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-rw-r--r--bitsandbytes/cuda_setup/main.py40
-rw-r--r--bitsandbytes/cuda_setup/paths.py27
2 files changed, 29 insertions, 38 deletions
diff --git a/bitsandbytes/cuda_setup/main.py b/bitsandbytes/cuda_setup/main.py
index f11b430..f8f35f0 100644
--- a/bitsandbytes/cuda_setup/main.py
+++ b/bitsandbytes/cuda_setup/main.py
@@ -19,6 +19,7 @@ evaluation:
import ctypes
from .paths import determine_cuda_runtime_lib_path
+from bitsandbytes.cextension import CUDASetup
def check_cuda_result(cuda, result_val):
@@ -26,15 +27,14 @@ def check_cuda_result(cuda, result_val):
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()}")
+ CUDASetup.get_instance.add_log_entry(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}!')
+ CUDASetup.get_instance.add_log_entry(f'ERROR: libcudart.so could not be read from path: {cudart_path}!')
return None
version = ctypes.c_int()
@@ -44,7 +44,7 @@ def get_cuda_version(cuda, cudart_path):
minor = (version-(major*1000))//10
if major < 11:
- print('CUDA SETUP: CUDA version lower than 11 are currenlty not supported for LLM.int8(). You will be only to use 8-bit optimizers and quantization routines!!')
+ CUDASetup.get_instance().add_log_entry('CUDA SETUP: CUDA version lower than 11 are currenlty not supported for LLM.int8(). You will be only to use 8-bit optimizers and quantization routines!!')
return f'{major}{minor}'
@@ -54,8 +54,7 @@ def get_cuda_lib_handle():
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!')
+ CUDA_RUNTIME_LIB.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
check_cuda_result(cuda, cuda.cuInit(0))
@@ -110,34 +109,33 @@ def get_compute_capability(cuda):
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)
- binary_name = "libbitsandbytes_cpu.so"
+ # we remove this for now and see how things go
+ #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)
#if not torch.cuda.is_available():
#print('No GPU detected. Loading CPU library...')
#return binary_name
+ binary_name = "libbitsandbytes_cpu.so"
+
+ cuda_setup = CUDASetup.get_instance()
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)!"
- )
+ cuda_setup.add_log_entry("WARNING: No libcudart.so found! Install CUDA or the cudatoolkit package (anaconda)!", is_warning=True)
return binary_name
- print(f"CUDA SETUP: CUDA runtime path found: {cudart_path}")
+ cuda_setup.add_log_entry((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_setup.add_log_entry(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..."
- )
+ cuda_setup.add_log_entry("WARNING: No GPU detected! Check your CUDA paths. Processing to load CPU-only library...", is_warning=True)
return binary_name
# 7.5 is the minimum CC vor cublaslt
@@ -149,7 +147,7 @@ def evaluate_cuda_setup():
# 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}')
+ cuda_setup.add_log_entry(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"
diff --git a/bitsandbytes/cuda_setup/paths.py b/bitsandbytes/cuda_setup/paths.py
index ba3f97f..3223359 100644
--- a/bitsandbytes/cuda_setup/paths.py
+++ b/bitsandbytes/cuda_setup/paths.py
@@ -1,7 +1,7 @@
import errno
from pathlib import Path
from typing import Set, Union
-from warnings import warn
+from bitsandbytes.cextension import CUDASetup
from .env_vars import get_potentially_lib_path_containing_env_vars
@@ -24,10 +24,8 @@ def remove_non_existent_dirs(candidate_paths: Set[Path]) -> Set[Path]:
non_existent_directories: Set[Path] = candidate_paths - existent_directories
if non_existent_directories:
- warn(
- "WARNING: The following directories listed in your path were found to "
- f"be non-existent: {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
@@ -62,9 +60,8 @@ def warn_in_case_of_duplicates(results_paths: Set[Path]) -> None:
"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."
- )
- warn(warning_msg)
+ 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]:
@@ -90,10 +87,8 @@ def determine_cuda_runtime_lib_path() -> Union[Path, None]:
if conda_cuda_libs:
return next(iter(conda_cuda_libs))
- warn(
- f'{candidate_env_vars["CONDA_PREFIX"]} did not contain '
- f'{CUDA_RUNTIME_LIB} as expected! Searching further paths...'
- )
+ 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"])
@@ -102,10 +97,8 @@ def determine_cuda_runtime_lib_path() -> Union[Path, None]:
return next(iter(lib_ld_cuda_libs))
warn_in_case_of_duplicates(lib_ld_cuda_libs)
- warn(
- f'{candidate_env_vars["LD_LIBRARY_PATH"]} did not contain '
- f'{CUDA_RUNTIME_LIB} as expected! Searching further paths...'
- )
+ 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()
@@ -117,7 +110,7 @@ def determine_cuda_runtime_lib_path() -> Union[Path, None]:
cuda_runtime_libs.update(find_cuda_lib_in(value))
if len(cuda_runtime_libs) == 0:
- print('CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...')
+ 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)