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Fix timeout when using LoRA adapters with Nemotron Super (#40916)

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Signed-off-by: Daniel Serebrenik <daserebrenik@nvidia.com>
This commit is contained in:
danisereb
2026-04-30 01:39:49 +08:00
committed by GitHub
parent 4a42aba380
commit d1a75e303d
2 changed files with 1 additions and 140 deletions
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tests/lora/test_lora_manager.py
-107
View File
@@ -943,110 +943,3 @@ def test_target_modules_match_packed_runtime_modules(
("layer1.dense2", RowParallelLinearWithLoRA),
],
)
@pytest.mark.parametrize("device", DEVICES)
def test_load_adapter_warns_on_unsupported_modules(
default_vllm_config, dist_init, dummy_model_gate_up, device, tmp_path
):
"""Test that _load_adapter warns when a LoRA adapter contains modules
not in the model's supported LoRA target modules."""
from unittest.mock import patch
import vllm.lora.worker_manager as wm_module
lora_config = LoRAConfig(
max_lora_rank=8, max_cpu_loras=4, max_loras=4, lora_dtype=DEFAULT_DTYPE
)
dummy_lora_files = f"{tmp_path}/lora_adapter"
os.makedirs(dummy_lora_files, exist_ok=True)
create_peft_lora(
dummy_model_gate_up,
save_dir=dummy_lora_files,
target_modules=["layer1.dense1", "dense2"],
lora_dtype=DEFAULT_DTYPE,
)
model_config = ModelConfig(max_model_len=16)
vllm_config = VllmConfig(model_config=model_config, lora_config=lora_config)
vllm_config.scheduler_config.max_num_seqs = 4
vllm_config.scheduler_config.max_num_batched_tokens = 2
worker_manager = WorkerLoRAManager(vllm_config, device, EMBEDDING_MODULES)
worker_manager.vocab_size = dummy_model_gate_up.unpadded_vocab_size
worker_manager.create_lora_manager(dummy_model_gate_up)
# Patch from_local_checkpoint to inject an unsupported module
original_from_checkpoint = LoRAModel.from_local_checkpoint
def patched_from_checkpoint(*args, **kwargs):
lora = original_from_checkpoint(*args, **kwargs)
lora.loras["unsupported_module"] = LoRALayerWeights(
module_name="unsupported_module",
rank=8,
lora_alpha=16,
lora_a=torch.randn(8, 10),
lora_b=torch.randn(10, 8),
)
return lora
lora_request = LoRARequest("test", 1, dummy_lora_files)
with (
patch.object(LoRAModel, "from_local_checkpoint", patched_from_checkpoint),
patch.object(wm_module.logger, "warning_once") as mock_warning,
):
worker_manager._load_adapter(lora_request)
warning_args = mock_warning.call_args_list
found = any("unsupported_module" in str(call) for call in warning_args)
assert found, (
f"Expected warning about 'unsupported_module', got: {warning_args}"
)
@pytest.mark.parametrize("device", DEVICES)
def test_load_adapter_warns_on_target_modules_restriction(
default_vllm_config, dist_init, dummy_model_gate_up, device, tmp_path
):
"""Test that _load_adapter warns when a LoRA adapter contains modules
excluded by the deployment-time target_modules restriction."""
from unittest.mock import patch
import vllm.lora.worker_manager as wm_module
# Restrict to only dense2 — adapter has dense1 which will be excluded
lora_config = LoRAConfig(
max_lora_rank=8,
max_cpu_loras=4,
max_loras=4,
lora_dtype=DEFAULT_DTYPE,
target_modules=["dense2"],
)
dummy_lora_files = f"{tmp_path}/lora_adapter"
os.makedirs(dummy_lora_files, exist_ok=True)
create_peft_lora(
dummy_model_gate_up,
save_dir=dummy_lora_files,
target_modules=["layer1.dense1", "dense2"],
lora_dtype=DEFAULT_DTYPE,
)
model_config = ModelConfig(max_model_len=16)
vllm_config = VllmConfig(model_config=model_config, lora_config=lora_config)
vllm_config.scheduler_config.max_num_seqs = 4
vllm_config.scheduler_config.max_num_batched_tokens = 2
worker_manager = WorkerLoRAManager(vllm_config, device, EMBEDDING_MODULES)
worker_manager.vocab_size = dummy_model_gate_up.unpadded_vocab_size
worker_manager.create_lora_manager(dummy_model_gate_up)
lora_request = LoRARequest("test", 1, dummy_lora_files)
with patch.object(wm_module.logger, "warning_once") as mock_warning:
worker_manager._load_adapter(lora_request)
warning_args = mock_warning.call_args_list
# dense1 is supported by the model but excluded by target_modules
found = any("target_modules" in str(call) for call in warning_args)
assert found, (
f"Expected warning about target_modules restriction, got: {warning_args}"
)
vllm/lora/worker_manager.py
+1 -33
View File
@@ -17,11 +17,7 @@ from vllm.lora.model_manager import (
)
from vllm.lora.peft_helper import PEFTHelper
from vllm.lora.request import LoRARequest
from vllm.lora.utils import (
get_adapter_absolute_path,
is_in_target_modules,
is_supported_lora_module,
)
from vllm.lora.utils import get_adapter_absolute_path
logger = init_logger(__name__)
@@ -146,34 +142,6 @@ class WorkerLoRAManager:
skip_prefixes=lora_skip_prefixes,
)
# Warn about adapter modules that will be ignored.
target_modules = self.lora_config.target_modules
expected_lora_modules_lst = list(expected_lora_modules)
for module_name in lora.loras:
if not is_supported_lora_module(module_name, expected_lora_modules_lst):
logger.warning_once(
"LoRA module '%s' in adapter '%s' is not in the "
"model's supported LoRA target modules [%s]. "
"These parameters will be ignored, which may "
"cause abnormal model behavior.",
module_name,
lora_request.lora_path,
", ".join(sorted(expected_lora_modules_lst)),
)
elif not is_in_target_modules(
module_name,
target_modules,
packed_modules_mapping,
):
logger.warning_once(
"LoRA module '%s' in adapter '%s' is not in the "
"deployment-time target_modules restriction [%s]."
" These parameters will be ignored.",
module_name,
lora_request.lora_path,
", ".join(sorted(target_modules)),
)
except FileNotFoundError as e:
# FileNotFoundError should be raised if both
# - No adapter found to download from huggingface (or in