1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
|
import ctypes as ct
import torch
from pathlib import Path
from warnings import warn
class CUDASetup(object):
_instance = None
def __init__(self):
raise RuntimeError("Call get_instance() instead")
def generate_instructions(self):
if self.cuda is None:
self.add_log_entry('CUDA SETUP: Problem: The main issue seems to be that the main CUDA library was not detected.')
self.add_log_entry('CUDA SETUP: Solution 1): Your paths are probably not up-to-date. You can update them via: sudo ldconfig.')
self.add_log_entry('CUDA SETUP: Solution 2): If you do not have sudo rights, you can do the following:')
self.add_log_entry('CUDA SETUP: Solution 2a): Find the cuda library via: find / -name libcuda.so 2>/dev/null')
self.add_log_entry('CUDA SETUP: Solution 2b): Once the library is found add it to the LD_LIBRARY_PATH: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:FOUND_PATH_FROM_2a')
self.add_log_entry('CUDA SETUP: Solution 2c): For a permanent solution add the export from 2b into your .bashrc file, located at ~/.bashrc')
return
if self.cudart_path is None:
self.add_log_entry('CUDA SETUP: Problem: The main issue seems to be that the main CUDA runtime library was not detected.')
self.add_log_entry('CUDA SETUP: Solution 1: To solve the issue the libcudart.so location needs to be added to the LD_LIBRARY_PATH variable')
self.add_log_entry('CUDA SETUP: Solution 1a): Find the cuda runtime library via: find / -name libcudart.so 2>/dev/null')
self.add_log_entry('CUDA SETUP: Solution 1b): Once the library is found add it to the LD_LIBRARY_PATH: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:FOUND_PATH_FROM_1a')
self.add_log_entry('CUDA SETUP: Solution 1c): For a permanent solution add the export from 1b into your .bashrc file, located at ~/.bashrc')
self.add_log_entry('CUDA SETUP: Solution 2: If no library was found in step 1a) you need to install CUDA.')
self.add_log_entry('CUDA SETUP: Solution 2a): Download CUDA install script: wget https://github.com/TimDettmers/bitsandbytes/blob/main/cuda_install.sh')
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.')
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')
return
make_cmd = f'CUDA_VERSION={self.cuda_version_string}'
if len(self.cuda_version_string) < 3:
make_cmd += ' make cuda92'
elif self.cuda_version_string == '110':
make_cmd += ' make cuda110'
elif self.cuda_version_string[:2] == '11' and int(self.cuda_version_string[2]) > 0:
make_cmd += ' make cuda11x'
has_cublaslt = self.cc in ["7.5", "8.0", "8.6"]
if not has_cublaslt:
make_cmd += '_nomatmul'
self.add_log_entry('CUDA SETUP: Something unexpected happened. Please compile from source:')
self.add_log_entry('git clone git@github.com:TimDettmers/bitsandbytes.git')
self.add_log_entry('cd bitsandbytes')
self.add_log_entry(make_cmd)
self.add_log_entry('python setup.py install')
def initialize(self):
self.has_printed = False
self.lib = None
self.run_cuda_setup()
def run_cuda_setup(self):
self.initialized = True
self.cuda_setup_log = []
from .cuda_setup.main import evaluate_cuda_setup
binary_name, cudart_path, cuda, cc, cuda_version_string = evaluate_cuda_setup()
self.cudart_path = cudart_path
self.cuda = cuda
self.cc = cc
self.cuda_version_string = cuda_version_string
package_dir = Path(__file__).parent
binary_path = package_dir / binary_name
try:
if not binary_path.exists():
self.add_log_entry(f"CUDA SETUP: Required library version not found: {binary_name}. Maybe you need to compile it from source?")
self.add_log_entry(f"CUDA SETUP: looked in {binary_path}")
legacy_binary_name = "libbitsandbytes.so"
self.add_log_entry(f"CUDA SETUP: Defaulting to {legacy_binary_name}...")
binary_path = package_dir / legacy_binary_name
if not binary_path.exists():
self.add_log_entry('')
self.add_log_entry('='*48 + 'ERROR' + '='*37)
self.add_log_entry('CUDA SETUP: CUDA detection failed! Possible reasons:')
self.add_log_entry('1. CUDA driver not installed')
self.add_log_entry('2. CUDA not installed')
self.add_log_entry('3. You have multiple conflicting CUDA libraries')
self.add_log_entry('4. Required library not pre-compiled for this bitsandbytes release!')
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`.')
self.add_log_entry('='*80)
self.add_log_entry('')
self.generate_instructions()
self.print_log_stack()
raise Exception('CUDA SETUP: Setup Failed!')
self.lib = ct.cdll.LoadLibrary(binary_path)
else:
self.add_log_entry(f"CUDA SETUP: Loading binary {binary_path}...")
self.lib = ct.cdll.LoadLibrary(binary_path)
except Exception as ex:
self.add_log_entry(str(ex))
self.print_log_stack()
def add_log_entry(self, msg, is_warning=False):
self.cuda_setup_log.append((msg, is_warning))
def print_log_stack(self):
for msg, is_warning in self.cuda_setup_log:
if is_warning:
warn(msg)
else:
print(msg)
@classmethod
def get_instance(cls):
if cls._instance is None:
cls._instance = cls.__new__(cls)
cls._instance.initialize()
return cls._instance
lib = CUDASetup.get_instance().lib
try:
if lib is None and torch.cuda.is_available():
CUDASetup.get_instance().generate_instructions()
CUDASetup.get_instance().print_log_stack()
raise RuntimeError('''
CUDA Setup failed despite GPU being available. Inspect the CUDA SETUP outputs aboveto fix your environment!
If you cannot find any issues and suspect a bug, please open an issue with detals about your environment:
https://github.com/TimDettmers/bitsandbytes/issues''')
lib.cadam32bit_g32
lib.get_context.restype = ct.c_void_p
lib.get_cusparse.restype = ct.c_void_p
COMPILED_WITH_CUDA = True
except AttributeError:
warn("The installed version of bitsandbytes was compiled without GPU support. "
"8-bit optimizers and GPU quantization are unavailable.")
COMPILED_WITH_CUDA = False
|
