forked from mrq/bitsandbytes-rocm
CUDASetup only executed once + fixed circular import.
This commit is contained in:
Tim Dettmers
parent
df9a9b0c4c
commit
336e24696c
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@ -1,122 +1,17 @@
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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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import torch
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from bitsandbytes.cuda_setup.main import CUDASetup
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class CUDASetup:
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_instance = None
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setup = CUDASetup.get_instance()
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if setup.initialized != True:
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setup.run_cuda_setup()
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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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lib = setup.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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@ -1,6 +0,0 @@
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from .main import evaluate_cuda_setup
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from .paths import (
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CUDA_RUNTIME_LIB,
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determine_cuda_runtime_lib_path,
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extract_candidate_paths,
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)
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@ -16,21 +16,243 @@ evaluation:
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- based on that set the default path
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"""
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import ctypes
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import ctypes as ct
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import os
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import errno
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import torch
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from bitsandbytes.cextension import CUDASetup
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from pathlib import Path
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from typing import Set, Union
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from .env_vars import get_potentially_lib_path_containing_env_vars
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from .paths import determine_cuda_runtime_lib_path
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CUDA_RUNTIME_LIB: str = "libcudart.so"
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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.initialized = False
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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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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.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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def extract_candidate_paths(paths_list_candidate: str) -> Set[Path]:
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return {Path(ld_path) for ld_path in paths_list_candidate.split(":") if ld_path}
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def remove_non_existent_dirs(candidate_paths: Set[Path]) -> Set[Path]:
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existent_directories: Set[Path] = set()
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for path in candidate_paths:
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try:
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if path.exists():
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existent_directories.add(path)
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except OSError as exc:
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if exc.errno != errno.ENAMETOOLONG:
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raise exc
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non_existent_directories: Set[Path] = candidate_paths - existent_directories
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if non_existent_directories:
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CUDASetup.get_instance().add_log_entry("WARNING: The following directories listed in your path were found to "
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f"be non-existent: {non_existent_directories}", is_warning=True)
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return existent_directories
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def get_cuda_runtime_lib_paths(candidate_paths: Set[Path]) -> Set[Path]:
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return {
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path / CUDA_RUNTIME_LIB
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for path in candidate_paths
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if (path / CUDA_RUNTIME_LIB).is_file()
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}
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def resolve_paths_list(paths_list_candidate: str) -> Set[Path]:
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"""
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Searches a given environmental var for the CUDA runtime library,
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i.e. `libcudart.so`.
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"""
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return remove_non_existent_dirs(extract_candidate_paths(paths_list_candidate))
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def find_cuda_lib_in(paths_list_candidate: str) -> Set[Path]:
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return get_cuda_runtime_lib_paths(
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resolve_paths_list(paths_list_candidate)
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)
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def warn_in_case_of_duplicates(results_paths: Set[Path]) -> None:
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if len(results_paths) > 1:
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warning_msg = (
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f"Found duplicate {CUDA_RUNTIME_LIB} files: {results_paths}.. "
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"We'll flip a coin and try one of these, in order to fail forward.\n"
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"Either way, this might cause trouble in the future:\n"
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"If you get `CUDA error: invalid device function` errors, the above "
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"might be the cause and the solution is to make sure only one "
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f"{CUDA_RUNTIME_LIB} in the paths that we search based on your env.")
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CUDASetup.get_instance().add_log_entry(warning_msg, is_warning=True)
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def determine_cuda_runtime_lib_path() -> Union[Path, None]:
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"""
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Searches for a cuda installations, in the following order of priority:
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1. active conda env
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2. LD_LIBRARY_PATH
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3. any other env vars, while ignoring those that
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- are known to be unrelated (see `bnb.cuda_setup.env_vars.to_be_ignored`)
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- don't contain the path separator `/`
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If multiple libraries are found in part 3, we optimistically try one,
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while giving a warning message.
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"""
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candidate_env_vars = get_potentially_lib_path_containing_env_vars()
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if "CONDA_PREFIX" in candidate_env_vars:
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conda_libs_path = Path(candidate_env_vars["CONDA_PREFIX"]) / "lib"
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conda_cuda_libs = find_cuda_lib_in(str(conda_libs_path))
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warn_in_case_of_duplicates(conda_cuda_libs)
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if conda_cuda_libs:
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return next(iter(conda_cuda_libs))
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CUDASetup.get_instance().add_log_entry(f'{candidate_env_vars["CONDA_PREFIX"]} did not contain '
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f'{CUDA_RUNTIME_LIB} as expected! Searching further paths...', is_warning=True)
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if "LD_LIBRARY_PATH" in candidate_env_vars:
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lib_ld_cuda_libs = find_cuda_lib_in(candidate_env_vars["LD_LIBRARY_PATH"])
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if lib_ld_cuda_libs:
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return next(iter(lib_ld_cuda_libs))
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warn_in_case_of_duplicates(lib_ld_cuda_libs)
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CUDASetup.get_instance().add_log_entry(f'{candidate_env_vars["LD_LIBRARY_PATH"]} did not contain '
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f'{CUDA_RUNTIME_LIB} as expected! Searching further paths...', is_warning=True)
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remaining_candidate_env_vars = {
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env_var: value for env_var, value in candidate_env_vars.items()
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if env_var not in {"CONDA_PREFIX", "LD_LIBRARY_PATH"}
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}
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cuda_runtime_libs = set()
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for env_var, value in remaining_candidate_env_vars.items():
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cuda_runtime_libs.update(find_cuda_lib_in(value))
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if len(cuda_runtime_libs) == 0:
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CUDASetup.get_instance().add_log_entry('CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...')
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cuda_runtime_libs.update(find_cuda_lib_in('/usr/local/cuda/lib64'))
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warn_in_case_of_duplicates(cuda_runtime_libs)
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return next(iter(cuda_runtime_libs)) if cuda_runtime_libs else None
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def check_cuda_result(cuda, result_val):
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# 3. Check for CUDA errors
|
||||
if result_val != 0:
|
||||
error_str = ctypes.c_char_p()
|
||||
cuda.cuGetErrorString(result_val, ctypes.byref(error_str))
|
||||
error_str = ct.c_char_p()
|
||||
cuda.cuGetErrorString(result_val, ct.byref(error_str))
|
||||
CUDASetup.get_instance().add_log_entry(f"CUDA exception! Error code: {error_str.value.decode()}")
|
||||
|
||||
|
||||
|
|
@ -39,13 +261,13 @@ def get_cuda_version(cuda, cudart_path):
|
|||
if cuda is None: return None
|
||||
|
||||
try:
|
||||
cudart = ctypes.CDLL(cudart_path)
|
||||
cudart = ct.CDLL(cudart_path)
|
||||
except OSError:
|
||||
CUDASetup.get_instance().add_log_entry(f'ERROR: libcudart.so could not be read from path: {cudart_path}!')
|
||||
return None
|
||||
|
||||
version = ctypes.c_int()
|
||||
check_cuda_result(cuda, cudart.cudaRuntimeGetVersion(ctypes.byref(version)))
|
||||
version = ct.c_int()
|
||||
check_cuda_result(cuda, cudart.cudaRuntimeGetVersion(ct.byref(version)))
|
||||
version = int(version.value)
|
||||
major = version//1000
|
||||
minor = (version-(major*1000))//10
|
||||
|
|
@ -59,7 +281,7 @@ def get_cuda_version(cuda, cudart_path):
|
|||
def get_cuda_lib_handle():
|
||||
# 1. find libcuda.so library (GPU driver) (/usr/lib)
|
||||
try:
|
||||
cuda = ctypes.CDLL("libcuda.so")
|
||||
cuda = ct.CDLL("libcuda.so")
|
||||
except OSError:
|
||||
CUDASetup.get_instance().add_log_entry('CUDA SETUP: WARNING! libcuda.so not found! Do you have a CUDA driver installed? If you are on a cluster, make sure you are on a CUDA machine!')
|
||||
return None
|
||||
|
|
@ -79,18 +301,18 @@ def get_compute_capabilities(cuda):
|
|||
# bits taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549
|
||||
"""
|
||||
|
||||
nGpus = ctypes.c_int()
|
||||
cc_major = ctypes.c_int()
|
||||
cc_minor = ctypes.c_int()
|
||||
nGpus = ct.c_int()
|
||||
cc_major = ct.c_int()
|
||||
cc_minor = ct.c_int()
|
||||
|
||||
device = ctypes.c_int()
|
||||
device = ct.c_int()
|
||||
|
||||
check_cuda_result(cuda, cuda.cuDeviceGetCount(ctypes.byref(nGpus)))
|
||||
check_cuda_result(cuda, cuda.cuDeviceGetCount(ct.byref(nGpus)))
|
||||
ccs = []
|
||||
for i in range(nGpus.value):
|
||||
check_cuda_result(cuda, cuda.cuDeviceGet(ctypes.byref(device), i))
|
||||
ref_major = ctypes.byref(cc_major)
|
||||
ref_minor = ctypes.byref(cc_minor)
|
||||
check_cuda_result(cuda, cuda.cuDeviceGet(ct.byref(device), i))
|
||||
ref_major = ct.byref(cc_major)
|
||||
ref_minor = ct.byref(cc_minor)
|
||||
# 2. call extern C function to determine CC
|
||||
check_cuda_result(cuda, cuda.cuDeviceComputeCapability(ref_major, ref_minor, device))
|
||||
ccs.append(f"{cc_major.value}.{cc_minor.value}")
|
||||
|
|
|
|||
|
|
@ -1,119 +0,0 @@
|
|||
import errno
|
||||
from pathlib import Path
|
||||
from typing import Set, Union
|
||||
|
||||
from bitsandbytes.cextension import CUDASetup
|
||||
|
||||
from .env_vars import get_potentially_lib_path_containing_env_vars
|
||||
|
||||
CUDA_RUNTIME_LIB: str = "libcudart.so"
|
||||
|
||||
|
||||
def extract_candidate_paths(paths_list_candidate: str) -> Set[Path]:
|
||||
return {Path(ld_path) for ld_path in paths_list_candidate.split(":") if ld_path}
|
||||
|
||||
|
||||
def remove_non_existent_dirs(candidate_paths: Set[Path]) -> Set[Path]:
|
||||
existent_directories: Set[Path] = set()
|
||||
for path in candidate_paths:
|
||||
try:
|
||||
if path.exists():
|
||||
existent_directories.add(path)
|
||||
except OSError as exc:
|
||||
if exc.errno != errno.ENAMETOOLONG:
|
||||
raise exc
|
||||
|
||||
non_existent_directories: Set[Path] = candidate_paths - existent_directories
|
||||
if non_existent_directories:
|
||||
CUDASetup.get_instance().add_log_entry("WARNING: The following directories listed in your path were found to "
|
||||
f"be non-existent: {non_existent_directories}", is_warning=True)
|
||||
|
||||
return existent_directories
|
||||
|
||||
|
||||
def get_cuda_runtime_lib_paths(candidate_paths: Set[Path]) -> Set[Path]:
|
||||
return {
|
||||
path / CUDA_RUNTIME_LIB
|
||||
for path in candidate_paths
|
||||
if (path / CUDA_RUNTIME_LIB).is_file()
|
||||
}
|
||||
|
||||
|
||||
def resolve_paths_list(paths_list_candidate: str) -> Set[Path]:
|
||||
"""
|
||||
Searches a given environmental var for the CUDA runtime library,
|
||||
i.e. `libcudart.so`.
|
||||
"""
|
||||
return remove_non_existent_dirs(extract_candidate_paths(paths_list_candidate))
|
||||
|
||||
|
||||
def find_cuda_lib_in(paths_list_candidate: str) -> Set[Path]:
|
||||
return get_cuda_runtime_lib_paths(
|
||||
resolve_paths_list(paths_list_candidate)
|
||||
)
|
||||
|
||||
|
||||
def warn_in_case_of_duplicates(results_paths: Set[Path]) -> None:
|
||||
if len(results_paths) > 1:
|
||||
warning_msg = (
|
||||
f"Found duplicate {CUDA_RUNTIME_LIB} files: {results_paths}.. "
|
||||
"We'll flip a coin and try one of these, in order to fail forward.\n"
|
||||
"Either way, this might cause trouble in the future:\n"
|
||||
"If you get `CUDA error: invalid device function` errors, the above "
|
||||
"might be the cause and the solution is to make sure only one "
|
||||
f"{CUDA_RUNTIME_LIB} in the paths that we search based on your env.")
|
||||
CUDASetup.get_instance().add_log_entry(warning_msg, is_warning=True)
|
||||
|
||||
|
||||
def determine_cuda_runtime_lib_path() -> Union[Path, None]:
|
||||
"""
|
||||
Searches for a cuda installations, in the following order of priority:
|
||||
1. active conda env
|
||||
2. LD_LIBRARY_PATH
|
||||
3. any other env vars, while ignoring those that
|
||||
- are known to be unrelated (see `bnb.cuda_setup.env_vars.to_be_ignored`)
|
||||
- don't contain the path separator `/`
|
||||
|
||||
If multiple libraries are found in part 3, we optimistically try one,
|
||||
while giving a warning message.
|
||||
"""
|
||||
candidate_env_vars = get_potentially_lib_path_containing_env_vars()
|
||||
|
||||
if "CONDA_PREFIX" in candidate_env_vars:
|
||||
conda_libs_path = Path(candidate_env_vars["CONDA_PREFIX"]) / "lib"
|
||||
|
||||
conda_cuda_libs = find_cuda_lib_in(str(conda_libs_path))
|
||||
warn_in_case_of_duplicates(conda_cuda_libs)
|
||||
|
||||
if conda_cuda_libs:
|
||||
return next(iter(conda_cuda_libs))
|
||||
|
||||
CUDASetup.get_instance().add_log_entry(f'{candidate_env_vars["CONDA_PREFIX"]} did not contain '
|
||||
f'{CUDA_RUNTIME_LIB} as expected! Searching further paths...', is_warning=True)
|
||||
|
||||
if "LD_LIBRARY_PATH" in candidate_env_vars:
|
||||
lib_ld_cuda_libs = find_cuda_lib_in(candidate_env_vars["LD_LIBRARY_PATH"])
|
||||
|
||||
if lib_ld_cuda_libs:
|
||||
return next(iter(lib_ld_cuda_libs))
|
||||
warn_in_case_of_duplicates(lib_ld_cuda_libs)
|
||||
|
||||
CUDASetup.get_instance().add_log_entry(f'{candidate_env_vars["LD_LIBRARY_PATH"]} did not contain '
|
||||
f'{CUDA_RUNTIME_LIB} as expected! Searching further paths...', is_warning=True)
|
||||
|
||||
remaining_candidate_env_vars = {
|
||||
env_var: value for env_var, value in candidate_env_vars.items()
|
||||
if env_var not in {"CONDA_PREFIX", "LD_LIBRARY_PATH"}
|
||||
}
|
||||
|
||||
cuda_runtime_libs = set()
|
||||
for env_var, value in remaining_candidate_env_vars.items():
|
||||
cuda_runtime_libs.update(find_cuda_lib_in(value))
|
||||
|
||||
if len(cuda_runtime_libs) == 0:
|
||||
CUDASetup.get_instance().add_log_entry('CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...')
|
||||
cuda_runtime_libs.update(find_cuda_lib_in('/usr/local/cuda/lib64'))
|
||||
|
||||
warn_in_case_of_duplicates(cuda_runtime_libs)
|
||||
|
||||
return next(iter(cuda_runtime_libs)) if cuda_runtime_libs else None
|
||||
|
|
@ -4,7 +4,7 @@ from typing import List, NamedTuple
|
|||
import pytest
|
||||
|
||||
import bitsandbytes as bnb
|
||||
from bitsandbytes.cuda_setup import (
|
||||
from bitsandbytes.cuda_setup.main import (
|
||||
CUDA_RUNTIME_LIB,
|
||||
determine_cuda_runtime_lib_path,
|
||||
evaluate_cuda_setup,
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user