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__init__.py
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# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import importlib
import sys
import torch
from . import _ops, research, utils
from .autograd._functions import (
MatmulLtState,
matmul,
matmul_4bit,
)
from .backends.cpu import ops as cpu_ops
from .backends.default import ops as default_ops
from .nn import modules
from .optim import adam
# This is a signal for integrations with transformers/diffusers.
# Eventually we may remove this but it is currently required for compatibility.
features = {"multi_backend"}
supported_torch_devices = {
"cpu",
"cuda", # NVIDIA/AMD GPU
"xpu", # Intel GPU
"hpu", # Intel Gaudi
"npu", # Ascend NPU
"mps", # Apple Silicon
}
if torch.cuda.is_available():
from .backends.cuda import ops as cuda_ops
if hasattr(torch, "xpu") and torch.xpu.is_available():
from .backends.xpu import ops as xpu_ops
if importlib.util.find_spec("habana_frameworks") and importlib.util.find_spec("habana_frameworks.torch"):
# In case not automatically imported
import habana_frameworks.torch
if hasattr(torch, "hpu") and torch.hpu.is_available():
from .backends.hpu import ops as hpu_ops
def _import_backends():
"""
Discover and autoload all available backends installed as separate packages.
Packages with an entrypoint for "bitsandbytes.backends" will be loaded.
Inspired by PyTorch implementation: https://pytorch.org/tutorials/prototype/python_extension_autoload.html
"""
from importlib.metadata import entry_points
extensions = entry_points(group="bitsandbytes.backends")
for ext in extensions:
try:
entry = ext.load()
entry()
except Exception as e:
raise RuntimeError(f"bitsandbytes: failed to load backend {ext.name}: {e}") from e
_import_backends()
__pdoc__ = {
"libbitsandbytes": False,
"optim.optimizer.Optimizer8bit": False,
"optim.optimizer.MockArgs": False,
}
__version__ = "0.48.3.dev0"