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"""
extract factors the build is dependent on:
[X] compute capability
[ ] TODO: Q - What if we have multiple GPUs of different makes?
- CUDA version
- Software:
- CPU-only: only CPU quantization functions (no optimizer, no matrix multiple)
- CuBLAS-LT: full-build 8-bit optimizer
- no CuBLAS-LT: no 8-bit matrix multiplication (`nomatmul`)
evaluation:
- if paths faulty, return meaningful error
- else:
- determine CUDA version
- determine capabilities
- based on that set the default path
"""
import ctypes as ct
import logging
import os
from pathlib import Path
import torch
from bitsandbytes.consts import DYNAMIC_LIBRARY_SUFFIX, PACKAGE_DIR
from bitsandbytes.cuda_specs import CUDASpecs, get_cuda_specs
logger = logging.getLogger(__name__)
def get_cuda_bnb_library_path(cuda_specs: CUDASpecs) -> Path:
"""
Get the disk path to the CUDA BNB native library specified by the
given CUDA specs, taking into account the `BNB_CUDA_VERSION` override environment variable.
The library is not guaranteed to exist at the returned path.
"""
library_name = f"libbitsandbytes_cuda{cuda_specs.cuda_version_string}"
if not cuda_specs.has_cublaslt:
# if not has_cublaslt (CC < 7.5), then we have to choose _nocublaslt
library_name += "_nocublaslt"
library_name = f"{library_name}{DYNAMIC_LIBRARY_SUFFIX}"
override_value = os.environ.get("BNB_CUDA_VERSION")
if override_value:
library_name_stem, _, library_name_ext = library_name.rpartition(".")
# `library_name_stem` will now be e.g. `libbitsandbytes_cuda118`;
# let's remove any trailing numbers:
library_name_stem = library_name_stem.rstrip("0123456789")
# `library_name_stem` will now be e.g. `libbitsandbytes_cuda`;
# let's tack the new version number and the original extension back on.
library_name = f"{library_name_stem}{override_value}.{library_name_ext}"
logger.warning(
f"WARNING: BNB_CUDA_VERSION={override_value} environment variable detected; loading {library_name}.\n"
"This can be used to load a bitsandbytes version that is different from the PyTorch CUDA version.\n"
"If this was unintended set the BNB_CUDA_VERSION variable to an empty string: export BNB_CUDA_VERSION=\n"
"If you use the manual override make sure the right libcudart.so is in your LD_LIBRARY_PATH\n"
"For example by adding the following to your .bashrc: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<path_to_cuda_dir/lib64\n",
)
return PACKAGE_DIR / library_name
class BNBNativeLibrary:
_lib: ct.CDLL
compiled_with_cuda = False
def __init__(self, lib: ct.CDLL):
self._lib = lib
def __getattr__(self, item):
return getattr(self._lib, item)
class CudaBNBNativeLibrary(BNBNativeLibrary):
compiled_with_cuda = True
def __init__(self, lib: ct.CDLL):
super().__init__(lib)
lib.get_context.restype = ct.c_void_p
lib.get_cusparse.restype = ct.c_void_p
lib.cget_managed_ptr.restype = ct.c_void_p
def get_native_library() -> BNBNativeLibrary:
binary_path = PACKAGE_DIR / f"libbitsandbytes_cpu{DYNAMIC_LIBRARY_SUFFIX}"
cuda_specs = get_cuda_specs()
if cuda_specs:
cuda_binary_path = get_cuda_bnb_library_path(cuda_specs)
if cuda_binary_path.exists():
binary_path = cuda_binary_path
else:
logger.warning("Could not find the bitsandbytes CUDA binary at %r", cuda_binary_path)
logger.debug(f"Loading bitsandbytes native library from: {binary_path}")
dll = ct.cdll.LoadLibrary(str(binary_path))
if hasattr(dll, "get_context"): # only a CUDA-built library exposes this
return CudaBNBNativeLibrary(dll)
logger.warning(
"The installed version of bitsandbytes was compiled without GPU support. "
"8-bit optimizers, 8-bit multiplication, and GPU quantization are unavailable.",
)
return BNBNativeLibrary(dll)
try:
lib = get_native_library()
except Exception as e:
lib = None
logger.error(f"Could not load bitsandbytes native library: {e}", exc_info=True)
if torch.cuda.is_available():
logger.warning(
"""
CUDA Setup failed despite CUDA being available. Please run the following command to get more information:
python -m bitsandbytes
Inspect the output of the command and see if you can locate CUDA libraries. You might need to add them
to your LD_LIBRARY_PATH. If you suspect a bug, please take the information from python -m bitsandbytes
and open an issue at: https://github.com/TimDettmers/bitsandbytes/issues
""",
)
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