[Core] Allow specifying custom Executor (#6557)

This commit is contained in:
Antoni Baum
2024-07-19 18:25:06 -07:00
committed by GitHub
parent 2e26564259
commit 7bd82002ae
22 changed files with 310 additions and 92 deletions

View File

@@ -564,6 +564,10 @@ def get_tokenizer_pool_config(tokenizer_group_type):
return TokenizerPoolConfig(pool_size=1,
pool_type="ray",
extra_config={})
if isinstance(tokenizer_group_type, type):
return TokenizerPoolConfig(pool_size=1,
pool_type=tokenizer_group_type,
extra_config={})
raise ValueError(f"Unknown tokenizer_group_type: {tokenizer_group_type}")

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@@ -0,0 +1,91 @@
import asyncio
import os
import pytest
from vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs
from vllm.engine.async_llm_engine import AsyncLLMEngine
from vllm.engine.llm_engine import LLMEngine
from vllm.executor.gpu_executor import GPUExecutor, GPUExecutorAsync
from vllm.sampling_params import SamplingParams
class Mock:
...
class CustomGPUExecutor(GPUExecutor):
def execute_model(self, *args, **kwargs):
# Drop marker to show that this was ran
with open(".marker", "w"):
...
return super().execute_model(*args, **kwargs)
class CustomGPUExecutorAsync(GPUExecutorAsync):
async def execute_model_async(self, *args, **kwargs):
with open(".marker", "w"):
...
return await super().execute_model_async(*args, **kwargs)
@pytest.mark.parametrize("model", ["facebook/opt-125m"])
def test_custom_executor_type_checking(model):
with pytest.raises(ValueError):
engine_args = EngineArgs(model=model,
distributed_executor_backend=Mock)
LLMEngine.from_engine_args(engine_args)
with pytest.raises(ValueError):
engine_args = AsyncEngineArgs(model=model,
distributed_executor_backend=Mock)
AsyncLLMEngine.from_engine_args(engine_args)
with pytest.raises(TypeError):
engine_args = AsyncEngineArgs(
model=model, distributed_executor_backend=CustomGPUExecutor)
AsyncLLMEngine.from_engine_args(engine_args)
@pytest.mark.parametrize("model", ["facebook/opt-125m"])
def test_custom_executor(model, tmpdir):
cwd = os.path.abspath(".")
os.chdir(tmpdir)
try:
assert not os.path.exists(".marker")
engine_args = EngineArgs(
model=model, distributed_executor_backend=CustomGPUExecutor)
engine = LLMEngine.from_engine_args(engine_args)
sampling_params = SamplingParams(max_tokens=1)
engine.add_request("0", "foo", sampling_params)
engine.step()
assert os.path.exists(".marker")
finally:
os.chdir(cwd)
@pytest.mark.parametrize("model", ["facebook/opt-125m"])
def test_custom_executor_async(model, tmpdir):
cwd = os.path.abspath(".")
os.chdir(tmpdir)
try:
assert not os.path.exists(".marker")
engine_args = AsyncEngineArgs(
model=model, distributed_executor_backend=CustomGPUExecutorAsync)
engine = AsyncLLMEngine.from_engine_args(engine_args)
sampling_params = SamplingParams(max_tokens=1)
async def t():
stream = await engine.add_request("0", "foo", sampling_params)
async for x in stream:
...
asyncio.run(t())
assert os.path.exists(".marker")
finally:
os.chdir(cwd)

View File

@@ -7,17 +7,28 @@ from unittest.mock import patch
import pytest
from transformers import AutoTokenizer, PreTrainedTokenizerBase
from vllm.transformers_utils.tokenizer_group import get_tokenizer_group
from vllm.transformers_utils.tokenizer_group import (TokenizerGroup,
get_tokenizer_group)
from vllm.transformers_utils.tokenizer_group.ray_tokenizer_group import (
RayTokenizerGroupPool)
from vllm.transformers_utils.tokenizer_group.tokenizer_group import (
TokenizerGroup)
from ..conftest import get_tokenizer_pool_config
class CustomTokenizerGroup(TokenizerGroup):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._i = 0
def encode(self, *args, **kwargs):
self._i += 1
return super().encode(*args, **kwargs)
@pytest.mark.asyncio
@pytest.mark.parametrize("tokenizer_group_type", [None, "ray"])
@pytest.mark.parametrize("tokenizer_group_type",
[None, "ray", CustomTokenizerGroup])
async def test_tokenizer_group(tokenizer_group_type):
reference_tokenizer = AutoTokenizer.from_pretrained("gpt2")
tokenizer_group = get_tokenizer_group(
@@ -36,6 +47,8 @@ async def test_tokenizer_group(tokenizer_group_type):
PreTrainedTokenizerBase)
assert tokenizer_group.get_lora_tokenizer(
None) == await tokenizer_group.get_lora_tokenizer_async(None)
if tokenizer_group_type is CustomTokenizerGroup:
assert tokenizer_group._i > 0
@pytest.mark.asyncio