biondizzle/vllm
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

Convert formatting to use ruff instead of yapf + isort (#26247)

Browse Source 
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
Download Patch File Download Diff File Expand all files Collapse all files

47
vllm/lora/peft_helper.py
View File

@@ -18,9 +18,9 @@ logger = init_logger(__name__)
@dataclass
class PEFTHelper:
"""
"""
A helper class for PEFT configurations, specifically designed for LoRA.
This class handles configuration validation, compatibility checks for
This class handles configuration validation, compatibility checks for
various LoRA implementations.
"""
@@ -71,37 +71,38 @@ class PEFTHelper:
# Identify any missing required fields
missing_fields = required_fields - set(config_dict.keys())
if missing_fields:
raise ValueError(
f"Missing required configuration fields: {missing_fields}")
raise ValueError(f"Missing required configuration fields: {missing_fields}")
# Filter out fields that aren't defined in the class
filtered_dict = {
k: v
for k, v in config_dict.items() if k in class_fields
}
filtered_dict = {k: v for k, v in config_dict.items() if k in class_fields}
return cls(**filtered_dict)
@classmethod
def from_local_dir(
cls,
lora_path: str,
max_position_embeddings: Optional[int],
tensorizer_config_dict: Optional[dict] = None) -> "PEFTHelper":
cls,
lora_path: str,
max_position_embeddings: Optional[int],
tensorizer_config_dict: Optional[dict] = None,
) -> "PEFTHelper":
lora_config_path = os.path.join(lora_path, "adapter_config.json")
if tensorizer_config_dict:
tensorizer_config = TensorizerConfig(**tensorizer_config_dict)
tensorizer_args = tensorizer_config._construct_tensorizer_args()
from tensorizer.stream_io import open_stream
lora_config_path = os.path.join(tensorizer_config.tensorizer_dir,
"adapter_config.json")
with open_stream(lora_config_path,
mode="rb",
**tensorizer_args.stream_kwargs) as f:
lora_config_path = os.path.join(
tensorizer_config.tensorizer_dir, "adapter_config.json"
)
with open_stream(
lora_config_path, mode="rb", **tensorizer_args.stream_kwargs
) as f:
config = json.load(f)
logger.info("Successfully deserialized LoRA config from %s",
tensorizer_config.tensorizer_dir)
logger.info(
"Successfully deserialized LoRA config from %s",
tensorizer_config.tensorizer_dir,
)
else:
with open(lora_config_path) as f:
@@ -112,16 +113,16 @@ class PEFTHelper:
def validate_legal(self, lora_config: LoRAConfig) -> None:
"""
Validates the LoRA configuration settings against application
Validates the LoRA configuration settings against application
constraints and requirements.
"""
error_msg = self._validate_features()
if self.r > lora_config.max_lora_rank:
error_msg.append(
f"LoRA rank {self.r} is greater than max_lora_rank"
f" {lora_config.max_lora_rank}.")
f" {lora_config.max_lora_rank}."
)
if self.bias != "none" and not lora_config.bias_enabled:
error_msg.append(
"Adapter bias cannot be used without bias_enabled.")
error_msg.append("Adapter bias cannot be used without bias_enabled.")
if error_msg:
raise ValueError(f"{' '.join(error_msg)}")