init
This commit is contained in:
73
tests/quantization/test_configs.py
Normal file
73
tests/quantization/test_configs.py
Normal file
@@ -0,0 +1,73 @@
|
||||
"""Tests whether Marlin models can be loaded from the autogptq config.
|
||||
|
||||
Run `pytest tests/quantization/test_configs.py --forked`.
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass
|
||||
|
||||
import pytest
|
||||
|
||||
from vllm.config import ModelConfig
|
||||
|
||||
|
||||
@dataclass
|
||||
class ModelPair:
|
||||
model_marlin: str
|
||||
model_gptq: str
|
||||
|
||||
|
||||
# Model Id // Quantization Arg // Expected Type
|
||||
MODEL_ARG_EXPTYPES = [
|
||||
# AUTOGPTQ
|
||||
# compat: autogptq <=0.7.1 is_marlin_format: bool
|
||||
# Model Serialized in Marlin Format should always use Marlin kernel.
|
||||
("neuralmagic/TinyLlama-1.1B-Chat-v1.0-marlin", None, "marlin"),
|
||||
("neuralmagic/TinyLlama-1.1B-Chat-v1.0-marlin", "marlin", "marlin"),
|
||||
("neuralmagic/TinyLlama-1.1B-Chat-v1.0-marlin", "gptq", "marlin"),
|
||||
("neuralmagic/TinyLlama-1.1B-Chat-v1.0-marlin", "awq", "ERROR"),
|
||||
# Model Serialized in Exllama Format.
|
||||
("TheBloke/Llama-2-7B-Chat-GPTQ", None, "gptq_marlin"),
|
||||
("TheBloke/Llama-2-7B-Chat-GPTQ", "marlin", "gptq_marlin"),
|
||||
("TheBloke/Llama-2-7B-Chat-GPTQ", "gptq", "gptq"),
|
||||
("TheBloke/Llama-2-7B-Chat-GPTQ", "awq", "ERROR"),
|
||||
# compat: autogptq >=0.8.0 use checkpoint_format: str
|
||||
# Model Serialized in Marlin Format should always use Marlin kernel.
|
||||
("LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-Marlin-4bit", None, "marlin"),
|
||||
("LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-Marlin-4bit", "marlin", "marlin"),
|
||||
("LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-Marlin-4bit", "gptq", "marlin"),
|
||||
("LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-Marlin-4bit", "awq", "ERROR"),
|
||||
# Model Serialized in Exllama Format.
|
||||
("LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-4bit", None, "gptq_marlin"),
|
||||
("LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-4bit", "marlin", "gptq_marlin"),
|
||||
("LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-4bit", "gptq", "gptq"),
|
||||
("LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-4bit", "awq", "ERROR"),
|
||||
|
||||
# AUTOAWQ
|
||||
("TheBloke/OpenHermes-2.5-Mistral-7B-AWQ", None, "awq"),
|
||||
("TheBloke/OpenHermes-2.5-Mistral-7B-AWQ", "awq", "awq"),
|
||||
("TheBloke/OpenHermes-2.5-Mistral-7B-AWQ", "marlin", "ERROR"),
|
||||
("TheBloke/OpenHermes-2.5-Mistral-7B-AWQ", "gptq", "ERROR"),
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.parametrize("model_arg_exptype", MODEL_ARG_EXPTYPES)
|
||||
def test_auto_gptq(model_arg_exptype: str) -> None:
|
||||
model_path, quantization_arg, expected_type = model_arg_exptype
|
||||
|
||||
try:
|
||||
model_config = ModelConfig(model_path,
|
||||
model_path,
|
||||
tokenizer_mode="auto",
|
||||
trust_remote_code=False,
|
||||
seed=0,
|
||||
dtype="float16",
|
||||
revision=None,
|
||||
quantization=quantization_arg)
|
||||
found_quantization_type = model_config.quantization
|
||||
except ValueError:
|
||||
found_quantization_type = "ERROR"
|
||||
|
||||
assert found_quantization_type == expected_type, (
|
||||
f"Expected quant_type == {expected_type} for {model_path}, "
|
||||
f"but found {found_quantization_type} "
|
||||
f"for no --quantization {quantization_arg} case")
|
||||
Reference in New Issue
Block a user