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[V0 Deprecation] Remove Prompt Adapters (#20588)

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Signed-off-by: mgoin <mgoin64@gmail.com>
This commit is contained in:
Michael Goin
2025-07-23 19:36:48 -04:00
committed by GitHub
parent 78c13e30e1
commit 82ec66f514
60 changed files with 126 additions and 1727 deletions
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72
tests/entrypoints/openai/test_completion.py
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@@ -2,6 +2,7 @@
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
# imports for guided decoding tests
import json
import os
import shutil
from tempfile import TemporaryDirectory
from typing import Optional
@@ -26,10 +27,6 @@ MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
# technically these adapters use a different base model,
# but we're not testing generation quality here
LORA_NAME = "typeof/zephyr-7b-beta-lora"
PA_NAME = "swapnilbp/llama_tweet_ptune"
# if PA_NAME changes, PA_NUM_VIRTUAL_TOKENS might also
# need to change to match the prompt adapter
PA_NUM_VIRTUAL_TOKENS = 8
GUIDED_DECODING_BACKENDS = ["outlines", "lm-format-enforcer", "xgrammar"]
@@ -56,13 +53,7 @@ def zephyr_lora_added_tokens_files(zephyr_lora_files):
@pytest.fixture(scope="module")
def zephyr_pa_files():
return snapshot_download(repo_id=PA_NAME)
@pytest.fixture(scope="module")
def default_server_args(zephyr_lora_files, zephyr_lora_added_tokens_files,
zephyr_pa_files):
def default_server_args(zephyr_lora_files, zephyr_lora_added_tokens_files):
return [
# use half precision for speed and memory savings in CI environment
"--dtype",
@@ -81,15 +72,6 @@ def default_server_args(zephyr_lora_files, zephyr_lora_added_tokens_files,
"64",
"--max-cpu-loras",
"2",
# pa config
"--enable-prompt-adapter",
"--prompt-adapters",
f"zephyr-pa={zephyr_pa_files}",
f"zephyr-pa2={zephyr_pa_files}",
"--max-prompt-adapters",
"2",
"--max-prompt-adapter-token",
"128",
]
@@ -98,8 +80,19 @@ def default_server_args(zephyr_lora_files, zephyr_lora_added_tokens_files,
def server(default_server_args, request):
if request.param:
default_server_args.append(request.param)
with RemoteOpenAIServer(MODEL_NAME, default_server_args) as remote_server:
yield remote_server
original_value = os.environ.get('VLLM_USE_V1')
os.environ['VLLM_USE_V1'] = '0'
try:
with RemoteOpenAIServer(MODEL_NAME,
default_server_args) as remote_server:
yield remote_server
finally:
# Restore original env value
if original_value is None:
os.environ.pop('VLLM_USE_V1', None)
else:
os.environ['VLLM_USE_V1'] = original_value
@pytest_asyncio.fixture
@@ -110,14 +103,11 @@ async def client(server):
@pytest.mark.asyncio
@pytest.mark.parametrize(
# first test base model, then test loras, then test prompt adapters
"model_name,num_virtual_tokens",
[(MODEL_NAME, 0), ("zephyr-lora", 0), ("zephyr-lora2", 0),
("zephyr-pa", PA_NUM_VIRTUAL_TOKENS),
("zephyr-pa2", PA_NUM_VIRTUAL_TOKENS)],
# first test base model, then test loras
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-lora2"],
)
async def test_single_completion(client: openai.AsyncOpenAI, model_name: str,
num_virtual_tokens: int):
async def test_single_completion(client: openai.AsyncOpenAI, model_name: str):
completion = await client.completions.create(model=model_name,
prompt="Hello, my name is",
max_tokens=5,
@@ -130,9 +120,7 @@ async def test_single_completion(client: openai.AsyncOpenAI, model_name: str,
assert len(choice.text) >= 5
assert choice.finish_reason == "length"
assert completion.usage == openai.types.CompletionUsage(
completion_tokens=5,
prompt_tokens=6 + num_virtual_tokens,
total_tokens=11 + num_virtual_tokens)
completion_tokens=5, prompt_tokens=6, total_tokens=11)
# test using token IDs
completion = await client.completions.create(
@@ -175,9 +163,9 @@ async def test_added_lora_tokens_base_model(client: openai.AsyncOpenAI):
@pytest.mark.asyncio
@pytest.mark.parametrize(
# first test base model, then test loras, then test prompt adapters
# first test base model, then test loras
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-lora2", "zephyr-pa", "zephyr-pa2"],
[MODEL_NAME, "zephyr-lora", "zephyr-lora2"],
)
async def test_no_logprobs(client: openai.AsyncOpenAI, model_name: str):
# test using token IDs
@@ -194,9 +182,9 @@ async def test_no_logprobs(client: openai.AsyncOpenAI, model_name: str):
@pytest.mark.asyncio
@pytest.mark.parametrize(
# just test 1 lora and 1 pa hereafter
# just test 1 lora
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-pa"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_zero_logprobs(client: openai.AsyncOpenAI, model_name: str):
# test using token IDs
@@ -217,7 +205,7 @@ async def test_zero_logprobs(client: openai.AsyncOpenAI, model_name: str):
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-pa"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_some_logprobs(client: openai.AsyncOpenAI, model_name: str):
# test using token IDs
@@ -238,7 +226,7 @@ async def test_some_logprobs(client: openai.AsyncOpenAI, model_name: str):
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-pa"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_too_many_completion_logprobs(client: openai.AsyncOpenAI,
model_name: str):
@@ -314,7 +302,7 @@ async def test_prompt_logprobs_completion(client: openai.AsyncOpenAI,
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-pa"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_completion_streaming(client: openai.AsyncOpenAI,
model_name: str):
@@ -348,7 +336,7 @@ async def test_completion_streaming(client: openai.AsyncOpenAI,
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-pa"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_parallel_streaming(client: openai.AsyncOpenAI, model_name: str):
"""Streaming for parallel sampling.
@@ -382,7 +370,7 @@ async def test_parallel_streaming(client: openai.AsyncOpenAI, model_name: str):
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-pa"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_completion_stream_options(client: openai.AsyncOpenAI,
model_name: str):
@@ -519,7 +507,7 @@ async def test_completion_stream_options(client: openai.AsyncOpenAI,
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-pa"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_batch_completions(client: openai.AsyncOpenAI, model_name: str):
# test both text and token IDs