forked from mrq/bitsandbytes-rocm
136 lines
6.9 KiB
Python
136 lines
6.9 KiB
Python
import ctypes as ct
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from pathlib import Path
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from warnings import warn
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import torch
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class CUDASetup:
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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 git@github.com: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.has_printed = False
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self.lib = None
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self.run_cuda_setup()
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def run_cuda_setup(self):
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self.initialized = True
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self.cuda_setup_log = []
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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 Exception as ex:
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self.add_log_entry(str(ex))
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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 above to 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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