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Fix qwen config (#261)

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This commit is contained in:
Liangsheng Yin
2024-03-11 09:54:18 +08:00
committed by GitHub
parent a833de05d3
commit a7ace9c88d
2 changed files with 5 additions and 5 deletions
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2
python/pyproject.toml
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@@ -19,7 +19,7 @@ dependencies = [
[project.optional-dependencies] [project.optional-dependencies]
srt = ["aiohttp", "fastapi", "psutil", "rpyc", "torch", "uvloop", "uvicorn", srt = ["aiohttp", "fastapi", "psutil", "rpyc", "torch", "uvloop", "uvicorn",
"zmq", "vllm>=0.2.5", "interegular", "lark", "numba", "zmq", "vllm>=0.3.3", "interegular", "lark", "numba",
"pydantic", "referencing", "diskcache", "cloudpickle", "pillow", "outlines>=0.0.27"] "pydantic", "referencing", "diskcache", "cloudpickle", "pillow", "outlines>=0.0.27"]
openai = ["openai>=1.0", "numpy"] openai = ["openai>=1.0", "numpy"]
anthropic = ["anthropic", "numpy"] anthropic = ["anthropic", "numpy"]

8
python/sglang/srt/models/qwen.py
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@@ -5,6 +5,7 @@ from sglang.srt.layers.logits_processor import LogitsProcessor
from sglang.srt.layers.radix_attention import RadixAttention from sglang.srt.layers.radix_attention import RadixAttention
from sglang.srt.managers.router.model_runner import InputMetadata from sglang.srt.managers.router.model_runner import InputMetadata
from torch import nn from torch import nn
from transformers import PretrainedConfig
from vllm.model_executor.layers.activation import SiluAndMul from vllm.model_executor.layers.activation import SiluAndMul
from vllm.model_executor.layers.layernorm import RMSNorm from vllm.model_executor.layers.layernorm import RMSNorm
from vllm.model_executor.layers.linear import ( from vllm.model_executor.layers.linear import (
@@ -25,7 +26,6 @@ from vllm.model_executor.weight_utils import (
default_weight_loader, default_weight_loader,
hf_model_weights_iterator, hf_model_weights_iterator,
) )
from vllm.transformers_utils.configs.qwen import QWenConfig
class QWenMLP(nn.Module): class QWenMLP(nn.Module):
@@ -130,7 +130,7 @@ class QWenAttention(nn.Module):
class QWenBlock(nn.Module): class QWenBlock(nn.Module):
def __init__(self, config: QWenConfig, layer_id, linear_method=None): def __init__(self, config: PretrainedConfig, layer_id, linear_method=None):
super().__init__() super().__init__()
self.ln_1 = RMSNorm(config.hidden_size, eps=config.layer_norm_epsilon) self.ln_1 = RMSNorm(config.hidden_size, eps=config.layer_norm_epsilon)
@@ -179,7 +179,7 @@ class QWenBlock(nn.Module):
class QWenModel(nn.Module): class QWenModel(nn.Module):
def __init__(self, config: QWenConfig, linear_method=None): def __init__(self, config: PretrainedConfig, linear_method=None):
super().__init__() super().__init__()
self.config = config self.config = config
self.vocab_size = config.vocab_size self.vocab_size = config.vocab_size
@@ -216,7 +216,7 @@ class QWenModel(nn.Module):
class QWenLMHeadModel(nn.Module): class QWenLMHeadModel(nn.Module):
def __init__(self, config: QWenConfig, linear_method=None): def __init__(self, config: PretrainedConfig, linear_method=None):
super().__init__() super().__init__()
self.config = config self.config = config
self.transformer = QWenModel(config, linear_method=linear_method) self.transformer = QWenModel(config, linear_method=linear_method)