From 7b5e0592f875772cfed27f00fe16928a503c582a Mon Sep 17 00:00:00 2001 From: mrq Date: Thu, 16 Mar 2023 20:42:32 +0000 Subject: [PATCH] migrated bitsandbytes out, since AIVC technically uses this more --- bitsandbytes_windows/cextension.py | 54 ------ bitsandbytes_windows/cuda_setup/main.py | 168 ------------------ bitsandbytes_windows/libbitsandbytes_cpu.dll | Bin 76288 -> 0 bytes .../libbitsandbytes_cuda116.dll | Bin 4724224 -> 0 bytes bitsandbytes_windows/nn/__init__.py | 6 - 5 files changed, 228 deletions(-) delete mode 100644 bitsandbytes_windows/cextension.py delete mode 100644 bitsandbytes_windows/cuda_setup/main.py delete mode 100644 bitsandbytes_windows/libbitsandbytes_cpu.dll delete mode 100644 bitsandbytes_windows/libbitsandbytes_cuda116.dll delete mode 100644 bitsandbytes_windows/nn/__init__.py diff --git a/bitsandbytes_windows/cextension.py b/bitsandbytes_windows/cextension.py deleted file mode 100644 index f2dc4b87..00000000 --- a/bitsandbytes_windows/cextension.py +++ /dev/null @@ -1,54 +0,0 @@ -import ctypes as ct -from pathlib import Path -from warnings import warn - -from .cuda_setup.main import evaluate_cuda_setup - - -class CUDALibrary_Singleton(object): - _instance = None - - def __init__(self): - raise RuntimeError("Call get_instance() instead") - - def initialize(self): - binary_name = evaluate_cuda_setup() - package_dir = Path(__file__).parent - binary_path = package_dir / binary_name - - if not binary_path.exists(): - print(f"CUDA SETUP: TODO: compile library for specific version: {binary_name}") - legacy_binary_name = "libbitsandbytes.so" - print(f"CUDA SETUP: Defaulting to {legacy_binary_name}...") - binary_path = package_dir / legacy_binary_name - if not binary_path.exists(): - print('CUDA SETUP: CUDA detection failed. Either CUDA driver not installed, CUDA not installed, or you have multiple conflicting CUDA libraries!') - print('CUDA SETUP: If you compiled from source, try again with `make CUDA_VERSION=DETECTED_CUDA_VERSION` for example, `make CUDA_VERSION=113`.') - raise Exception('CUDA SETUP: Setup Failed!') - # self.lib = ct.cdll.LoadLibrary(binary_path) - self.lib = ct.cdll.LoadLibrary(str(binary_path)) # $$$ - else: - #print(f"CUDA SETUP: Loading binary {binary_path}...") - # self.lib = ct.cdll.LoadLibrary(binary_path) - self.lib = ct.cdll.LoadLibrary(str(binary_path)) # $$$ - - @classmethod - def get_instance(cls): - if cls._instance is None: - cls._instance = cls.__new__(cls) - cls._instance.initialize() - return cls._instance - - -lib = CUDALibrary_Singleton.get_instance().lib -try: - 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 diff --git a/bitsandbytes_windows/cuda_setup/main.py b/bitsandbytes_windows/cuda_setup/main.py deleted file mode 100644 index 85788910..00000000 --- a/bitsandbytes_windows/cuda_setup/main.py +++ /dev/null @@ -1,168 +0,0 @@ -""" -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 - -from .paths import determine_cuda_runtime_lib_path - - -def check_cuda_result(cuda, result_val): - # 3. Check for CUDA errors - if result_val != 0: - error_str = ctypes.c_char_p() - cuda.cuGetErrorString(result_val, ctypes.byref(error_str)) - print(f"CUDA exception! Error code: {error_str.value.decode()}") - -def get_cuda_version(cuda, cudart_path): - # https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART____VERSION.html#group__CUDART____VERSION - try: - cudart = ctypes.CDLL(cudart_path) - except OSError: - # TODO: shouldn't we error or at least warn here? - print(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 = int(version.value) - major = version//1000 - minor = (version-(major*1000))//10 - - if major < 11: - print('CUDA SETUP: CUDA version lower than 11 are currently not supported for LLM.int8(). You will be only to use 8-bit optimizers and quantization routines!!') - - return f'{major}{minor}' - - -def get_cuda_lib_handle(): - # 1. find libcuda.so library (GPU driver) (/usr/lib) - try: - cuda = ctypes.CDLL("libcuda.so") - except OSError: - # TODO: shouldn't we error or at least warn here? - print('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 - check_cuda_result(cuda, cuda.cuInit(0)) - - return cuda - - -def get_compute_capabilities(cuda): - """ - 1. find libcuda.so library (GPU driver) (/usr/lib) - init_device -> init variables -> call function by reference - 2. call extern C function to determine CC - (https://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__DEVICE__DEPRECATED.html) - 3. Check for CUDA errors - https://stackoverflow.com/questions/14038589/what-is-the-canonical-way-to-check-for-errors-using-the-cuda-runtime-api - # bits taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549 - """ - - - nGpus = ctypes.c_int() - cc_major = ctypes.c_int() - cc_minor = ctypes.c_int() - - device = ctypes.c_int() - - check_cuda_result(cuda, cuda.cuDeviceGetCount(ctypes.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) - # 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}") - - return ccs - - -# def get_compute_capability()-> Union[List[str, ...], None]: # FIXME: error -def get_compute_capability(cuda): - """ - Extracts the highest compute capbility from all available GPUs, as compute - capabilities are downwards compatible. If no GPUs are detected, it returns - None. - """ - ccs = get_compute_capabilities(cuda) - if ccs is not None: - # TODO: handle different compute capabilities; for now, take the max - return ccs[-1] - return None - - -def evaluate_cuda_setup(): - """ - print('') - print('='*35 + 'BUG REPORT' + '='*35) - print('Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues') - print('For effortless bug reporting copy-paste your error into this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link') - print('='*80) - """ - return "libbitsandbytes_cuda116.dll" # $$$ - - binary_name = "libbitsandbytes_cpu.so" - #if not torch.cuda.is_available(): - #print('No GPU detected. Loading CPU library...') - #return binary_name - - cudart_path = determine_cuda_runtime_lib_path() - if cudart_path is None: - print( - "WARNING: No libcudart.so found! Install CUDA or the cudatoolkit package (anaconda)!" - ) - return binary_name - - print(f"CUDA SETUP: CUDA runtime path found: {cudart_path}") - cuda = get_cuda_lib_handle() - cc = get_compute_capability(cuda) - print(f"CUDA SETUP: Highest compute capability among GPUs detected: {cc}") - cuda_version_string = get_cuda_version(cuda, cudart_path) - - - if cc == '': - print( - "WARNING: No GPU detected! Check your CUDA paths. Processing to load CPU-only library..." - ) - return binary_name - - # 7.5 is the minimum CC vor cublaslt - has_cublaslt = cc in ["7.5", "8.0", "8.6"] - - # TODO: - # (1) CUDA missing cases (no CUDA installed by CUDA driver (nvidia-smi accessible) - # (2) Multiple CUDA versions installed - - # we use ls -l instead of nvcc to determine the cuda version - # since most installations will have the libcudart.so installed, but not the compiler - print(f'CUDA SETUP: Detected CUDA version {cuda_version_string}') - - def get_binary_name(): - "if not has_cublaslt (CC < 7.5), then we have to choose _nocublaslt.so" - bin_base_name = "libbitsandbytes_cuda" - if has_cublaslt: - return f"{bin_base_name}{cuda_version_string}.so" - else: - return f"{bin_base_name}{cuda_version_string}_nocublaslt.so" - - binary_name = get_binary_name() - - return binary_name diff --git a/bitsandbytes_windows/libbitsandbytes_cpu.dll b/bitsandbytes_windows/libbitsandbytes_cpu.dll deleted file mode 100644 index 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