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Enabled BnB NF4 inference on Gaudi #20172

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Enabled BnB NF4 inference on Gaudi #20172

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12 changes: 6 additions & 6 deletions vllm/model_executor/layers/quantization/bitsandbytes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@
from vllm.model_executor.layers.quantization import QuantizationMethods
from vllm.model_executor.layers.quantization.base_config import (
QuantizationConfig)
from vllm.platforms import current_platform
from vllm.utils import direct_register_custom_op


Expand Down Expand Up @@ -384,12 +385,11 @@ def _apply_bnb_4bit_fake(


try:
direct_register_custom_op(
op_name="apply_bnb_4bit",
op_func=_apply_bnb_4bit,
mutates_args=["out"],
fake_impl=_apply_bnb_4bit_fake,
)
direct_register_custom_op(op_name="apply_bnb_4bit",
op_func=_apply_bnb_4bit,
mutates_args=["out"],
fake_impl=_apply_bnb_4bit_fake,
dispatch_key=current_platform.dispatch_key)
apply_bnb_4bit = torch.ops.vllm.apply_bnb_4bit

except AttributeError as error:
Expand Down
6 changes: 4 additions & 2 deletions vllm/model_executor/model_loader/bitsandbytes_loader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -371,10 +371,12 @@ def _unquantized_generator(self, hf_weights_files, use_safetensors,
...]

# bitsandbytes requires data in GPU
if weight_sub_tensor.is_cuda:
if (weight_sub_tensor.is_cuda
or weight_sub_tensor.device.type == "hpu"):
loaded_weight = weight_sub_tensor
else:
loaded_weight = weight_sub_tensor.cuda()
loaded_weight = weight_sub_tensor.to(
device=current_platform.device_type)

# remove the following after the issue is fixed:
# https://github.com/bitsandbytes-foundation/bitsandbytes/issues/1342
Expand Down