Enhanced error handling in CUDA SETUP failures.

CHANGELOG.md

@@ -67,3 +67,26 @@ Features:
 
 Deprecated:
  - Pre-compiled release for CUDA 9.2, 10.0, 10.2 no longer available
+
+### 0.31.0
+
+#### 8-bit Inference and Packaging Update
+
+Features:
+ - added direct outlier extraction. This enables outlier extraction without fp16 weights without performance degradation.
+ - Added automatic CUDA SETUP procedure and packaging all binaries into a single bitsandbytes package.
+
+### 0.32.0
+
+#### 8-bit Inference Performance Enhancements
+
+We added performance enhancements for small models. This makes small models about 2x faster for LLM.int8() inference.
+
+Features:
+ - Int32 dequantization now supports fused biases.
+ - Linear8bitLt now uses a fused bias implementation.
+ - Change `.data.storage().data_ptr()` to `.data.data_ptr()` to enhance inference performance.
+
+Bug fixes:
+ - Now throws and error if LLM.int8() is used on a GPU that is not supported.
+ - Enhances error messaging if CUDA SETUP fails.

bitsandbytes/cextension.py

@@ -17,12 +17,17 @@ class CUDALibrary_Singleton(object):
         binary_path = package_dir / binary_name
 
         if not binary_path.exists():
-            print(f"CUDA_SETUP: TODO: compile library for specific version: {binary_name}")
+            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}...")
-            self.lib = ct.cdll.LoadLibrary(package_dir / legacy_binary_name)
+            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)
         else:
-            print(f"CUDA_SETUP: Loading binary {binary_path}...")
+            print(f"CUDA SETUP: Loading binary {binary_path}...")
             self.lib = ct.cdll.LoadLibrary(binary_path)
 
     @classmethod

bitsandbytes/cuda_setup/main.py

@@ -46,7 +46,7 @@ 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!')
+       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!!')
 
     return f'{major}{minor}'
 
@@ -57,7 +57,7 @@ def get_cuda_lib_handle():
         cuda = ctypes.CDLL("libcuda.so")
     except OSError:
         # TODO: shouldn't we error or at least warn here?
-        print('ERROR: libcuda.so not found!')
+        raise Exception('CUDA SETUP: ERROR! 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))
 
@@ -115,7 +115,8 @@ def get_compute_capability(cuda):
 def evaluate_cuda_setup():
     print('')
     print('='*35 + 'BUG REPORT' + '='*35)
-    print('Welcome to bitsandbytes. For bug reports, please use this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link')
+    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"
     cudart_path = determine_cuda_runtime_lib_path()
@@ -125,7 +126,7 @@ def evaluate_cuda_setup():
         )
         return binary_name
 
-    print(f"CUDA SETUP: CUDA path found: {cudart_path}")
+    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}")
@@ -147,7 +148,7 @@ 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}')
+    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"

csrc/ops.cu

@@ -371,6 +371,9 @@ template void transform<int32_t, COL32, ROW, false, 32>(cublasLtHandle_t ltHandl
 template <int FORMATB, int DTYPE_OUT, int SCALE_ROWS> int igemmlt(cublasLtHandle_t ltHandle, int m, int n, int k, const int8_t *A, const int8_t *B, void *C, float *row_scale, int lda, int ldb, int ldc) 
 {
 #ifdef NO_CUBLASLT
+  printf("ERROR: Your GPU does not support Int8 Matmul!");
+  assert(false);
+
 	return 0;
 #else
     int has_error = 0;

setup.py

@@ -18,7 +18,7 @@ def read(fname):
 
 setup(
     name=f"bitsandbytes",
-    version=f"0.31.8",
+    version=f"0.32.0",
     author="Tim Dettmers",
     author_email="dettmers@cs.washington.edu",
     description="8-bit optimizers and matrix multiplication routines.",