mirror of
https://git.datalinker.icu/vllm-project/vllm.git
synced 2026-03-23 09:33:40 +08:00
refactor tests
Signed-off-by: Xingyu Liu <charlotteliu12x@gmail.com>
This commit is contained in:
Xingyu Liu
parent
0cd72dc438
commit
5401f6529d
@ -1,163 +1,144 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
||||
"""Tests for ModelArchitectureConfig and its integration with ModelConfig."""
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from vllm.config import ModelConfig, ParallelConfig, SpeculativeConfig
|
||||
|
||||
BASE_TRUST_REMOTE_CODE_MODELS = {
|
||||
"nvidia/Llama-3_3-Nemotron-Super-49B-v1",
|
||||
"XiaomiMiMo/MiMo-7B-RL",
|
||||
# Excluded: Not available online right now
|
||||
# "FreedomIntelligence/openPangu-Ultra-MoE-718B-V1.1",
|
||||
"meituan-longcat/LongCat-Flash-Chat",
|
||||
}
|
||||
|
||||
def test_basic():
|
||||
trust_remote_code_models = [
|
||||
"nvidia/Llama-3_3-Nemotron-Super-49B-v1",
|
||||
"XiaomiMiMo/MiMo-7B-RL",
|
||||
# Excluded: Not available online right now
|
||||
# "FreedomIntelligence/openPangu-Ultra-MoE-718B-V1.1",
|
||||
"meituan-longcat/LongCat-Flash-Chat",
|
||||
]
|
||||
models_to_test = [
|
||||
"state-spaces/mamba-130m-hf",
|
||||
"mistralai/Mamba-Codestral-7B-v0.1",
|
||||
# Excluded: terratorch/torchgeo version mismatch in
|
||||
# Async Engine, Inputs, Utils, Worker, Config Test (CPU) CI test environment
|
||||
# (NonGeoDataset import error).
|
||||
# "ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
|
||||
"Zyphra/Zamba2-7B-instruct",
|
||||
"mosaicml/mpt-7b",
|
||||
"databricks/dbrx-instruct",
|
||||
"tiiuae/falcon-7b",
|
||||
"tiiuae/falcon-40b",
|
||||
"luccafong/deepseek_mtp_main_random",
|
||||
"luccafong/deepseek_mtp_draft_random",
|
||||
"Qwen/Qwen3-Next-80B-A3B-Instruct",
|
||||
"tiny-random/qwen3-next-moe",
|
||||
"zai-org/GLM-4.5",
|
||||
"baidu/ERNIE-4.5-21B-A3B-PT",
|
||||
# Models using base convertor
|
||||
"lmsys/gpt-oss-20b-bf16",
|
||||
"deepseek-ai/DeepSeek-V3.2-Exp",
|
||||
"meta-llama/Llama-4-Scout-17B-16E-Instruct",
|
||||
] + trust_remote_code_models
|
||||
BASE_MODELS_TO_TEST = [
|
||||
"state-spaces/mamba-130m-hf",
|
||||
"mistralai/Mamba-Codestral-7B-v0.1",
|
||||
# Excluded: terratorch/torchgeo version mismatch in CPU CI environment
|
||||
# (NonGeoDataset import error). Tested in model initialization tests.
|
||||
# "ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
|
||||
"Zyphra/Zamba2-7B-instruct",
|
||||
"mosaicml/mpt-7b",
|
||||
"databricks/dbrx-instruct",
|
||||
"tiiuae/falcon-7b",
|
||||
"tiiuae/falcon-40b",
|
||||
"luccafong/deepseek_mtp_main_random",
|
||||
"Qwen/Qwen3-Next-80B-A3B-Instruct",
|
||||
"tiny-random/qwen3-next-moe",
|
||||
"zai-org/GLM-4.5",
|
||||
"baidu/ERNIE-4.5-21B-A3B-PT",
|
||||
# Models using base convertor
|
||||
"lmsys/gpt-oss-20b-bf16",
|
||||
"deepseek-ai/DeepSeek-V3.2-Exp",
|
||||
"meta-llama/Llama-4-Scout-17B-16E-Instruct",
|
||||
] + list(BASE_TRUST_REMOTE_CODE_MODELS)
|
||||
|
||||
groundtruth_path = Path(__file__).parent / "base_model_arch_groundtruth.json"
|
||||
# (target_model, draft_model, trust_remote_code)
|
||||
SPECULATIVE_MODELS = [
|
||||
("JackFram/llama-68m", "abhigoyal/vllm-medusa-llama-68m-random", False),
|
||||
("luccafong/deepseek_mtp_main_random", "luccafong/deepseek_mtp_draft_random", True),
|
||||
("eagle618/deepseek-v3-random", "eagle618/eagle-deepseek-v3-random", True),
|
||||
("meta-llama/Meta-Llama-3-8B-Instruct", "yuhuili/EAGLE-LLaMA3-Instruct-8B", True),
|
||||
("meta-llama/Llama-3.1-8B-Instruct", "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B", True),
|
||||
]
|
||||
|
||||
|
||||
def _load_groundtruth(filename: str) -> dict:
|
||||
"""Load groundtruth JSON from the test directory."""
|
||||
groundtruth_path = Path(__file__).parent / filename
|
||||
with open(groundtruth_path) as f:
|
||||
model_arch_groundtruth = json.load(f)
|
||||
return json.load(f)
|
||||
|
||||
for model in models_to_test:
|
||||
print(f"testing {model=}")
|
||||
model_config = ModelConfig(
|
||||
model, trust_remote_code=model in trust_remote_code_models
|
||||
)
|
||||
|
||||
model_arch_config = model_config.model_arch_config
|
||||
expected = model_arch_groundtruth[model]
|
||||
assert model_arch_config.architectures == expected["architectures"]
|
||||
assert model_arch_config.model_type == expected["model_type"]
|
||||
assert model_arch_config.text_model_type == expected["text_model_type"]
|
||||
assert model_arch_config.hidden_size == expected["hidden_size"]
|
||||
assert (
|
||||
model_arch_config.total_num_hidden_layers
|
||||
== expected["total_num_hidden_layers"]
|
||||
)
|
||||
assert (
|
||||
model_arch_config.total_num_attention_heads
|
||||
== expected["total_num_attention_heads"]
|
||||
)
|
||||
def _assert_model_arch_config(
|
||||
model_arch_config, expected: dict, check_head_size: bool = True
|
||||
):
|
||||
"""Assert model_arch_config matches expected values."""
|
||||
assert model_arch_config.architectures == expected["architectures"]
|
||||
assert model_arch_config.model_type == expected["model_type"]
|
||||
assert model_arch_config.text_model_type == expected["text_model_type"]
|
||||
assert model_arch_config.hidden_size == expected["hidden_size"]
|
||||
assert (
|
||||
model_arch_config.total_num_hidden_layers == expected["total_num_hidden_layers"]
|
||||
)
|
||||
assert (
|
||||
model_arch_config.total_num_attention_heads
|
||||
== expected["total_num_attention_heads"]
|
||||
)
|
||||
assert model_arch_config.vocab_size == expected["vocab_size"]
|
||||
assert model_arch_config.total_num_kv_heads == expected["total_num_kv_heads"]
|
||||
assert model_arch_config.num_experts == expected["num_experts"]
|
||||
assert model_arch_config.is_deepseek_mla == expected["is_deepseek_mla"]
|
||||
assert str(model_arch_config.torch_dtype) == expected["dtype"]
|
||||
|
||||
if check_head_size:
|
||||
assert model_arch_config.head_size == expected["head_size"]
|
||||
assert model_arch_config.vocab_size == expected["vocab_size"]
|
||||
assert model_arch_config.total_num_kv_heads == expected["total_num_kv_heads"]
|
||||
assert model_arch_config.num_experts == expected["num_experts"]
|
||||
assert model_arch_config.is_deepseek_mla == expected["is_deepseek_mla"]
|
||||
dtype = model_arch_config.torch_dtype
|
||||
assert str(dtype) == expected["dtype"]
|
||||
|
||||
# Ensure model_config methods return expected values
|
||||
assert model_config.architectures == expected["architectures"]
|
||||
assert model_config.get_vocab_size() == expected["vocab_size"]
|
||||
assert model_config.get_hidden_size() == expected["hidden_size"]
|
||||
|
||||
def _assert_model_config_methods(
|
||||
model_config, expected: dict, check_head_size: bool = True
|
||||
):
|
||||
"""Assert model_config methods return expected values."""
|
||||
assert model_config.architectures == expected["architectures"]
|
||||
assert model_config.get_vocab_size() == expected["vocab_size"]
|
||||
assert model_config.get_hidden_size() == expected["hidden_size"]
|
||||
assert model_config.get_total_num_kv_heads() == expected["total_num_kv_heads"]
|
||||
assert model_config.get_num_experts() == expected["num_experts"]
|
||||
assert (
|
||||
model_config.get_total_num_hidden_layers()
|
||||
== expected["total_num_hidden_layers"]
|
||||
)
|
||||
|
||||
if check_head_size:
|
||||
assert model_config.get_head_size() == expected["head_size"]
|
||||
assert model_config.get_total_num_kv_heads() == expected["total_num_kv_heads"]
|
||||
assert model_config.get_num_experts() == expected["num_experts"]
|
||||
assert (
|
||||
model_config.get_total_num_hidden_layers()
|
||||
== expected["total_num_hidden_layers"]
|
||||
)
|
||||
|
||||
|
||||
def test_draft_models():
|
||||
speculative_models = [
|
||||
("JackFram/llama-68m", "abhigoyal/vllm-medusa-llama-68m-random", False),
|
||||
(
|
||||
"luccafong/deepseek_mtp_main_random",
|
||||
"luccafong/deepseek_mtp_draft_random",
|
||||
True,
|
||||
),
|
||||
("eagle618/deepseek-v3-random", "eagle618/eagle-deepseek-v3-random", True),
|
||||
(
|
||||
"meta-llama/Meta-Llama-3-8B-Instruct",
|
||||
"yuhuili/EAGLE-LLaMA3-Instruct-8B",
|
||||
True,
|
||||
),
|
||||
(
|
||||
"meta-llama/Llama-3.1-8B-Instruct",
|
||||
"yuhuili/EAGLE3-LLaMA3.1-Instruct-8B",
|
||||
True,
|
||||
),
|
||||
]
|
||||
@pytest.mark.parametrize("model", BASE_MODELS_TO_TEST)
|
||||
def test_base_model_arch_config(model: str):
|
||||
"""Test model architecture config for base models."""
|
||||
groundtruth = _load_groundtruth("base_model_arch_groundtruth.json")
|
||||
expected = groundtruth[model]
|
||||
|
||||
groundtruth_path = Path(__file__).parent / "draft_model_arch_groundtruth.json"
|
||||
with open(groundtruth_path) as f:
|
||||
model_arch_groundtruth = json.load(f)
|
||||
model_config = ModelConfig(
|
||||
model, trust_remote_code=model in BASE_TRUST_REMOTE_CODE_MODELS
|
||||
)
|
||||
|
||||
for target_model, draft_model, trust_remote_code in speculative_models:
|
||||
print(f"testing {target_model=} {draft_model=}")
|
||||
target_model_config = ModelConfig(
|
||||
target_model, trust_remote_code=trust_remote_code
|
||||
)
|
||||
speculative_config = {
|
||||
"model": draft_model,
|
||||
"num_speculative_tokens": 1,
|
||||
"target_model_config": target_model_config,
|
||||
"target_parallel_config": ParallelConfig(),
|
||||
}
|
||||
_assert_model_arch_config(model_config.model_arch_config, expected)
|
||||
_assert_model_config_methods(model_config, expected)
|
||||
|
||||
speculative_config = SpeculativeConfig(**speculative_config)
|
||||
model_config = speculative_config.draft_model_config
|
||||
|
||||
model_arch_config = model_config.model_arch_config
|
||||
expected = model_arch_groundtruth[draft_model]
|
||||
assert model_arch_config.architectures == expected["architectures"]
|
||||
assert model_arch_config.model_type == expected["model_type"]
|
||||
assert model_arch_config.text_model_type == expected["text_model_type"]
|
||||
assert model_arch_config.hidden_size == expected["hidden_size"]
|
||||
assert (
|
||||
model_arch_config.total_num_hidden_layers
|
||||
== expected["total_num_hidden_layers"]
|
||||
)
|
||||
assert (
|
||||
model_arch_config.total_num_attention_heads
|
||||
== expected["total_num_attention_heads"]
|
||||
)
|
||||
@pytest.mark.parametrize(
|
||||
"target_model,draft_model,trust_remote_code", SPECULATIVE_MODELS
|
||||
)
|
||||
def test_draft_model_arch_config(
|
||||
target_model: str, draft_model: str, trust_remote_code: bool
|
||||
):
|
||||
"""Test model architecture config for draft/speculative models."""
|
||||
groundtruth = _load_groundtruth("draft_model_arch_groundtruth.json")
|
||||
expected = groundtruth[draft_model]
|
||||
|
||||
assert model_arch_config.vocab_size == expected["vocab_size"]
|
||||
assert model_arch_config.total_num_kv_heads == expected["total_num_kv_heads"]
|
||||
assert model_arch_config.num_experts == expected["num_experts"]
|
||||
assert model_arch_config.is_deepseek_mla == expected["is_deepseek_mla"]
|
||||
dtype = model_arch_config.torch_dtype
|
||||
assert str(dtype) == expected["dtype"]
|
||||
target_model_config = ModelConfig(target_model, trust_remote_code=trust_remote_code)
|
||||
speculative_config = SpeculativeConfig(
|
||||
model=draft_model,
|
||||
num_speculative_tokens=1,
|
||||
target_model_config=target_model_config,
|
||||
target_parallel_config=ParallelConfig(),
|
||||
)
|
||||
model_config = speculative_config.draft_model_config
|
||||
|
||||
# Ensure model_config methods return expected values
|
||||
assert model_config.architectures == expected["architectures"]
|
||||
assert model_config.get_vocab_size() == expected["vocab_size"]
|
||||
assert model_config.get_hidden_size() == expected["hidden_size"]
|
||||
assert model_config.get_total_num_kv_heads() == expected["total_num_kv_heads"]
|
||||
assert model_config.get_num_experts() == expected["num_experts"]
|
||||
assert (
|
||||
model_config.get_total_num_hidden_layers()
|
||||
== expected["total_num_hidden_layers"]
|
||||
)
|
||||
# For medusa models, head_size may cause division by zero before
|
||||
# model_arch_config was introduced, so we conditionally check it
|
||||
check_head_size = isinstance(expected["head_size"], int)
|
||||
|
||||
if isinstance(expected["head_size"], int):
|
||||
# Before model_arch_config is introduced, get_head_size() for medusa
|
||||
# model config will throw out `integer division or modulo by zero` error.
|
||||
assert model_arch_config.head_size == expected["head_size"]
|
||||
assert model_config.get_head_size() == expected["head_size"]
|
||||
_assert_model_arch_config(
|
||||
model_config.model_arch_config, expected, check_head_size=check_head_size
|
||||
)
|
||||
_assert_model_config_methods(
|
||||
model_config, expected, check_head_size=check_head_size
|
||||
)
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user