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80 lines
3.3 KiB
Python
80 lines
3.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Tests whether gptq models with dynamic quantized can be loaded.
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Run `pytest tests/quantization/test_gptq_dynamic.py --forked`.
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"""
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import pytest
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import torch
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from vllm.model_executor.layers.linear import UnquantizedLinearMethod
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from vllm.model_executor.layers.quantization.gptq import GPTQLinearMethod
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from vllm.model_executor.layers.quantization.gptq_marlin import GPTQMarlinLinearMethod
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from vllm.model_executor.layers.quantization.utils.gptq_utils import (
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get_dynamic_override,
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)
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PROMPT = "On the surface of Mars, we found"
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# The first layer is quantized using bits=4, group_size=128
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# The second layer is quantized using bits=8, group_size=32
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# All other layers (layer index >= 2) are not quantized
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MODEL_QUANT = [
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("ModelCloud/Qwen1.5-1.8B-Chat-GPTQ-4bits-dynamic-cfg-with-lm_head-symTrue", True),
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(
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"ModelCloud/Qwen1.5-1.8B-Chat-GPTQ-4bits-dynamic-cfg-with-lm_head-symFalse",
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False,
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),
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]
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@pytest.mark.parametrize("model_id, use_marlin_kernel", MODEL_QUANT)
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def test_gptq_with_dynamic(
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vllm_runner, model_id: str, use_marlin_kernel: bool, monkeypatch
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):
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# `LLM.apply_model` requires pickling a function.
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monkeypatch.setenv("VLLM_ALLOW_INSECURE_SERIALIZATION", "1")
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linear_method_cls = (
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GPTQMarlinLinearMethod if use_marlin_kernel else (GPTQLinearMethod)
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)
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with vllm_runner(model_id, dtype=torch.float16, max_model_len=2048) as llm:
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def check_model(model):
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for name, submodule in model.named_modules():
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if name == "lm_head":
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assert isinstance(submodule.quant_method, linear_method_cls)
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elif name == "model.layers.0.self_attn.qkv_proj":
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# The first layer is quantized using bits=4, group_size=128
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# desc_act=True
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assert isinstance(submodule.quant_method, linear_method_cls)
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config = submodule.quant_method.quant_config
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assert config.weight_bits == 4
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assert config.group_size == 128
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assert config.desc_act
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elif name == "model.layers.1.self_attn.qkv_proj":
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# The second layer is quantized using bits=8, group_size=32
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# desc_act=False
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assert isinstance(submodule.quant_method, linear_method_cls)
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config = submodule.quant_method.quant_config
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assert (
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get_dynamic_override(config, layer_name=name, key="bits") == 8
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)
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assert (
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get_dynamic_override(config, layer_name=name, key="group_size")
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== 32
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)
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assert not get_dynamic_override(
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config, layer_name=name, key="desc_act"
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)
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elif (
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name == "model.layers.2.self_attn.qkv_proj"
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or name == "model.layers.2.mlp.gate_up_proj"
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):
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# All other layers (layer index >= 2) are not quantized
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assert isinstance(submodule.quant_method, UnquantizedLinearMethod)
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llm.apply_model(check_model)
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