Fixed CUDA Conda PyTorch 2.0 issues.

README.md

@@ -14,8 +14,25 @@ Resources:
 Python >=3.8. Linux distribution (Ubuntu, MacOS, etc.) + CUDA > 10.0. LLM.int8() requires Turing or Ampere GPUs.
 
 **Installation**:
+
 ``pip install bitsandbytes``
 
+In some cases it can happen that you need to compile from source. In that case, you can install CUDA with the install script in the repository. No sudo is required for this install.
+
+```bash
+wget https://raw.githubusercontent.com/TimDettmers/bitsandbytes/main/cuda_install.sh
+# Syntax cuda_install CUDA_VERSION INSTALL_PREFIX EXPORT_TO_BASH
+#   CUDA_VERSION in {110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121}
+#   EXPORT_TO_BASH in {0, 1} with 0=False and 1=True 
+
+# For example, the following installs CUDA 11.8 to ~/local/cuda-11.8 and exports the path to your .bashrc
+bash cuda install 118 ~/local 1 
+```
+
+To use a specific CUDA version just for a single compile run, you can set the variable `CUDA_HOME`, for example the following command compiles `libbitsandbytes_cuda117.so` using compiler flags for cuda11x with the cuda version at `~/local/cuda-11.7`:
+
+``CUDA_HOME=~/local/cuda-11.7 CUDA_VERSION=117 make cuda11x``
+
 **Using 8-bit optimizer**:
 1. Comment out optimizer: ``#torch.optim.Adam(....)``
 2. Add 8-bit optimizer of your choice ``bnb.optim.Adam8bit(....)`` (arguments stay the same)

bitsandbytes/cextension.py

@@ -11,8 +11,6 @@
 setup = CUDASetup.get_instance()
 if setup.initialized != True:
     setup.run_cuda_setup()
-    if 'BITSANDBYTES_NOWELCOME' not in os.environ or str(os.environ['BITSANDBYTES_NOWELCOME']) == '0':
-        setup.print_log_stack()
 
 lib = setup.lib
 try:
@@ -31,3 +29,7 @@
     warn("The installed version of bitsandbytes was compiled without GPU support. "
         "8-bit optimizers and GPU quantization are unavailable.")
     COMPILED_WITH_CUDA = False
+
+# print the setup details after checking for errors so we do not print twice
+if 'BITSANDBYTES_NOWELCOME' not in os.environ or str(os.environ['BITSANDBYTES_NOWELCOME']) == '0':
+    setup.print_log_stack()

bitsandbytes/cuda_setup/main.py

@@ -21,12 +21,21 @@
 import errno
 import torch
 from warnings import warn
+from itertools import product
 
 from pathlib import Path
 from typing import Set, Union
 from .env_vars import get_potentially_lib_path_containing_env_vars
 
-CUDA_RUNTIME_LIB: str = "libcudart.so"
+# these are the most common libs names
+# libcudart.so is missing by default for a conda install with PyTorch 2.0 and instead
+# we have libcudart.so.11.0 which causes a lot of errors before
+# not sure if libcudart.so.12.0 exists in pytorch installs, but it does not hurt
+CUDA_RUNTIME_LIBS: list = ["libcudart.so", 'libcudart.so.11.0', 'libcudart.so.12.0']
+
+# this is a order list of backup paths to search CUDA in, if it cannot be found in the main environmental paths
+backup_paths = []
+backup_paths.append('$CONDA_PREFIX/lib/libcudart.so.11.0')
 
 class CUDASetup:
     _instance = None
@@ -98,6 +107,8 @@ def run_cuda_setup(self):
         package_dir = Path(__file__).parent.parent
         binary_path = package_dir / binary_name
 
+        print('bin', binary_path)
+
         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?")
@@ -117,15 +128,13 @@ def run_cuda_setup(self):
                     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))
@@ -178,11 +187,12 @@ def remove_non_existent_dirs(candidate_paths: Set[Path]) -> Set[Path]:
 
 
 def get_cuda_runtime_lib_paths(candidate_paths: Set[Path]) -> Set[Path]:
-    return {
-        path / CUDA_RUNTIME_LIB
-        for path in candidate_paths
-        if (path / CUDA_RUNTIME_LIB).is_file()
-    }
+    paths = set()
+    for libname in CUDA_RUNTIME_LIBS:
+        for path in candidate_paths:
+            if (path / libname).is_file():
+                paths.add(path / libname)
+    return paths
 
 
 def resolve_paths_list(paths_list_candidate: str) -> Set[Path]:
@@ -257,7 +267,7 @@ def determine_cuda_runtime_lib_path() -> Union[Path, None]:
         cuda_runtime_libs.update(find_cuda_lib_in(value))
 
     if len(cuda_runtime_libs) == 0:
-        CUDASetup.get_instance().add_log_entry('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 in backup paths...')
         cuda_runtime_libs.update(find_cuda_lib_in('/usr/local/cuda/lib64'))
 
     warn_in_case_of_duplicates(cuda_runtime_libs)

cuda_install.sh

@@ -17,6 +17,7 @@ URL121=https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installer
 
 CUDA_VERSION=$1
 BASE_PATH=$2
+EXPORT_BASHRC=$3
 
 if [[ -n "$CUDA_VERSION" ]]; then
   if   [[ "$CUDA_VERSION" -eq "92" ]]; then
@@ -76,11 +77,13 @@ FILE=$(basename $URL)
 if [[ -n "$CUDA_VERSION" ]]; then
   echo $URL
   echo $FILE
-  wget $URL
-  bash $FILE --no-drm --no-man-page --override --toolkitpath=$BASE_PATH/$FOLDER/ --toolkit --silent
-  echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$BASE_PATH/$FOLDER/lib64/" >> ~/.bashrc
-  echo "export PATH=$PATH:$BASE_PATH/$FOLDER/bin/" >> ~/.bashrc
-  source ~/.bashrc
+  #wget $URL
+  #bash $FILE --no-drm --no-man-page --override --toolkitpath=$BASE_PATH/$FOLDER/ --toolkit --silent
+  if [ "$EXPORT_BASHRC" -eq "1" ]; then
+    echo "export LD_LIBRARY_PATH=\$LD_LIBRARY_PATH:$BASE_PATH/$FOLDER/lib64" >> ~/.bashrc
+    echo "export PATH=\$PATH:$BASE_PATH/$FOLDER/bin" >> ~/.bashrc
+    source ~/.bashrc
+  fi
 else
   echo ""
 fi

tests/test_cuda_setup_evaluator.py

@@ -5,95 +5,20 @@
 
 import bitsandbytes as bnb
 from bitsandbytes.cuda_setup.main import (
-    CUDA_RUNTIME_LIB,
     determine_cuda_runtime_lib_path,
     evaluate_cuda_setup,
     extract_candidate_paths,
 )
 
-"""
-'LD_LIBRARY_PATH': ':/mnt/D/titus/local/cuda-11.1/lib64/'
-'CONDA_EXE': '/mnt/D/titus/miniconda/bin/conda'
-'LESSCLOSE': '/usr/bin/lesspipe %s %s'
-'OLDPWD': '/mnt/D/titus/src'
-'CONDA_PREFIX': '/mnt/D/titus/miniconda/envs/8-bit'
-'SSH_AUTH_SOCK': '/mnt/D/titus/.ssh/ssh-agent.tim-uw.sock'
-'CONDA_PREFIX_1': '/mnt/D/titus/miniconda'
-'PWD': '/mnt/D/titus/src/8-bit'
-'HOME': '/mnt/D/titus'
-'CONDA_PYTHON_EXE': '/mnt/D/titus/miniconda/bin/python'
-'CUDA_HOME': '/mnt/D/titus/local/cuda-11.1/'
-'TMUX': '/tmp/tmux-1007/default,59286,1'
-'XDG_DATA_DIRS': '/usr/local/share:/usr/share:/var/lib/snapd/desktop'
-'SSH_TTY': '/dev/pts/0'
-'MAIL': '/var/mail/titus'
-'SHELL': '/bin/bash'
-'DBUS_SESSION_BUS_ADDRESS': 'unix:path=/run/user/1007/bus'
-'XDG_RUNTIME_DIR': '/run/user/1007'
-'PATH': '/mnt/D/titus/miniconda/envs/8-bit/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/mnt/D/titus/local/cuda-11.1/bin'
-'LESSOPEN': '| /usr/bin/lesspipe %s'
-'_': '/mnt/D/titus/miniconda/envs/8-bit/bin/python'
-# any that include 'CONDA' that are not 'CONDA_PREFIX'
 
-# we search for
-'CUDA_HOME': '/mnt/D/titus/local/cuda-11.1/'
-"""
-
-
-class InputAndExpectedOutput(NamedTuple):
-    input: str
-    output: str
-
-
-HAPPY_PATH__LD_LIB_TEST_PATHS: List[InputAndExpectedOutput] = [
-    (
-        f"some/other/dir:dir/with/{CUDA_RUNTIME_LIB}",
-        f"dir/with/{CUDA_RUNTIME_LIB}",
-    ),
-    (
-        f":some/other/dir:dir/with/{CUDA_RUNTIME_LIB}",
-        f"dir/with/{CUDA_RUNTIME_LIB}",
-    ),
-    (
-        f"some/other/dir:dir/with/{CUDA_RUNTIME_LIB}:",
-        f"dir/with/{CUDA_RUNTIME_LIB}",
-    ),
-    (
-        f"some/other/dir::dir/with/{CUDA_RUNTIME_LIB}",
-        f"dir/with/{CUDA_RUNTIME_LIB}",
-    ),
-    (
-        f"dir/with/{CUDA_RUNTIME_LIB}:some/other/dir",
-        f"dir/with/{CUDA_RUNTIME_LIB}",
-    ),
-    (
-        f"dir/with/{CUDA_RUNTIME_LIB}:other/dir/libcuda.so",
-        f"dir/with/{CUDA_RUNTIME_LIB}",
-    ),
-]
-
-
-@pytest.fixture(params=HAPPY_PATH__LD_LIB_TEST_PATHS)
-def happy_path_path_string(tmpdir, request):
-    for path in extract_candidate_paths(request.param):
-        test_dir.mkdir()
-        if CUDA_RUNTIME_LIB in path:
-            (test_input / CUDA_RUNTIME_LIB).touch()
-
-UNHAPPY_PATH__LD_LIB_TEST_PATHS = [
-    f"a/b/c/{CUDA_RUNTIME_LIB}:d/e/f/{CUDA_RUNTIME_LIB}",
-    f"a/b/c/{CUDA_RUNTIME_LIB}:d/e/f/{CUDA_RUNTIME_LIB}:g/h/j/{CUDA_RUNTIME_LIB}",
-]
-
-
-def test_full_system():
+def test_cuda_full_system():
     ## this only tests the cuda version and not compute capability
 
     # if CONDA_PREFIX exists, it has priority before all other env variables
     # but it does not contain the library directly, so we need to look at the a sub-folder
     version = ""
     if "CONDA_PREFIX" in os.environ:
-        ls_output, err = bnb.utils.execute_and_return(f'ls -l {os.environ["CONDA_PREFIX"]}/lib/libcudart.so')
+        ls_output, err = bnb.utils.execute_and_return(f'ls -l {os.environ["CONDA_PREFIX"]}/lib/libcudart.so.11.0')
         major, minor, revision = (ls_output.split(" ")[-1].replace("libcudart.so.", "").split("."))
         version = float(f"{major}.{minor}")