diff --git a/bitsandbytes/__main__.py b/bitsandbytes/__main__.py index 5f11875..175a30e 100644 --- a/bitsandbytes/__main__.py +++ b/bitsandbytes/__main__.py @@ -3,8 +3,9 @@ # cli() import os import sys -import torch +from warnings import warn +import torch HEADER_WIDTH = 60 @@ -32,8 +33,6 @@ print() from . import COMPILED_WITH_CUDA, PACKAGE_GITHUB_URL from .cuda_setup.main import get_compute_capabilities, get_cuda_lib_handle from .cuda_setup.env_vars import to_be_ignored -from .utils import print_stderr - print_header("POTENTIALLY LIBRARY-PATH-LIKE ENV VARS") for k, v in os.environ.items(): @@ -84,7 +83,7 @@ try: except ImportError: print() - print_stderr( + warn( f"WARNING: {__package__} is currently running as CPU-only!\n" "Therefore, 8-bit optimizers and GPU quantization are unavailable.\n\n" f"If you think that this is so erroneously,\nplease report an issue!" diff --git a/bitsandbytes/autograd/_functions.py b/bitsandbytes/autograd/_functions.py index 4dbf129..be975f6 100644 --- a/bitsandbytes/autograd/_functions.py +++ b/bitsandbytes/autograd/_functions.py @@ -1,6 +1,5 @@ import operator import torch -import bitsandbytes as bnb import bitsandbytes.functional as F from dataclasses import dataclass @@ -378,9 +377,6 @@ class MatMul8bitLt(torch.autograd.Function): return grad_A, grad_B, None, grad_bias, None -matmul = MatMul8bitLt.apply - - def matmul( A: tensor, B: tensor, diff --git a/bitsandbytes/cuda_setup/compute_capability.py b/bitsandbytes/cuda_setup/compute_capability.py deleted file mode 100644 index 7a3f463..0000000 --- a/bitsandbytes/cuda_setup/compute_capability.py +++ /dev/null @@ -1,79 +0,0 @@ -import ctypes -from dataclasses import dataclass, field - - -@dataclass -class CudaLibVals: - # code bits taken from - # https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549 - - nGpus: ctypes.c_int = field(default=ctypes.c_int()) - cc_major: ctypes.c_int = field(default=ctypes.c_int()) - cc_minor: ctypes.c_int = field(default=ctypes.c_int()) - device: ctypes.c_int = field(default=ctypes.c_int()) - error_str: ctypes.c_char_p = field(default=ctypes.c_char_p()) - cuda: ctypes.CDLL = field(init=False, repr=False) - ccs: List[str, ...] = field(init=False) - - def _initialize_driver_API(self): - self.check_cuda_result(self.cuda.cuInit(0)) - - def _load_cuda_lib(self): - """ - 1. find libcuda.so library (GPU driver) (/usr/lib) - init_device -> init variables -> call function by reference - """ - libnames = "libcuda.so" - for libname in libnames: - try: - self.cuda = ctypes.CDLL(libname) - except OSError: - continue - else: - break - else: - raise OSError("could not load any of: " + " ".join(libnames)) - - def call_cuda_func(self, function_obj, **kwargs): - CUDA_SUCCESS = 0 # constant taken from cuda.h - pass - # if (CUDA_SUCCESS := function_obj( - - def _error_handle(cuda_lib_call_return_value): - """ - 2. call extern C function to determine CC - (see https://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__DEVICE__DEPRECATED.html) - """ - CUDA_SUCCESS = 0 # constant taken from cuda.h - - if cuda_lib_call_return_value != CUDA_SUCCESS: - self.cuda.cuGetErrorString( - cuda_lib_call_return_value, - ctypes.byref(self.error_str), - ) - print("Count not initialize CUDA - failure!") - raise Exception("CUDA exception!") - return cuda_lib_call_return_value - - def __post_init__(self): - self._load_cuda_lib() - self._initialize_driver_API() - self.check_cuda_result( - self.cuda, self.cuda.cuDeviceGetCount(ctypes.byref(self.nGpus)) - ) - tmp_ccs = [] - for gpu_index in range(self.nGpus.value): - check_cuda_result( - self.cuda, - self.cuda.cuDeviceGet(ctypes.byref(self.device), gpu_index), - ) - check_cuda_result( - self.cuda, - self.cuda.cuDeviceComputeCapability( - ctypes.byref(self.cc_major), - ctypes.byref(self.cc_minor), - self.device, - ), - ) - tmp_ccs.append(f"{self.cc_major.value}.{self.cc_minor.value}") - self.ccs = sorted(tmp_ccs, reverse=True) diff --git a/bitsandbytes/cuda_setup/main.py b/bitsandbytes/cuda_setup/main.py index d305c64..78a2844 100644 --- a/bitsandbytes/cuda_setup/main.py +++ b/bitsandbytes/cuda_setup/main.py @@ -17,10 +17,7 @@ evaluation: """ import ctypes -import torch -from pathlib import Path -from ..utils import execute_and_return from .paths import determine_cuda_runtime_lib_path @@ -81,7 +78,6 @@ def get_compute_capabilities(cuda): cc_major = ctypes.c_int() cc_minor = ctypes.c_int() - result = ctypes.c_int() device = ctypes.c_int() check_cuda_result(cuda, cuda.cuDeviceGetCount(ctypes.byref(nGpus))) diff --git a/bitsandbytes/cuda_setup/paths.py b/bitsandbytes/cuda_setup/paths.py index 9c565c7..6f6425f 100644 --- a/bitsandbytes/cuda_setup/paths.py +++ b/bitsandbytes/cuda_setup/paths.py @@ -2,23 +2,11 @@ from pathlib import Path from typing import Set, Union from warnings import warn -from ..utils import print_stderr from .env_vars import get_potentially_lib_path_containing_env_vars - CUDA_RUNTIME_LIB: str = "libcudart.so" -def purge_unwanted_semicolon(tentative_path: Path) -> Path: - """ - Special function to handle the following exception: - __LMOD_REF_COUNT_PATH=/sw/cuda/11.6.2/bin:2;/mmfs1/home/dettmers/git/sched/bin:1;/mmfs1/home/dettmers/data/anaconda3/bin:1;/mmfs1/home/dettmers/data/anaconda3/condabin:1;/mmfs1/home/dettmers/.local/bin:1;/mmfs1/home/dettmers/bin:1;/usr/local/bin:1;/usr/bin:1;/usr/local/sbin:1;/usr/sbin:1;/mmfs1/home/dettmers/.fzf/bin:1;/mmfs1/home/dettmers/data/local/cuda-11.4/bin:1 - """ - # if ';' in str(tentative_path): - # path_as_str, _ = str(tentative_path).split(';') - pass - - 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} @@ -29,7 +17,7 @@ def remove_non_existent_dirs(candidate_paths: Set[Path]) -> Set[Path]: } if non_existent_directories: - print_stderr( + warn( "WARNING: The following directories listed in your path were found to " f"be non-existent: {non_existent_directories}" ) @@ -117,8 +105,6 @@ def determine_cuda_runtime_lib_path() -> Union[Path, None]: 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)) diff --git a/bitsandbytes/functional.py b/bitsandbytes/functional.py index 75d083b..22200f2 100644 --- a/bitsandbytes/functional.py +++ b/bitsandbytes/functional.py @@ -5,7 +5,6 @@ import ctypes as ct import operator import random -import math import torch from typing import Tuple @@ -243,23 +242,6 @@ def get_transform_func(dtype, orderA, orderOut, transpose=False): return getattr(lib, name) -class GlobalData(object): - _instance = None - - def __init__(self): - raise RuntimeError("Call get_instance() instead") - - def initialize(self): - self.data = {} - - @classmethod - def get_instance(cls): - if cls._instance is None: - cls._instance = cls.__new__(cls) - cls._instance.initialize() - return cls._instance - - def get_transform_buffer( shape, dtype, device, to_order, from_order="row", transpose=False ): diff --git a/bitsandbytes/utils.py b/bitsandbytes/utils.py index 4256a87..1cd90e3 100644 --- a/bitsandbytes/utils.py +++ b/bitsandbytes/utils.py @@ -1,6 +1,5 @@ import shlex import subprocess -import sys from typing import Tuple @@ -22,11 +21,3 @@ def execute_and_return(command_string: str) -> Tuple[str, str]: std_out, std_err = execute_and_return_decoded_std_streams(command_string) return std_out, std_err - - -def print_stderr(s: str) -> None: - print(s, file=sys.stderr) - - -def warn_of_missing_prerequisite(s: str) -> None: - print_stderr("WARNING, missing pre-requisite: " + s)