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fix bug when using gptq model on xpu device

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Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
This commit is contained in:
Liu, Kaixuan 2025-07-01 14:23:10 -04:00
parent dbc98328da
commit dcb694c6c3
1 changed files with 14 additions and 2 deletions
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16
src/transformers/quantizers/quantizer_gptq.py
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@ -22,7 +22,14 @@ from .base import HfQuantizer
if TYPE_CHECKING: if TYPE_CHECKING:
from ..modeling_utils import PreTrainedModel from ..modeling_utils import PreTrainedModel
from ..utils import is_auto_gptq_available, is_gptqmodel_available, is_optimum_available, is_torch_available, logging from ..utils import (
is_auto_gptq_available,
is_gptqmodel_available,
is_optimum_available,
is_torch_available,
is_torch_xpu_available,
logging,
)
from ..utils.quantization_config import GPTQConfig, QuantizationConfigMixin from ..utils.quantization_config import GPTQConfig, QuantizationConfigMixin
@ -89,7 +96,12 @@ class GptqHfQuantizer(HfQuantizer):
def update_device_map(self, device_map): def update_device_map(self, device_map):
if device_map is None: if device_map is None:
device_map = {"": torch.device("cpu")} if torch.cuda.is_available():
device_map = {"": torch.cuda.current_device()}
elif is_torch_xpu_available():
device_map = {"": torch.xpu.current_device()}
else:
device_map = {"": "cpu"}
# Only with auto-gptq do not support CPU, we should move the model to cuda if available. # Only with auto-gptq do not support CPU, we should move the model to cuda if available.
if not is_gptqmodel_available() and device_map in ("cpu", {"": torch.device("cpu")}): if not is_gptqmodel_available() and device_map in ("cpu", {"": torch.device("cpu")}):
device_map == {"": 0} device_map == {"": 0}