mirror of
https://git.datalinker.icu/vllm-project/vllm.git
synced 2025-12-10 09:45:49 +08:00
e489ad7a21
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**
commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:18:24 2025 -0500
Add SPDX license headers to python source files
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
also be easily used by tools to help manage license compliance.
The Linux Foundation runs license scans against the codebase to help
ensure
we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
More information can be found on the SPDX site:
- https://spdx.dev/learn/handling-license-info/
Signed-off-by: Russell Bryant <rbryant@redhat.com>
commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:36:32 2025 -0500
Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>
---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>
319 lines
17 KiB
Python
319 lines
17 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
|
|
from dataclasses import dataclass, field
|
|
from typing import AbstractSet, Any, Literal, Mapping, Optional
|
|
|
|
import pytest
|
|
from packaging.version import Version
|
|
from transformers import __version__ as TRANSFORMERS_VERSION
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class _HfExamplesInfo:
|
|
default: str
|
|
"""The default model to use for testing this architecture."""
|
|
|
|
extras: Mapping[str, str] = field(default_factory=dict)
|
|
"""Extra models to use for testing this architecture."""
|
|
|
|
tokenizer: Optional[str] = None
|
|
"""Set the tokenizer to load for this architecture."""
|
|
|
|
tokenizer_mode: str = "auto"
|
|
"""Set the tokenizer type for this architecture."""
|
|
|
|
speculative_model: Optional[str] = None
|
|
"""
|
|
The default model to use for testing this architecture, which is only used
|
|
for speculative decoding.
|
|
"""
|
|
|
|
min_transformers_version: Optional[str] = None
|
|
"""
|
|
The minimum version of HF Transformers that is required to run this model.
|
|
"""
|
|
|
|
is_available_online: bool = True
|
|
"""
|
|
Set this to ``False`` if the name of this architecture no longer exists on
|
|
the HF repo. To maintain backwards compatibility, we have not removed them
|
|
from the main model registry, so without this flag the registry tests will
|
|
fail.
|
|
"""
|
|
|
|
trust_remote_code: bool = False
|
|
"""The ``trust_remote_code`` level required to load the model."""
|
|
|
|
hf_overrides: dict[str, Any] = field(default_factory=dict)
|
|
"""The ``hf_overrides`` required to load the model."""
|
|
|
|
def check_transformers_version(
|
|
self,
|
|
*,
|
|
on_fail: Literal["error", "skip"],
|
|
) -> None:
|
|
"""
|
|
If the installed transformers version does not meet the requirements,
|
|
perform the given action.
|
|
"""
|
|
if self.min_transformers_version is None:
|
|
return
|
|
|
|
current_version = TRANSFORMERS_VERSION
|
|
required_version = self.min_transformers_version
|
|
if Version(current_version) < Version(required_version):
|
|
msg = (
|
|
f"You have `transformers=={current_version}` installed, but "
|
|
f"`transformers>={required_version}` is required to run this "
|
|
"model")
|
|
|
|
if on_fail == "error":
|
|
raise RuntimeError(msg)
|
|
else:
|
|
pytest.skip(msg)
|
|
|
|
def check_available_online(
|
|
self,
|
|
*,
|
|
on_fail: Literal["error", "skip"],
|
|
) -> None:
|
|
"""
|
|
If the model is not available online, perform the given action.
|
|
"""
|
|
if not self.is_available_online:
|
|
msg = "Model is not available online"
|
|
|
|
if on_fail == "error":
|
|
raise RuntimeError(msg)
|
|
else:
|
|
pytest.skip(msg)
|
|
|
|
|
|
# yapf: disable
|
|
_TEXT_GENERATION_EXAMPLE_MODELS = {
|
|
# [Decoder-only]
|
|
"AquilaModel": _HfExamplesInfo("BAAI/AquilaChat-7B",
|
|
trust_remote_code=True),
|
|
"AquilaForCausalLM": _HfExamplesInfo("BAAI/AquilaChat2-7B",
|
|
trust_remote_code=True),
|
|
"ArcticForCausalLM": _HfExamplesInfo("Snowflake/snowflake-arctic-instruct",
|
|
trust_remote_code=True),
|
|
"BaiChuanForCausalLM": _HfExamplesInfo("baichuan-inc/Baichuan-7B",
|
|
trust_remote_code=True),
|
|
"BaichuanForCausalLM": _HfExamplesInfo("baichuan-inc/Baichuan2-7B-chat",
|
|
trust_remote_code=True),
|
|
"BloomForCausalLM": _HfExamplesInfo("bigscience/bloomz-1b1"),
|
|
# ChatGLMModel supports multimodal
|
|
"CohereForCausalLM": _HfExamplesInfo("CohereForAI/c4ai-command-r-v01",
|
|
trust_remote_code=True),
|
|
"Cohere2ForCausalLM": _HfExamplesInfo("CohereForAI/c4ai-command-r7b-12-2024", # noqa: E501
|
|
trust_remote_code=True),
|
|
"DbrxForCausalLM": _HfExamplesInfo("databricks/dbrx-instruct"),
|
|
"DeciLMForCausalLM": _HfExamplesInfo("Deci/DeciLM-7B-instruct",
|
|
trust_remote_code=True),
|
|
"DeepseekForCausalLM": _HfExamplesInfo("deepseek-ai/deepseek-llm-7b-chat"),
|
|
"DeepseekV2ForCausalLM": _HfExamplesInfo("deepseek-ai/DeepSeek-V2-Lite-Chat", # noqa: E501
|
|
trust_remote_code=True),
|
|
"DeepseekV3ForCausalLM": _HfExamplesInfo("deepseek-ai/DeepSeek-V3", # noqa: E501
|
|
trust_remote_code=True),
|
|
"ExaoneForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct"), # noqa: E501
|
|
"Fairseq2LlamaForCausalLM": _HfExamplesInfo("mgleize/fairseq2-dummy-Llama-3.2-1B"), # noqa: E501
|
|
"FalconForCausalLM": _HfExamplesInfo("tiiuae/falcon-7b"),
|
|
"GemmaForCausalLM": _HfExamplesInfo("google/gemma-2b"),
|
|
"Gemma2ForCausalLM": _HfExamplesInfo("google/gemma-2-9b"),
|
|
"GlmForCausalLM": _HfExamplesInfo("THUDM/glm-4-9b-chat-hf"),
|
|
"GPT2LMHeadModel": _HfExamplesInfo("gpt2"),
|
|
"GPTBigCodeForCausalLM": _HfExamplesInfo("bigcode/starcoder"),
|
|
"GPTJForCausalLM": _HfExamplesInfo("EleutherAI/gpt-j-6b"),
|
|
"GPTNeoXForCausalLM": _HfExamplesInfo("EleutherAI/pythia-160m"),
|
|
"GraniteForCausalLM": _HfExamplesInfo("ibm/PowerLM-3b"),
|
|
"GraniteMoeForCausalLM": _HfExamplesInfo("ibm/PowerMoE-3b"),
|
|
"InternLMForCausalLM": _HfExamplesInfo("internlm/internlm-chat-7b",
|
|
trust_remote_code=True),
|
|
"InternLM2ForCausalLM": _HfExamplesInfo("internlm/internlm2-chat-7b",
|
|
trust_remote_code=True),
|
|
"InternLM2VEForCausalLM": _HfExamplesInfo("OpenGVLab/Mono-InternVL-2B",
|
|
trust_remote_code=True),
|
|
"InternLM3ForCausalLM": _HfExamplesInfo("internlm/internlm3-8b-instruct",
|
|
trust_remote_code=True),
|
|
"JAISLMHeadModel": _HfExamplesInfo("inceptionai/jais-13b-chat"),
|
|
"JambaForCausalLM": _HfExamplesInfo("ai21labs/AI21-Jamba-1.5-Mini"),
|
|
"LlamaForCausalLM": _HfExamplesInfo("meta-llama/Meta-Llama-3-8B"),
|
|
"LLaMAForCausalLM": _HfExamplesInfo("decapoda-research/llama-7b-hf",
|
|
is_available_online=False),
|
|
"MambaForCausalLM": _HfExamplesInfo("state-spaces/mamba-130m-hf"),
|
|
"FalconMambaForCausalLM": _HfExamplesInfo("tiiuae/falcon-mamba-7b-instruct"), # noqa: E501
|
|
"MiniCPMForCausalLM": _HfExamplesInfo("openbmb/MiniCPM-2B-sft-bf16",
|
|
trust_remote_code=True),
|
|
"MiniCPM3ForCausalLM": _HfExamplesInfo("openbmb/MiniCPM3-4B",
|
|
trust_remote_code=True),
|
|
"MistralForCausalLM": _HfExamplesInfo("mistralai/Mistral-7B-Instruct-v0.1"),
|
|
"MixtralForCausalLM": _HfExamplesInfo("mistralai/Mixtral-8x7B-Instruct-v0.1"), # noqa: E501
|
|
"QuantMixtralForCausalLM": _HfExamplesInfo("mistral-community/Mixtral-8x22B-v0.1-AWQ"), # noqa: E501
|
|
"MptForCausalLM": _HfExamplesInfo("mpt", is_available_online=False),
|
|
"MPTForCausalLM": _HfExamplesInfo("mosaicml/mpt-7b"),
|
|
"NemotronForCausalLM": _HfExamplesInfo("nvidia/Minitron-8B-Base"),
|
|
"OlmoForCausalLM": _HfExamplesInfo("allenai/OLMo-1B-hf"),
|
|
"Olmo2ForCausalLM": _HfExamplesInfo("shanearora/OLMo-7B-1124-hf"),
|
|
"OlmoeForCausalLM": _HfExamplesInfo("allenai/OLMoE-1B-7B-0924-Instruct"),
|
|
"OPTForCausalLM": _HfExamplesInfo("facebook/opt-iml-max-1.3b"),
|
|
"OrionForCausalLM": _HfExamplesInfo("OrionStarAI/Orion-14B-Chat",
|
|
trust_remote_code=True),
|
|
"PersimmonForCausalLM": _HfExamplesInfo("adept/persimmon-8b-chat"),
|
|
"PhiForCausalLM": _HfExamplesInfo("microsoft/phi-2"),
|
|
"Phi3ForCausalLM": _HfExamplesInfo("microsoft/Phi-3-mini-4k-instruct"),
|
|
"Phi3SmallForCausalLM": _HfExamplesInfo("microsoft/Phi-3-small-8k-instruct",
|
|
trust_remote_code=True),
|
|
"PhiMoEForCausalLM": _HfExamplesInfo("microsoft/Phi-3.5-MoE-instruct",
|
|
trust_remote_code=True),
|
|
# QWenLMHeadModel supports multimodal
|
|
"Qwen2ForCausalLM": _HfExamplesInfo("Qwen/Qwen2-7B-Instruct"),
|
|
"Qwen2MoeForCausalLM": _HfExamplesInfo("Qwen/Qwen1.5-MoE-A2.7B-Chat"),
|
|
"RWForCausalLM": _HfExamplesInfo("tiiuae/falcon-40b",
|
|
is_available_online=False),
|
|
"StableLMEpochForCausalLM": _HfExamplesInfo("stabilityai/stablelm-zephyr-3b", # noqa: E501
|
|
is_available_online=False),
|
|
"StableLmForCausalLM": _HfExamplesInfo("stabilityai/stablelm-3b-4e1t"),
|
|
"Starcoder2ForCausalLM": _HfExamplesInfo("bigcode/starcoder2-3b"),
|
|
"SolarForCausalLM": _HfExamplesInfo("upstage/solar-pro-preview-instruct"),
|
|
"TeleChat2ForCausalLM": _HfExamplesInfo("Tele-AI/TeleChat2-3B",
|
|
trust_remote_code=True),
|
|
"XverseForCausalLM": _HfExamplesInfo("xverse/XVERSE-7B-Chat",
|
|
is_available_online=False,
|
|
trust_remote_code=True),
|
|
# [Encoder-decoder]
|
|
"BartModel": _HfExamplesInfo("facebook/bart-base"),
|
|
"BartForConditionalGeneration": _HfExamplesInfo("facebook/bart-large-cnn"),
|
|
# Florence-2 uses BartFastTokenizer which can't be loaded from AutoTokenizer
|
|
# Therefore, we borrow the BartTokenizer from the original Bart model
|
|
"Florence2ForConditionalGeneration": _HfExamplesInfo("microsoft/Florence-2-base", # noqa: E501
|
|
tokenizer="facebook/bart-base",
|
|
trust_remote_code=True), # noqa: E501
|
|
}
|
|
|
|
_EMBEDDING_EXAMPLE_MODELS = {
|
|
# [Text-only]
|
|
"BertModel": _HfExamplesInfo("BAAI/bge-base-en-v1.5"),
|
|
"Gemma2Model": _HfExamplesInfo("BAAI/bge-multilingual-gemma2"),
|
|
"GritLM": _HfExamplesInfo("parasail-ai/GritLM-7B-vllm"),
|
|
"InternLM2ForRewardModel": _HfExamplesInfo("internlm/internlm2-1_8b-reward",
|
|
trust_remote_code=True),
|
|
"JambaForSequenceClassification": _HfExamplesInfo("ai21labs/Jamba-tiny-reward-dev"), # noqa: E501
|
|
"LlamaModel": _HfExamplesInfo("llama", is_available_online=False),
|
|
"MistralModel": _HfExamplesInfo("intfloat/e5-mistral-7b-instruct"),
|
|
"Qwen2Model": _HfExamplesInfo("ssmits/Qwen2-7B-Instruct-embed-base"),
|
|
"Qwen2ForRewardModel": _HfExamplesInfo("Qwen/Qwen2.5-Math-RM-72B"),
|
|
"Qwen2ForProcessRewardModel": _HfExamplesInfo("Qwen/Qwen2.5-Math-PRM-7B"),
|
|
"Qwen2ForSequenceClassification": _HfExamplesInfo("jason9693/Qwen2.5-1.5B-apeach"), # noqa: E501
|
|
"RobertaModel": _HfExamplesInfo("sentence-transformers/stsb-roberta-base-v2"), # noqa: E501
|
|
"RobertaForMaskedLM": _HfExamplesInfo("sentence-transformers/all-roberta-large-v1"), # noqa: E501
|
|
"XLMRobertaModel": _HfExamplesInfo("intfloat/multilingual-e5-large"),
|
|
# [Multimodal]
|
|
"LlavaNextForConditionalGeneration": _HfExamplesInfo("royokong/e5-v"),
|
|
"Phi3VForCausalLM": _HfExamplesInfo("TIGER-Lab/VLM2Vec-Full",
|
|
trust_remote_code=True),
|
|
"Qwen2VLForConditionalGeneration": _HfExamplesInfo("MrLight/dse-qwen2-2b-mrl-v1"), # noqa: E501
|
|
}
|
|
|
|
_CROSS_ENCODER_EXAMPLE_MODELS = {
|
|
# [Text-only]
|
|
"BertForSequenceClassification": _HfExamplesInfo("cross-encoder/ms-marco-MiniLM-L-6-v2"), # noqa: E501
|
|
"RobertaForSequenceClassification": _HfExamplesInfo("cross-encoder/quora-roberta-base"), # noqa: E501
|
|
"XLMRobertaForSequenceClassification": _HfExamplesInfo("BAAI/bge-reranker-v2-m3"), # noqa: E501
|
|
}
|
|
|
|
_MULTIMODAL_EXAMPLE_MODELS = {
|
|
# [Decoder-only]
|
|
"AriaForConditionalGeneration": _HfExamplesInfo("rhymes-ai/Aria",
|
|
min_transformers_version="4.48"),
|
|
"Blip2ForConditionalGeneration": _HfExamplesInfo("Salesforce/blip2-opt-2.7b"), # noqa: E501
|
|
"ChameleonForConditionalGeneration": _HfExamplesInfo("facebook/chameleon-7b"), # noqa: E501
|
|
"ChatGLMModel": _HfExamplesInfo("THUDM/glm-4v-9b",
|
|
extras={"text_only": "THUDM/chatglm3-6b"},
|
|
trust_remote_code=True),
|
|
"ChatGLMForConditionalGeneration": _HfExamplesInfo("chatglm2-6b",
|
|
is_available_online=False),
|
|
"DeepseekVLV2ForCausalLM": _HfExamplesInfo("deepseek-ai/deepseek-vl2-tiny", # noqa: E501
|
|
hf_overrides={"architectures": ["DeepseekVLV2ForCausalLM"]}), # noqa: E501
|
|
"FuyuForCausalLM": _HfExamplesInfo("adept/fuyu-8b"),
|
|
"H2OVLChatModel": _HfExamplesInfo("h2oai/h2ovl-mississippi-800m"),
|
|
"InternVLChatModel": _HfExamplesInfo("OpenGVLab/InternVL2-1B",
|
|
trust_remote_code=True),
|
|
"Idefics3ForConditionalGeneration": _HfExamplesInfo("HuggingFaceM4/Idefics3-8B-Llama3"), # noqa: E501
|
|
"LlavaForConditionalGeneration": _HfExamplesInfo("llava-hf/llava-1.5-7b-hf",
|
|
extras={"mistral": "mistral-community/pixtral-12b"}), # noqa: E501
|
|
"LlavaNextForConditionalGeneration": _HfExamplesInfo("llava-hf/llava-v1.6-mistral-7b-hf"), # noqa: E501
|
|
"LlavaNextVideoForConditionalGeneration": _HfExamplesInfo("llava-hf/LLaVA-NeXT-Video-7B-hf"), # noqa: E501
|
|
"LlavaOnevisionForConditionalGeneration": _HfExamplesInfo("llava-hf/llava-onevision-qwen2-0.5b-ov-hf"), # noqa: E501
|
|
"MantisForConditionalGeneration": _HfExamplesInfo("TIGER-Lab/Mantis-8B-siglip-llama3", # noqa: E501
|
|
hf_overrides={"architectures": ["MantisForConditionalGeneration"]}), # noqa: E501
|
|
"MiniCPMO": _HfExamplesInfo("openbmb/MiniCPM-o-2_6",
|
|
trust_remote_code=True),
|
|
"MiniCPMV": _HfExamplesInfo("openbmb/MiniCPM-V-2_6",
|
|
trust_remote_code=True),
|
|
"MolmoForCausalLM": _HfExamplesInfo("allenai/Molmo-7B-D-0924",
|
|
trust_remote_code=True),
|
|
"NVLM_D": _HfExamplesInfo("nvidia/NVLM-D-72B",
|
|
trust_remote_code=True),
|
|
"PaliGemmaForConditionalGeneration": _HfExamplesInfo("google/paligemma-3b-pt-224"), # noqa: E501
|
|
"Phi3VForCausalLM": _HfExamplesInfo("microsoft/Phi-3-vision-128k-instruct",
|
|
trust_remote_code=True),
|
|
"PixtralForConditionalGeneration": _HfExamplesInfo("mistralai/Pixtral-12B-2409", # noqa: E501
|
|
tokenizer_mode="mistral"),
|
|
"QWenLMHeadModel": _HfExamplesInfo("Qwen/Qwen-VL-Chat",
|
|
extras={"text_only": "Qwen/Qwen-7B-Chat"}, # noqa: E501
|
|
trust_remote_code=True),
|
|
"Qwen2AudioForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2-Audio-7B-Instruct"), # noqa: E501
|
|
"Qwen2VLForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2-VL-2B-Instruct"), # noqa: E501
|
|
"UltravoxModel": _HfExamplesInfo("fixie-ai/ultravox-v0_3",
|
|
trust_remote_code=True),
|
|
# [Encoder-decoder]
|
|
"MllamaForConditionalGeneration": _HfExamplesInfo("meta-llama/Llama-3.2-11B-Vision-Instruct"), # noqa: E501
|
|
"WhisperForConditionalGeneration": _HfExamplesInfo("openai/whisper-large-v3"), # noqa: E501
|
|
}
|
|
|
|
_SPECULATIVE_DECODING_EXAMPLE_MODELS = {
|
|
"EAGLEModel": _HfExamplesInfo("JackFram/llama-68m",
|
|
speculative_model="abhigoyal/vllm-eagle-llama-68m-random"), # noqa: E501
|
|
"MedusaModel": _HfExamplesInfo("JackFram/llama-68m",
|
|
speculative_model="abhigoyal/vllm-medusa-llama-68m-random"), # noqa: E501
|
|
"MLPSpeculatorPreTrainedModel": _HfExamplesInfo("JackFram/llama-160m",
|
|
speculative_model="ibm-fms/llama-160m-accelerator"), # noqa: E501
|
|
}
|
|
|
|
_EXAMPLE_MODELS = {
|
|
**_TEXT_GENERATION_EXAMPLE_MODELS,
|
|
**_EMBEDDING_EXAMPLE_MODELS,
|
|
**_CROSS_ENCODER_EXAMPLE_MODELS,
|
|
**_MULTIMODAL_EXAMPLE_MODELS,
|
|
**_SPECULATIVE_DECODING_EXAMPLE_MODELS,
|
|
}
|
|
|
|
|
|
class HfExampleModels:
|
|
def __init__(self, hf_models: Mapping[str, _HfExamplesInfo]) -> None:
|
|
super().__init__()
|
|
|
|
self.hf_models = hf_models
|
|
|
|
def get_supported_archs(self) -> AbstractSet[str]:
|
|
return self.hf_models.keys()
|
|
|
|
def get_hf_info(self, model_arch: str) -> _HfExamplesInfo:
|
|
return self.hf_models[model_arch]
|
|
|
|
def find_hf_info(self, model_id: str) -> _HfExamplesInfo:
|
|
for info in self.hf_models.values():
|
|
if info.default == model_id:
|
|
return info
|
|
|
|
# Fallback to extras
|
|
for info in self.hf_models.values():
|
|
if any(extra == model_id for extra in info.extras.values()):
|
|
return info
|
|
|
|
raise ValueError(f"No example model defined for {model_id}")
|
|
|
|
|
|
HF_EXAMPLE_MODELS = HfExampleModels(_EXAMPLE_MODELS)
|