chore: update vllm to 0.5.4 (#966)

This commit is contained in:
Yineng Zhang
2024-08-07 19:15:41 +08:00
committed by GitHub
parent a01ddd9605
commit c31f084c71
14 changed files with 15 additions and 18 deletions

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@@ -34,8 +34,7 @@ jobs:
pip cache purge
pip install --upgrade pip
pip install -e "python[all]"
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.3/ --force-reinstall
pip install --upgrade transformers
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/ --force-reinstall
- name: Benchmark Serving Throughput
run: |

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@@ -34,8 +34,7 @@ jobs:
pip cache purge
pip install --upgrade pip
pip install -e "python[all]"
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.3/ --force-reinstall
pip install --upgrade transformers
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/ --force-reinstall
pip install accelerate
- name: Test Frontend Language

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@@ -49,7 +49,7 @@ pip install --upgrade pip
pip install "sglang[all]"
# Install FlashInfer CUDA kernels
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.3/
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/
```
### Method 2: From source
@@ -62,7 +62,7 @@ pip install --upgrade pip
pip install -e "python[all]"
# Install FlashInfer CUDA kernels
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.3/
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/
```
### Method 3: Using docker

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@@ -29,6 +29,6 @@ RUN pip3 --no-cache-dir install --upgrade pip \
&& git clone --depth=1 https://github.com/sgl-project/sglang.git \
&& cd sglang \
&& pip --no-cache-dir install -e "python[all]" \
&& pip3 --no-cache-dir install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.3/
&& pip3 --no-cache-dir install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/
ENV DEBIAN_FRONTEND=interactive

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@@ -23,7 +23,7 @@ dependencies = [
srt = ["aiohttp", "fastapi", "hf_transfer", "huggingface_hub", "interegular",
"packaging", "pillow", "psutil", "pydantic", "python-multipart",
"torch", "uvicorn", "uvloop", "zmq",
"vllm==0.5.3.post1", "outlines>=0.0.44"]
"vllm==0.5.4", "outlines>=0.0.44"]
openai = ["openai>=1.0", "tiktoken"]
anthropic = ["anthropic>=0.20.0"]
litellm = ["litellm>=1.0.0"]

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@@ -14,6 +14,7 @@ PACKAGE_LIST = [
"sglang",
"flashinfer",
"triton",
"transformers",
"requests",
"tqdm",
"numpy",

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@@ -18,9 +18,7 @@ import torch
from sglang.test.runners import DEFAULT_PROMPTS, HFRunner, SRTRunner
MODELS = [
# (model_name, tp_size)
("meta-llama/Meta-Llama-3.1-8B-Instruct", 1),
# ("meta-llama/Meta-Llama-3.1-8B-Instruct", 2),
]
TORCH_DTYPES = [torch.float16]
@@ -51,7 +49,7 @@ class TestCausalModels(unittest.TestCase):
hf_logprobs = torch.Tensor(hf_outputs.top_input_logprobs[i])
srt_logprobs = torch.Tensor(srt_outputs.top_input_logprobs[i])
tolerance = 2e-2
tolerance = 3e-2
assert torch.all(
abs(hf_logprobs - srt_logprobs) < tolerance
), f"prefill logprobs not all close"

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@@ -20,7 +20,7 @@ if __name__ == "__main__":
arg_parser.add_argument(
"--timeout-per-file",
type=int,
default=1000,
default=2000,
help="The time limit for running one file in seconds.",
)
arg_parser.add_argument(

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@@ -11,7 +11,7 @@ class TestAccuracy(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
cls.base_url = f"http://localhost:8157"
cls.base_url = "http://127.0.0.1:8157"
cls.process = popen_launch_server(
cls.model,
cls.base_url,

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@@ -11,7 +11,7 @@ class TestAccuracy(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
cls.base_url = f"http://localhost:8157"
cls.base_url = "http://127.0.0.1:8157"
cls.process = popen_launch_server(cls.model, cls.base_url, timeout=300)
@classmethod

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@@ -14,7 +14,7 @@ class TestOpenAIServer(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
cls.base_url = f"http://localhost:8157"
cls.base_url = "http://127.0.0.1:8157"
cls.api_key = "sk-123456"
cls.process = popen_launch_server(
cls.model, cls.base_url, timeout=300, api_key=cls.api_key

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@@ -13,7 +13,7 @@ class TestSRTEndpoint(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
cls.base_url = f"http://localhost:{8157}"
cls.base_url = "http://127.0.0.1:8157"
cls.process = popen_launch_server(cls.model, cls.base_url, timeout=300)
@classmethod

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@@ -11,7 +11,7 @@ class TestAccuracy(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
cls.base_url = f"http://localhost:8157"
cls.base_url = "http://127.0.0.1:8157"
cls.process = popen_launch_server(
cls.model, cls.base_url, timeout=300, other_args=["--enable-torch-compile"]
)

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@@ -13,7 +13,7 @@ class TestOpenAIVisionServer(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = "liuhaotian/llava-v1.6-vicuna-7b"
cls.base_url = "http://localhost:8157"
cls.base_url = "http://127.0.0.1:8157"
cls.api_key = "sk-123456"
cls.process = popen_launch_server(
cls.model,