diff --git a/.github/workflows/python-package.yml b/.github/workflows/python-package.yml
index 91e6d82a6..d2da82501 100644
--- a/.github/workflows/python-package.yml
+++ b/.github/workflows/python-package.yml
@@ -116,10 +116,23 @@ jobs:
uses: docker/setup-qemu-action@v2
- name: Clean up disk space
run: |
- sudo rm -rf /usr/share/dotnet
- sudo rm -rf /opt/ghc
- sudo rm -rf "/usr/local/share/boost"
- sudo rm -rf "$AGENT_TOOLSDIRECTORY"
+ sudo rm -rf \
+ /usr/share/dotnet \
+ /opt/ghc \
+ "/usr/local/share/boost" \
+ "$AGENT_TOOLSDIRECTORY" \
+ /opt/hostedtoolcache \
+ /opt/google/chrome \
+ /opt/microsoft/msedge \
+ /opt/microsoft/powershell \
+ /opt/pipx \
+ /usr/lib/mono \
+ /usr/local/julia* \
+ /usr/local/lib/android \
+ /usr/local/lib/node_modules \
+ /usr/local/share/chromium \
+ /usr/local/share/powershell \
+ /usr/share/swift
- name: Build C++
run: bash .github/scripts/build-rocm.sh
env:
diff --git a/bitsandbytes/cextension.py b/bitsandbytes/cextension.py
index 6c18275c6..cc5d8deff 100644
--- a/bitsandbytes/cextension.py
+++ b/bitsandbytes/cextension.py
@@ -99,7 +99,7 @@ def get_native_library() -> BNBNativeLibrary:
if cuda_binary_path.exists():
binary_path = cuda_binary_path
else:
- logger.warning("Could not find the bitsandbytes CUDA binary at %r", cuda_binary_path)
+ logger.warning("Could not find the bitsandbytes %s binary at %r", BNB_BACKEND, cuda_binary_path)
logger.debug(f"Loading bitsandbytes native library from: {binary_path}")
dll = ct.cdll.LoadLibrary(str(binary_path))
@@ -116,21 +116,24 @@ def get_native_library() -> BNBNativeLibrary:
hip_major, hip_minor = map(int, torch.version.hip.split(".")[0:2])
HIP_ENVIRONMENT, BNB_HIP_VERSION = True, hip_major * 100 + hip_minor
BNB_HIP_VERSION_SHORT = f"{hip_major}{hip_minor}"
+ BNB_BACKEND = "ROCm"
else:
HIP_ENVIRONMENT, BNB_HIP_VERSION = False, 0
BNB_HIP_VERSION_SHORT = ""
+ BNB_BACKEND = "CUDA"
+
lib = get_native_library()
except Exception as e:
lib = None
logger.error(f"Could not load bitsandbytes native library: {e}", exc_info=True)
if torch.cuda.is_available():
logger.warning(
- """
-CUDA Setup failed despite CUDA being available. Please run the following command to get more information:
+ f"""
+{BNB_BACKEND} Setup failed despite {BNB_BACKEND} being available. Please run the following command to get more information:
python -m bitsandbytes
-Inspect the output of the command and see if you can locate CUDA libraries. You might need to add them
+Inspect the output of the command and see if you can locate {BNB_BACKEND} libraries. You might need to add them
to your LD_LIBRARY_PATH. If you suspect a bug, please take the information from python -m bitsandbytes
and open an issue at: https://github.com/TimDettmers/bitsandbytes/issues
""",
diff --git a/bitsandbytes/diagnostics/cuda.py b/bitsandbytes/diagnostics/cuda.py
index 8974c6400..014b753a9 100644
--- a/bitsandbytes/diagnostics/cuda.py
+++ b/bitsandbytes/diagnostics/cuda.py
@@ -5,7 +5,7 @@
import torch
-from bitsandbytes.cextension import get_cuda_bnb_library_path
+from bitsandbytes.cextension import HIP_ENVIRONMENT, get_cuda_bnb_library_path
from bitsandbytes.consts import NONPYTORCH_DOC_URL
from bitsandbytes.cuda_specs import CUDASpecs
from bitsandbytes.diagnostics.utils import print_dedented
@@ -32,15 +32,20 @@
"_", # current Python interpreter
}
-CUDA_RUNTIME_LIB_PATTERNS = (
- "cudart64*.dll", # Windows
- "libcudart*.so*", # libcudart.so, libcudart.so.11.0, libcudart.so.12.0, libcudart.so.12.1, libcudart.so.12.2 etc.
- "nvcuda*.dll", # Windows
-)
-
logger = logging.getLogger(__name__)
+def get_runtime_lib_patterns() -> tuple:
+ if HIP_ENVIRONMENT:
+ return ("libamdhip64.so*",)
+ else:
+ return (
+ "cudart64*.dll", # Windows
+ "libcudart*.so*", # libcudart.so, libcudart.so.11.0, libcudart.so.12.0, libcudart.so.12.1, libcudart.so.12.2 etc.
+ "nvcuda*.dll", # Windows
+ )
+
+
def find_cuda_libraries_in_path_list(paths_list_candidate: str) -> Iterable[Path]:
for dir_string in paths_list_candidate.split(os.pathsep):
if not dir_string:
@@ -55,9 +60,9 @@ def find_cuda_libraries_in_path_list(paths_list_candidate: str) -> Iterable[Path
continue
except OSError: # Assume an esoteric error trying to poke at the directory
pass
- for lib_pattern in CUDA_RUNTIME_LIB_PATTERNS:
+ for lib_pattern in get_runtime_lib_patterns():
for pth in dir.glob(lib_pattern):
- if pth.is_file():
+ if pth.is_file() and not pth.is_symlink():
yield pth
except (OSError, PermissionError):
pass
@@ -104,7 +109,7 @@ def find_cudart_libraries() -> Iterator[Path]:
yield from find_cuda_libraries_in_path_list(value)
-def print_cuda_diagnostics(cuda_specs: CUDASpecs) -> None:
+def _print_cuda_diagnostics(cuda_specs: CUDASpecs) -> None:
print(
f"PyTorch settings found: CUDA_VERSION={cuda_specs.cuda_version_string}, "
f"Highest Compute Capability: {cuda_specs.highest_compute_capability}.",
@@ -149,10 +154,40 @@ def print_cuda_diagnostics(cuda_specs: CUDASpecs) -> None:
# (2) Multiple CUDA versions installed
-def print_cuda_runtime_diagnostics() -> None:
+def _print_hip_diagnostics(cuda_specs: CUDASpecs) -> None:
+ print(f"PyTorch settings found: ROCM_VERSION={cuda_specs.cuda_version_string}")
+
+ binary_path = get_cuda_bnb_library_path(cuda_specs)
+ if not binary_path.exists():
+ print_dedented(
+ f"""
+ Library not found: {binary_path}.
+ Maybe you need to compile it from source? If you compiled from source, check that ROCM_VERSION
+ in PyTorch Settings matches your ROCm install. If not, reinstall PyTorch for your ROCm version
+ and rebuild bitsandbytes.
+ """,
+ )
+
+ hip_major, hip_minor = cuda_specs.cuda_version_tuple
+ if (hip_major, hip_minor) < (6, 1):
+ print_dedented(
+ """
+ WARNING: bitsandbytes is fully supported only from ROCm 6.1.
+ """,
+ )
+
+
+def print_diagnostics(cuda_specs: CUDASpecs) -> None:
+ if HIP_ENVIRONMENT:
+ _print_hip_diagnostics(cuda_specs)
+ else:
+ _print_cuda_diagnostics(cuda_specs)
+
+
+def _print_cuda_runtime_diagnostics() -> None:
cudart_paths = list(find_cudart_libraries())
if not cudart_paths:
- print("CUDA SETUP: WARNING! CUDA runtime files not found in any environmental path.")
+ print("WARNING! CUDA runtime files not found in any environmental path.")
elif len(cudart_paths) > 1:
print_dedented(
f"""
@@ -174,3 +209,33 @@ def print_cuda_runtime_diagnostics() -> None:
)
for pth in cudart_paths:
print(f"* Found CUDA runtime at: {pth}")
+
+
+def _print_hip_runtime_diagnostics() -> None:
+ cudart_paths = list(find_cudart_libraries())
+ if not cudart_paths:
+ print("WARNING! ROCm runtime files not found in any environmental path.")
+ elif len(cudart_paths) > 1:
+ print_dedented(
+ f"""
+ Found duplicate ROCm runtime files (see below).
+
+ We select the PyTorch default ROCm runtime, which is {torch.version.hip},
+ but this might mismatch with the ROCm version that is needed for bitsandbytes.
+
+ To resolve it, install PyTorch built for the ROCm version you want to use
+
+ and set LD_LIBRARY_PATH to your ROCm install path, e.g.
+ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/rocm-6.1.2/lib,
+ """,
+ )
+
+ for pth in cudart_paths:
+ print(f"* Found ROCm runtime at: {pth}")
+
+
+def print_runtime_diagnostics() -> None:
+ if HIP_ENVIRONMENT:
+ _print_hip_runtime_diagnostics()
+ else:
+ _print_cuda_runtime_diagnostics()
diff --git a/bitsandbytes/diagnostics/main.py b/bitsandbytes/diagnostics/main.py
index 1ce096f69..8dc43ed2a 100644
--- a/bitsandbytes/diagnostics/main.py
+++ b/bitsandbytes/diagnostics/main.py
@@ -3,11 +3,12 @@
import torch
+from bitsandbytes.cextension import BNB_BACKEND, HIP_ENVIRONMENT
from bitsandbytes.consts import PACKAGE_GITHUB_URL
from bitsandbytes.cuda_specs import get_cuda_specs
from bitsandbytes.diagnostics.cuda import (
- print_cuda_diagnostics,
- print_cuda_runtime_diagnostics,
+ print_diagnostics,
+ print_runtime_diagnostics,
)
from bitsandbytes.diagnostics.utils import print_dedented, print_header
@@ -16,12 +17,13 @@ def sanity_check():
from bitsandbytes.cextension import lib
if lib is None:
+ compute_backend = "cuda" if not HIP_ENVIRONMENT else "hip"
print_dedented(
- """
+ f"""
Couldn't load the bitsandbytes library, likely due to missing binaries.
Please ensure bitsandbytes is properly installed.
- For source installations, compile the binaries with `cmake -DCOMPUTE_BACKEND=cuda -S .`.
+ For source installations, compile the binaries with `cmake -DCOMPUTE_BACKEND={compute_backend} -S .`.
See the documentation for more details if needed.
Trying a simple check anyway, but this will likely fail...
@@ -49,19 +51,24 @@ def main():
print_header("OTHER")
cuda_specs = get_cuda_specs()
- print("CUDA specs:", cuda_specs)
+ if HIP_ENVIRONMENT:
+ rocm_specs = f" rocm_version_string='{cuda_specs.cuda_version_string}',"
+ rocm_specs += f" rocm_version_tuple={cuda_specs.cuda_version_tuple}"
+ print(f"{BNB_BACKEND} specs:{rocm_specs}")
+ else:
+ print(f"{BNB_BACKEND} specs:{cuda_specs}")
if not torch.cuda.is_available():
- print("Torch says CUDA is not available. Possible reasons:")
- print("1. CUDA driver not installed")
- print("2. CUDA not installed")
- print("3. You have multiple conflicting CUDA libraries")
+ print(f"Torch says {BNB_BACKEND} is not available. Possible reasons:")
+ print(f"1. {BNB_BACKEND} driver not installed")
+ print(f"2. {BNB_BACKEND} not installed")
+ print(f"3. You have multiple conflicting {BNB_BACKEND} libraries")
if cuda_specs:
- print_cuda_diagnostics(cuda_specs)
- print_cuda_runtime_diagnostics()
+ print_diagnostics(cuda_specs)
+ print_runtime_diagnostics()
print_header("")
print_header("DEBUG INFO END")
print_header("")
- print("Checking that the library is importable and CUDA is callable...")
+ print(f"Checking that the library is importable and {BNB_BACKEND} is callable...")
try:
sanity_check()
print("SUCCESS!")
diff --git a/csrc/ops.hip b/csrc/ops.hip
index 157e84629..4fdc3cbfa 100644
--- a/csrc/ops.hip
+++ b/csrc/ops.hip
@@ -576,6 +576,7 @@ template <int FORMATB, int DTYPE_OUT, int SCALE_ROWS> int igemmlt(hipblasLtHandl
if (returnedAlgoCount == 0)
{
has_error = 1;
+ fprintf(stderr, "Error: Matmul Algo Heuristic didn't return algorithms\n");
}
else
{
@@ -614,18 +615,25 @@ template <int FORMATB, int DTYPE_OUT, int SCALE_ROWS> int igemmlt(hipblasLtHandl
heuristicResult,
&returnedAlgoCount));
- if(!SCALE_ROWS)
+ if (returnedAlgoCount == 0)
{
- float alpha = 1.0f, beta = 0.0f;
-
- has_error |= checkHipblasStatus(hipblasLtMatmul(ltHandle, matmulDesc,&alpha, A, Adesc, B, Bdesc, &beta, (int8_t*)C, Cdesc, (int8_t*)C, Cdesc, &heuristicResult[0].algo, nullptr, 0, 0));
+ has_error = 1;
+ fprintf(stderr, "Error: Matmul Algo Heuristic didn't return algorithms\n");
}
else
{
- //has_error |= checkHipblasStatus(hipblasLtMatmulDescSetAttribute(matmulDesc, hipblasLt_MATMUL_DESC_POINTER_MODE, &alphaVec, sizeof(alphaVec)));
- float beta = 0.0f;
-
- has_error |= checkHipblasStatus(hipblasLtMatmul(ltHandle, matmulDesc, row_scale, A, Adesc, B, Bdesc, &beta, (int8_t*)C, Cdesc, (int8_t*)C, Cdesc, &heuristicResult[0].algo, nullptr, 0, 0));
+ if(!SCALE_ROWS)
+ {
+ float alpha = 1.0f, beta = 0.0f;
+
+ has_error |= checkHipblasStatus(hipblasLtMatmul(ltHandle, matmulDesc,&alpha, A, Adesc, B, Bdesc, &beta, (int8_t*)C, Cdesc, (int8_t*)C, Cdesc, &heuristicResult[0].algo, nullptr, 0, 0));
+ }
+ else
+ {
+ float beta = 0.0f;
+
+ has_error |= checkHipblasStatus(hipblasLtMatmul(ltHandle, matmulDesc, row_scale, A, Adesc, B, Bdesc, &beta, (int8_t*)C, Cdesc, (int8_t*)C, Cdesc, &heuristicResult[0].algo, nullptr, 0, 0));
+ }
}
}
@@ -635,7 +643,7 @@ template <int FORMATB, int DTYPE_OUT, int SCALE_ROWS> int igemmlt(hipblasLtHandl
if (Adesc) has_error |= checkHipblasStatus(hipblasLtMatrixLayoutDestroy(Adesc));
if (matmulDesc) has_error |= checkHipblasStatus(hipblasLtMatmulDescDestroy(matmulDesc));
if(has_error == 1)
- printf("error detected");
+ fprintf(stderr, "error detected\n");
return has_error;
#endif // NO_HIPBLASLT