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57 changes: 26 additions & 31 deletions examples/offline_inference/lora_with_quantization_inference.py
Original file line number Diff line number Diff line change
Expand Up @@ -75,43 +75,38 @@ def initialize_engine(model: str, quantization: str,
lora_repo: Optional[str]) -> LLMEngine:
"""Initialize the LLMEngine."""

if quantization == "bitsandbytes":
# QLoRA (https://arxiv.org/abs/2305.14314) is a quantization technique.
# It quantizes the model when loading, with some config info from the
# LoRA adapter repo. So need to set the parameter of load_format and
# qlora_adapter_name_or_path as below.
engine_args = EngineArgs(model=model,
quantization=quantization,
qlora_adapter_name_or_path=lora_repo,
enable_lora=True,
max_lora_rank=64)
else:
engine_args = EngineArgs(model=model,
quantization=quantization,
enable_lora=True,
max_loras=4)
engine_args = EngineArgs(model=model,
quantization=quantization,
enable_lora=True,
max_lora_rank=64,
max_loras=4)
return LLMEngine.from_engine_args(engine_args)


def main():
"""Main function that sets up and runs the prompt processing."""

test_configs = [{
"name": "qlora_inference_example",
'model': "huggyllama/llama-7b",
'quantization': "bitsandbytes",
'lora_repo': 'timdettmers/qlora-flan-7b'
}, {
"name": "AWQ_inference_with_lora_example",
'model': 'TheBloke/TinyLlama-1.1B-Chat-v0.3-AWQ',
'quantization': "awq",
'lora_repo': 'jashing/tinyllama-colorist-lora'
}, {
"name": "GPTQ_inference_with_lora_example",
'model': 'TheBloke/TinyLlama-1.1B-Chat-v0.3-GPTQ',
'quantization': "gptq",
'lora_repo': 'jashing/tinyllama-colorist-lora'
}]
test_configs = [
# QLoRA (https://arxiv.org/abs/2305.14314)
{
"name": "qlora_inference_example",
'model': "huggyllama/llama-7b",
'quantization': "bitsandbytes",
'lora_repo': 'timdettmers/qlora-flan-7b'
},
{
"name": "AWQ_inference_with_lora_example",
'model': 'TheBloke/TinyLlama-1.1B-Chat-v0.3-AWQ',
'quantization': "awq",
'lora_repo': 'jashing/tinyllama-colorist-lora'
},
{
"name": "GPTQ_inference_with_lora_example",
'model': 'TheBloke/TinyLlama-1.1B-Chat-v0.3-GPTQ',
'quantization': "gptq",
'lora_repo': 'jashing/tinyllama-colorist-lora'
}
]

for test_config in test_configs:
print(
Expand Down
33 changes: 16 additions & 17 deletions vllm/engine/arg_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@
import json
import re
import threading
import warnings
from dataclasses import MISSING, dataclass, fields
from itertools import permutations
from typing import (Any, Callable, Dict, List, Literal, Optional, Type,
Expand Down Expand Up @@ -394,7 +395,13 @@ def __post_init__(self):
if isinstance(self.compilation_config, (int, dict)):
self.compilation_config = CompilationConfig.from_cli(
str(self.compilation_config))

if self.qlora_adapter_name_or_path is not None:
warnings.warn(
"The `qlora_adapter_name_or_path` is deprecated "
"and will be removed in v0.10.0. ",
DeprecationWarning,
stacklevel=2,
)
# Setup plugins
from vllm.plugins import load_general_plugins
load_general_plugins()
Expand Down Expand Up @@ -504,10 +511,13 @@ def add_cli_args(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
**load_kwargs["ignore_patterns"])
load_group.add_argument("--use-tqdm-on-load",
**load_kwargs["use_tqdm_on_load"])
load_group.add_argument('--qlora-adapter-name-or-path',
type=str,
default=None,
help='Name or path of the QLoRA adapter.')
load_group.add_argument(
"--qlora-adapter-name-or-path",
type=str,
default=None,
help="The `--qlora-adapter-name-or-path` has no effect, do not set"
" it, and it will be removed in v0.10.0.",
)
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You could also add deprecated=True here (you'd probably need to merge from main though)

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Done

load_group.add_argument('--pt-load-map-location',
**load_kwargs["pt_load_map_location"])

Expand All @@ -533,7 +543,7 @@ def add_cli_args(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
action=argparse.BooleanOptionalAction,
help="[DEPRECATED] The `--enable-reasoning` flag is deprecated as "
"of v0.8.6. Use `--reasoning-parser` to specify the reasoning "
"parser backend insteadThis flag (`--enable-reasoning`) will be "
"parser backend instead. This flag (`--enable-reasoning`) will be "
"removed in v0.10.0. When `--reasoning-parser` is specified, "
"reasoning mode is automatically enabled.")
guided_decoding_group.add_argument(
Expand Down Expand Up @@ -895,12 +905,6 @@ def create_model_config(self) -> ModelConfig:

def create_load_config(self) -> LoadConfig:

if(self.qlora_adapter_name_or_path is not None) and \
self.quantization != "bitsandbytes":
raise ValueError(
"QLoRA adapter only support "
f"'bitsandbytes' quantization, but got {self.quantization}")

if self.quantization == "bitsandbytes":
self.load_format = "bitsandbytes"

Expand Down Expand Up @@ -1097,11 +1101,6 @@ def create_engine_config(
max_cpu_loras=self.max_cpu_loras if self.max_cpu_loras
and self.max_cpu_loras > 0 else None) if self.enable_lora else None

if self.qlora_adapter_name_or_path is not None and \
self.qlora_adapter_name_or_path != "":
self.model_loader_extra_config[
"qlora_adapter_name_or_path"] = self.qlora_adapter_name_or_path

# bitsandbytes pre-quantized model need a specific model loader
if model_config.quantization == "bitsandbytes":
self.quantization = self.load_format = "bitsandbytes"
Expand Down
11 changes: 1 addition & 10 deletions vllm/model_executor/model_loader/weight_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -162,17 +162,8 @@ def get_quant_config(model_config: ModelConfig,
None)
if hf_quant_config is not None:
return quant_cls.from_config(hf_quant_config)
# In case of bitsandbytes/QLoRA, get quant config from the adapter model.
if model_config.quantization == "bitsandbytes":
if (not load_config.model_loader_extra_config
or "qlora_adapter_name_or_path"
not in load_config.model_loader_extra_config):
return quant_cls.from_config({"adapter_name_or_path": ""})
model_name_or_path = load_config.model_loader_extra_config[
"qlora_adapter_name_or_path"]

else:
model_name_or_path = model_config.model
model_name_or_path = model_config.model
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Is this variable necessary at all now? We access the other attributes from model_config directly everywhere else in this method.

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Done

is_local = os.path.isdir(model_name_or_path)
if not is_local:
# Download the config files.
Expand Down