" will download CUDA 11.3 and install into the folder ~/local') |
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return |
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make_cmd = f'CUDA_VERSION={self.cuda_version_string}' |
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if len(self.cuda_version_string) < 3: |
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make_cmd += ' make cuda92' |
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elif self.cuda_version_string == '110': |
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make_cmd += ' make cuda110' |
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elif self.cuda_version_string[:2] == '11' and int(self.cuda_version_string[2]) > 0: |
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make_cmd += ' make cuda11x' |
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has_cublaslt = self.cc in ["7.5", "8.0", "8.6"] |
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if not has_cublaslt: |
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make_cmd += '_nomatmul' |
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self.add_log_entry('CUDA SETUP: Something unexpected happened. Please compile from source:') |
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self.add_log_entry('git clone [email protected]:TimDettmers/bitsandbytes.git') |
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self.add_log_entry('cd bitsandbytes') |
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self.add_log_entry(make_cmd) |
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self.add_log_entry('python setup.py install') |
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def initialize(self): |
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self.cuda_setup_log = [] |
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self.lib = None |
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from .cuda_setup.main import evaluate_cuda_setup |
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binary_name, cudart_path, cuda, cc, cuda_version_string = evaluate_cuda_setup() |
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self.cudart_path = cudart_path |
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self.cuda = cuda |
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self.cc = cc |
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self.cuda_version_string = cuda_version_string |
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package_dir = Path(__file__).parent |
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binary_path = package_dir / binary_name |
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try: |
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if not binary_path.exists(): |
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self.add_log_entry(f"CUDA SETUP: Required library version not found: {binary_name}. Maybe you need to compile it from source?") |
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legacy_binary_name = "libbitsandbytes.so" |
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self.add_log_entry(f"CUDA SETUP: Defaulting to {legacy_binary_name}...") |
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binary_path = package_dir / legacy_binary_name |
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if not binary_path.exists(): |
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self.add_log_entry('') |
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self.add_log_entry('='*48 + 'ERROR' + '='*37) |
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self.add_log_entry('CUDA SETUP: CUDA detection failed! Possible reasons:') |
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self.add_log_entry('1. CUDA driver not installed') |
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self.add_log_entry('2. CUDA not installed') |
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self.add_log_entry('3. You have multiple conflicting CUDA libraries') |
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self.add_log_entry('4. Required library not pre-compiled for this bitsandbytes release!') |
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self.add_log_entry('CUDA SETUP: If you compiled from source, try again with `make CUDA_VERSION=DETECTED_CUDA_VERSION` for example, `make CUDA_VERSION=113`.') |
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self.add_log_entry('='*80) |
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self.add_log_entry('') |
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self.generate_instructions() |
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self.print_log_stack() |
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raise Exception('CUDA SETUP: Setup Failed!') |
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self.lib = ct.cdll.LoadLibrary(binary_path) |
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else: |
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self.add_log_entry(f"CUDA SETUP: Loading binary {binary_path}...") |
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self.lib = ct.cdll.LoadLibrary(binary_path) |
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except: |
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self.print_log_stack() |
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def add_log_entry(self, msg, is_warning=False): |
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self.cuda_setup_log.append((msg, is_warning)) |
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def print_log_stack(self): |
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for msg, is_warning in self.cuda_setup_log: |
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if is_warning: |
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warn(msg) |
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else: |
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print(msg) |
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@classmethod |
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def get_instance(cls): |
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if cls._instance is None: |
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cls._instance = cls.__new__(cls) |
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cls._instance.initialize() |
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return cls._instance |
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lib = CUDASetup.get_instance().lib |
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try: |
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if lib is None and torch.cuda.is_available(): |
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CUDASetup.get_instance().generate_instructions() |
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CUDASetup.get_instance().print_log_stack() |
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raise RuntimeError(''' |
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CUDA Setup failed despite GPU being available. Inspect the CUDA SETUP outputs aboveto fix your environment! |
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If you cannot find any issues and suspect a bug, please open an issue with detals about your environment: |
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https://github.com/TimDettmers/bitsandbytes/issues''') |
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lib.cadam32bit_g32 |
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lib.get_context.restype = ct.c_void_p |
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lib.get_cusparse.restype = ct.c_void_p |
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COMPILED_WITH_CUDA = True |
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except AttributeError: |
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warn("The installed version of bitsandbytes was compiled without GPU support. " |
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"8-bit optimizers and GPU quantization are unavailable.") |
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COMPILED_WITH_CUDA = False |
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