vllm/tests/lora/test_lora_manager.py
2025-03-02 17:34:51 -08:00

628 lines
25 KiB
Python

# SPDX-License-Identifier: Apache-2.0
import os
import pytest
import torch
from safetensors.torch import load_file
from torch import nn
from vllm.config import LoRAConfig
from vllm.lora.layers import (ColumnParallelLinearWithLoRA,
MergedColumnParallelLinearWithLoRA,
RowParallelLinearWithLoRA)
from vllm.lora.lora import LoRALayerWeights, PackedLoRALayerWeights
from vllm.lora.models import (LoRAMapping, LoRAModel, LoRAModelManager,
LRUCacheLoRAModelManager)
from vllm.lora.peft_helper import PEFTHelper
from vllm.lora.request import LoRARequest
from vllm.lora.worker_manager import (LRUCacheWorkerLoRAManager,
WorkerLoRAManager)
from vllm.platforms import current_platform
EMBEDDING_MODULES = {
"embed_tokens": "input_embeddings",
"lm_head": "output_embeddings",
}
EMBEDDING_PADDING_MODULES = ["lm_head"]
DEVICES = ([
f"cuda:{i}" for i in range(1 if torch.cuda.device_count() == 1 else 2)
] if current_platform.is_cuda_alike() else ["cpu"])
@pytest.mark.parametrize("device", DEVICES)
def test_from_lora_tensors(sql_lora_files, device):
tensors = load_file(
os.path.join(sql_lora_files, "adapter_model.safetensors"))
new_embeddings = load_file(
os.path.join(sql_lora_files, "new_embeddings.safetensors"))
peft_helper = PEFTHelper.from_local_dir(sql_lora_files,
max_position_embeddings=4096)
lora_model = LoRAModel.from_lora_tensors(
1,
tensors,
peft_helper=peft_helper,
device=device,
embeddings=new_embeddings,
embedding_modules=EMBEDDING_MODULES,
embedding_padding_modules=EMBEDDING_PADDING_MODULES)
for module_name, lora in lora_model.loras.items():
assert lora.module_name == module_name
assert lora.rank == 8
assert lora.lora_alpha == 16
assert lora.lora_a is not None
assert lora.lora_b is not None
assert lora.lora_a.device == torch.device(device)
assert lora.lora_b.device == torch.device(device)
assert (lora.lora_a.shape[1] == lora.lora_b.shape[0]
), f"{lora.lora_a.shape=}, {lora.lora_b.shape=}"
assert lora.lora_a.shape[1] == 8
embeddings_module = next(
(k for k in EMBEDDING_MODULES if k in module_name), None)
if embeddings_module:
assert torch.equal(
lora.embeddings_tensor,
new_embeddings[EMBEDDING_MODULES[embeddings_module]].to(
device=lora.embeddings_tensor.device))
else:
assert lora.embeddings_tensor is None
def create_lora(lora_id: int, model: nn.Module, sub_modules: list[str],
device: torch.device) -> LoRAModel:
loras: dict[str, LoRALayerWeights] = {}
for name in sub_modules:
w = model.get_submodule(name).weight
loras[name] = LoRALayerWeights(
name,
8,
16,
torch.rand([w.shape[1], 8], device=device),
torch.rand([8, w.shape[0]], device=device),
)
return LoRAModel(lora_id, 8, loras)
def create_packed_lora(
lora_id: int,
model: nn.Module,
module_name,
replaced_module_names,
device: torch.device,
empty_replaced_module_name=None,
) -> LoRAModel:
w = model.get_submodule(module_name).weight
loras: dict[str, LoRALayerWeights] = {}
for replaced_module_name in replaced_module_names:
if replaced_module_name == empty_replaced_module_name:
continue
loras[replaced_module_name] = LoRALayerWeights(
replaced_module_name,
8,
16,
torch.rand([w.shape[1], 8], device=device),
torch.rand([8, w.shape[0] // len(replaced_module_names)],
device=device),
)
return LoRAModel(lora_id, 8, loras)
def test_replace_submodules(dist_init, dummy_model):
model = dummy_model
manager = LoRAModelManager(
model, 1, 1, 1,
LoRAConfig(max_lora_rank=8, max_cpu_loras=8, max_loras=8),
torch.device(DEVICES[0]))
model = manager.model
assert isinstance(model.get_submodule("dense1"),
ColumnParallelLinearWithLoRA)
assert isinstance(model.get_submodule("layer1.dense1"),
ColumnParallelLinearWithLoRA)
assert isinstance(model.get_submodule("dense2"), RowParallelLinearWithLoRA)
assert isinstance(model.get_submodule("layer1.dense2"),
RowParallelLinearWithLoRA)
@pytest.mark.parametrize("device", DEVICES)
def test_lora_model_manager(dist_init, dummy_model, device):
model = dummy_model
model_lora1 = create_lora(1,
model, ["layer1.dense1", "dense2", "lm_head"],
device=device)
model_lora2 = create_lora(2,
model, ["dense1", "dense2", "lm_head"],
device=device)
model_lora3 = create_lora(3,
model, ["dense1", "dense2", "lm_head"],
device=device)
manager = LoRAModelManager(model,
2,
2,
2,
LoRAConfig(max_lora_rank=8,
max_cpu_loras=3,
max_loras=2),
device=device)
assert all(x is None for x in manager.lora_index_to_id)
assert manager.add_adapter(model_lora1)
assert manager.activate_adapter(1)
assert manager.lora_index_to_id[0] == 1
assert not manager.add_adapter(model_lora1)
assert not manager.activate_adapter(1)
assert manager.add_adapter(model_lora2)
assert manager.activate_adapter(2)
assert manager.lora_index_to_id[0] == 1
assert manager.lora_index_to_id[1] == 2
assert not manager.add_adapter(model_lora2)
assert not manager.activate_adapter(2)
assert manager.add_adapter(model_lora3)
assert manager.lora_index_to_id[0] == 1
assert manager.lora_index_to_id[1] == 2
with pytest.raises(ValueError):
assert manager.activate_adapter(3)
assert manager.lora_index_to_id[0] == 1
assert manager.lora_index_to_id[1] == 2
assert manager.remove_adapter(model_lora2.id)
assert manager.lora_index_to_id[1] is None
assert not manager.remove_adapter(model_lora2.id)
assert manager.remove_adapter(model_lora1.id)
assert not manager.remove_adapter(model_lora1.id)
assert manager.add_adapter(model_lora1)
assert manager.lora_index_to_id[0] is None
assert manager.lora_index_to_id[1] is None
assert manager.add_adapter(model_lora2)
assert manager.activate_adapter(3)
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] is None
assert manager.activate_adapter(2)
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] == 2
assert manager.device == device
assert manager.punica_wrapper.device == device
assert hasattr(manager, "supported_lora_modules")
assert sorted(manager.supported_lora_modules) == [
"dense1",
"dense2",
"lm_head",
"output",
]
@pytest.mark.parametrize("device", DEVICES)
def test_lora_lru_cache_model_manager(dist_init, dummy_model, device):
model = dummy_model
model_lora1 = create_lora(1,
model, ["layer1.dense1", "dense2", "lm_head"],
device=device)
model_lora2 = create_lora(2,
model, ["dense1", "dense2", "lm_head"],
device=device)
model_lora3 = create_lora(3,
model, ["dense1", "dense2", "lm_head"],
device=device)
manager = LRUCacheLoRAModelManager(model,
2,
2,
2,
LoRAConfig(max_lora_rank=8,
max_cpu_loras=3,
max_loras=2),
device=device)
assert all(x is None for x in manager.lora_index_to_id)
assert manager.add_adapter(model_lora1)
assert manager.activate_adapter(1)
assert manager.lora_index_to_id[0] == 1
assert not manager.add_adapter(model_lora1)
assert not manager.activate_adapter(1)
assert manager.add_adapter(model_lora2)
assert manager.activate_adapter(2)
assert manager.lora_index_to_id[0] == 1
assert manager.lora_index_to_id[1] == 2
assert not manager.add_adapter(model_lora2)
assert not manager.activate_adapter(2)
assert manager.add_adapter(model_lora3)
assert manager.lora_index_to_id[0] == 1
assert manager.lora_index_to_id[1] == 2
assert manager.activate_adapter(3)
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] == 2
assert manager.remove_adapter(model_lora2.id)
assert manager.lora_index_to_id[1] is None
assert not manager.remove_adapter(model_lora2.id)
assert manager.remove_adapter(model_lora1.id)
assert not manager.remove_adapter(model_lora1.id)
assert manager.add_adapter(model_lora1)
assert manager.activate_adapter(1)
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] == 1
assert manager.add_adapter(model_lora2)
assert manager.deactivate_adapter(3)
assert manager.lora_index_to_id[0] is None
assert manager.lora_index_to_id[1] == 1
assert manager.activate_adapter(2)
assert manager.lora_index_to_id[0] == 2
assert manager.lora_index_to_id[1] == 1
assert manager.activate_adapter(3)
assert manager.lora_index_to_id[0] == 2
assert manager.lora_index_to_id[1] == 3
assert manager.pin_adapter(2)
assert manager.lora_index_to_id[0] == 2
assert manager.lora_index_to_id[1] == 3
assert manager.activate_adapter(1)
assert manager.lora_index_to_id[0] == 2
assert manager.lora_index_to_id[1] == 1
assert manager.deactivate_adapter(2)
assert manager.lora_index_to_id[0] is None
assert manager.lora_index_to_id[1] == 1
assert manager.activate_adapter(3)
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] == 1
assert manager.pin_adapter(3)
assert manager.pin_adapter(1)
with pytest.raises(RuntimeError):
assert manager.pin_adapter(2)
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] == 1
with pytest.raises(RuntimeError):
assert manager.activate_adapter(2)
assert manager.deactivate_adapter(3)
assert manager.pin_adapter(2)
assert manager.lora_index_to_id[0] == 2
assert manager.lora_index_to_id[1] == 1
assert manager.remove_adapter(3)
with pytest.raises(ValueError):
assert manager.pin_adapter(3)
assert manager.punica_wrapper.device == device
assert manager.device == device
@pytest.mark.parametrize("device", DEVICES)
def test_lru_lora_model_manager(dist_init, dummy_model, device):
# This tests just the LRU cache functionality, everything else is
# tested in test_lora_model_manager
model = dummy_model
model_lora1 = create_lora(1,
model, ["layer1.dense1", "dense2", "lm_head"],
device=device)
model_lora2 = create_lora(2,
model, ["dense1", "dense2", "lm_head"],
device=device)
model_lora3 = create_lora(3,
model, ["dense1", "dense2", "lm_head"],
device=device)
model_lora4 = create_lora(4,
model, ["dense1", "dense2", "lm_head"],
device=device)
manager = LRUCacheLoRAModelManager(model,
2,
2,
2,
LoRAConfig(max_lora_rank=8,
max_cpu_loras=2,
max_loras=2),
device=device)
assert all(x is None for x in manager.lora_index_to_id)
# Add up to capacity
assert manager.add_adapter(model_lora1)
assert manager.add_adapter(model_lora2)
assert manager.activate_adapter(1)
assert manager.activate_adapter(2)
assert set(manager.list_adapters()) == {1, 2}
assert manager.lora_index_to_id[0] == 1
assert manager.lora_index_to_id[1] == 2
# Add over capacity
assert manager.add_adapter(model_lora3)
assert manager.add_adapter(model_lora4)
assert manager.activate_adapter(3)
assert manager.activate_adapter(4)
assert set(manager.list_adapters()) == {3, 4}
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] == 4
# Add 3 again to move it to the top and then add 2
# should return false since it's in already
assert not manager.add_adapter(model_lora3)
assert not manager.activate_adapter(3)
assert manager.add_adapter(model_lora2)
assert manager.activate_adapter(2)
assert set(manager.list_adapters()) == {3, 2}
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] == 2
# Remove manually
assert manager.remove_adapter(3)
assert not manager.remove_adapter(3)
assert set(manager.list_adapters()) == {2}
assert manager.lora_index_to_id[0] is None
assert manager.lora_index_to_id[1] == 2
assert manager.add_adapter(model_lora3)
assert manager.activate_adapter(3)
assert manager.add_adapter(model_lora4)
assert manager.activate_adapter(4)
assert set(manager.list_adapters()) == {3, 4}
assert manager.lora_index_to_id[0] == 3
assert manager.lora_index_to_id[1] == 4
assert manager.remove_oldest_adapter()
assert set(manager.list_adapters()) == {4}
assert manager.lora_index_to_id[0] is None
assert manager.lora_index_to_id[1] == 4
assert manager.remove_oldest_adapter()
assert set(manager.list_adapters()) == set()
assert all(x is None for x in manager.lora_index_to_id)
assert not manager.remove_oldest_adapter()
assert set(manager.list_adapters()) == set()
assert all(x is None for x in manager.lora_index_to_id)
# pinning
assert manager.add_adapter(model_lora3)
assert manager.activate_adapter(3)
assert manager.add_adapter(model_lora4)
assert manager.activate_adapter(4)
assert set(manager.list_adapters()) == {3, 4}
with pytest.raises(ValueError):
assert manager.pin_adapter(1)
assert manager.pin_adapter(3)
# Remove manually
assert manager.remove_adapter(3)
assert not manager.remove_adapter(3)
assert set(manager.list_adapters()) == {4}
assert manager.lora_index_to_id[0] is None
assert manager.lora_index_to_id[1] == 4
assert manager.add_adapter(model_lora1)
assert manager.pin_adapter(1)
assert manager.add_adapter(model_lora2)
assert manager.activate_adapter(2)
assert set(manager.list_adapters()) == {1, 2}
assert manager.lora_index_to_id[0] == 1
assert manager.lora_index_to_id[1] == 2
assert manager.remove_oldest_adapter()
assert set(manager.list_adapters()) == {1}
assert manager.lora_index_to_id[0] == 1
assert manager.lora_index_to_id[1] is None
with pytest.raises(RuntimeError):
assert manager.remove_oldest_adapter()
assert set(manager.list_adapters()) == {1}
assert manager.punica_wrapper.device == device
assert manager.device == device
@pytest.mark.parametrize("device", DEVICES)
def test_lru_cache_worker_adapter_manager(llama_2_7b_model_extra_embeddings,
sql_lora_files, device):
lora_config = LoRAConfig(max_lora_rank=8, max_cpu_loras=4, max_loras=4)
worker_adapter_manager = LRUCacheWorkerLoRAManager(
4, 2, llama_2_7b_model_extra_embeddings.unpadded_vocab_size -
lora_config.lora_extra_vocab_size, lora_config, device,
EMBEDDING_MODULES, EMBEDDING_PADDING_MODULES)
worker_adapter_manager.create_lora_manager(
llama_2_7b_model_extra_embeddings)
mapping = LoRAMapping([], [])
worker_adapter_manager.set_active_adapters([
LoRARequest("1", 1, sql_lora_files),
LoRARequest("2", 2, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1, 2}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 2
worker_adapter_manager.set_active_adapters([
LoRARequest("1", 1, sql_lora_files),
LoRARequest("3", 3, sql_lora_files),
LoRARequest("4", 4, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1, 2, 3, 4}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 2
assert worker_adapter_manager._adapter_manager.lora_index_to_id[2] == 3
assert worker_adapter_manager._adapter_manager.lora_index_to_id[3] == 4
worker_adapter_manager.set_active_adapters([
LoRARequest("1", 1, sql_lora_files),
LoRARequest("2", 2, sql_lora_files),
LoRARequest("5", 5, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1, 2, 4, 5}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 2
assert worker_adapter_manager._adapter_manager.lora_index_to_id[2] == 5
assert worker_adapter_manager._adapter_manager.lora_index_to_id[3] == 4
worker_adapter_manager.set_active_adapters([
LoRARequest("1", 1, sql_lora_files),
LoRARequest("1", 1, sql_lora_files),
LoRARequest("1", 1, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1, 2, 4, 5}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 2
assert worker_adapter_manager._adapter_manager.lora_index_to_id[2] == 5
assert worker_adapter_manager._adapter_manager.lora_index_to_id[3] == 4
worker_adapter_manager.set_active_adapters([
LoRARequest("6", 6, sql_lora_files),
LoRARequest("7", 7, sql_lora_files),
LoRARequest("8", 8, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1, 6, 7, 8}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 7
assert worker_adapter_manager._adapter_manager.lora_index_to_id[2] == 8
assert worker_adapter_manager._adapter_manager.lora_index_to_id[3] == 6
# Over capacity
with pytest.raises(RuntimeError):
worker_adapter_manager.set_active_adapters([
LoRARequest("10", 10, sql_lora_files),
LoRARequest("11", 11, sql_lora_files),
LoRARequest("12", 12, sql_lora_files),
LoRARequest("13", 13, sql_lora_files),
LoRARequest("14", 14, sql_lora_files)
], mapping)
assert worker_adapter_manager.device == device
assert (worker_adapter_manager._adapter_manager.punica_wrapper.device ==
device)
@pytest.mark.parametrize("device", DEVICES)
def test_worker_adapter_manager(llama_2_7b_model_extra_embeddings,
sql_lora_files, device):
# Should remove every LoRA not specified in the request.
lora_config = LoRAConfig(max_lora_rank=8, max_cpu_loras=4, max_loras=4)
worker_adapter_manager = WorkerLoRAManager(
4, 2, llama_2_7b_model_extra_embeddings.unpadded_vocab_size -
lora_config.lora_extra_vocab_size, lora_config, device,
EMBEDDING_MODULES, EMBEDDING_PADDING_MODULES)
worker_adapter_manager.create_lora_manager(
llama_2_7b_model_extra_embeddings)
mapping = LoRAMapping([], [])
worker_adapter_manager.set_active_adapters([
LoRARequest("1", 1, sql_lora_files),
LoRARequest("2", 2, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1, 2}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 2
worker_adapter_manager.set_active_adapters([
LoRARequest("1", 1, sql_lora_files),
LoRARequest("3", 3, sql_lora_files),
LoRARequest("4", 4, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1, 3, 4}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 3
assert worker_adapter_manager._adapter_manager.lora_index_to_id[2] == 4
worker_adapter_manager.set_active_adapters([
LoRARequest("1", 1, sql_lora_files),
LoRARequest("2", 2, sql_lora_files),
LoRARequest("5", 5, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1, 2, 5}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 2
assert worker_adapter_manager._adapter_manager.lora_index_to_id[2] == 5
worker_adapter_manager.set_active_adapters([
LoRARequest("1", 1, sql_lora_files),
LoRARequest("1", 1, sql_lora_files),
LoRARequest("1", 1, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {1}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 1
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] is None
assert worker_adapter_manager._adapter_manager.lora_index_to_id[2] is None
worker_adapter_manager.set_active_adapters([
LoRARequest("6", 6, sql_lora_files),
LoRARequest("7", 7, sql_lora_files),
LoRARequest("8", 8, sql_lora_files)
], mapping)
assert worker_adapter_manager.list_adapters() == {6, 7, 8}
assert worker_adapter_manager._adapter_manager.lora_index_to_id[0] == 8
assert worker_adapter_manager._adapter_manager.lora_index_to_id[1] == 6
assert worker_adapter_manager._adapter_manager.lora_index_to_id[2] == 7
# Over capacity
with pytest.raises(RuntimeError):
worker_adapter_manager.set_active_adapters([
LoRARequest("10", 10, sql_lora_files),
LoRARequest("11", 11, sql_lora_files),
LoRARequest("12", 12, sql_lora_files),
LoRARequest("13", 13, sql_lora_files),
LoRARequest("14", 14, sql_lora_files)
], mapping)
assert worker_adapter_manager.device == device
assert (worker_adapter_manager._adapter_manager.punica_wrapper.device ==
device)
@pytest.mark.parametrize("device", DEVICES)
def test_packed_loras(dist_init, dummy_model_gate_up, device):
model = dummy_model_gate_up
model_lora = create_packed_lora(
1,
model,
module_name="gate_up_proj",
replaced_module_names=["gate_proj", "up_proj"],
device=device)
model_lora1 = create_packed_lora(
2,
model,
module_name="gate_up_proj",
replaced_module_names=["gate_proj", "up_proj"],
device=device,
empty_replaced_module_name="gate_proj",
)
manager = LoRAModelManager(model,
2,
2,
2,
LoRAConfig(max_lora_rank=8,
max_cpu_loras=2,
max_loras=2),
device=device)
model = manager.model
assert isinstance(model.get_submodule("gate_up_proj"),
MergedColumnParallelLinearWithLoRA)
# Verify packed lora is correct
model_lora_clone = model_lora.clone(1)
model_lora_clone1 = model_lora1.clone(1)
assert manager.add_adapter(model_lora)
assert manager.add_adapter(model_lora1)
assert model_lora.get_lora("gate_proj") is None
assert model_lora.get_lora("up_proj") is None
assert model_lora1.get_lora("up_proj") is None
packed_lora = model_lora.get_lora("gate_up_proj")
assert packed_lora and isinstance(packed_lora, PackedLoRALayerWeights)
torch.testing.assert_close(packed_lora.lora_a[0],
model_lora_clone.get_lora("gate_proj").lora_a)
torch.testing.assert_close(packed_lora.lora_b[0],
model_lora_clone.get_lora("gate_proj").lora_b)
torch.testing.assert_close(packed_lora.lora_a[1],
model_lora_clone.get_lora("up_proj").lora_a)
torch.testing.assert_close(packed_lora.lora_b[1],
model_lora_clone.get_lora("up_proj").lora_b)
packed_lora1 = model_lora1.get_lora("gate_up_proj")
assert packed_lora1 and isinstance(packed_lora1, PackedLoRALayerWeights)
assert packed_lora1.lora_a[0] is None
assert packed_lora1.lora_b[0] is None
torch.testing.assert_close(packed_lora1.lora_a[1],
model_lora_clone1.get_lora("up_proj").lora_a)
torch.testing.assert_close(packed_lora1.lora_b[1],
model_lora_clone1.get_lora("up_proj").lora_b)