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[2/N] executor pass the complete config to worker/modelrunner (#9938)

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Signed-off-by: youkaichao <youkaichao@gmail.com>
Co-authored-by: Nick Hill <nhill@redhat.com>
This commit is contained in:
youkaichao
2024-11-02 07:35:05 -07:00
committed by GitHub
parent 1d4cfe2be1
commit e893795443
44 changed files with 249 additions and 579 deletions
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50
vllm/v1/worker/gpu_worker.py
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@@ -6,10 +6,7 @@ from typing import TYPE_CHECKING, Optional, Tuple
import torch
import torch.distributed
from vllm.config import (CacheConfig, DeviceConfig, LoadConfig, LoRAConfig,
ModelConfig, ObservabilityConfig, ParallelConfig,
PromptAdapterConfig, SchedulerConfig,
SpeculativeConfig)
from vllm.config import CacheConfig, ModelConfig, ParallelConfig, VllmConfig
from vllm.distributed import (ensure_model_parallel_initialized,
init_distributed_environment,
set_custom_all_reduce)
@@ -30,48 +27,35 @@ class Worker:
def __init__(
self,
model_config: ModelConfig,
parallel_config: ParallelConfig,
scheduler_config: SchedulerConfig,
device_config: DeviceConfig,
cache_config: CacheConfig,
load_config: LoadConfig,
vllm_config: VllmConfig,
local_rank: int,
rank: int,
distributed_init_method: str,
speculative_config: Optional[SpeculativeConfig] = None,
lora_config: Optional[LoRAConfig] = None,
prompt_adapter_config: Optional[PromptAdapterConfig] = None,
observability_config: Optional[ObservabilityConfig] = None,
):
self.model_config = model_config
self.parallel_config = parallel_config
self.scheduler_config = scheduler_config
self.device_config = device_config
self.cache_config = cache_config
self.load_config = load_config
# TODO: use WorkerBase.__init__(self, vllm_config=vllm_config)
self.vllm_config = vllm_config
self.model_config = vllm_config.model_config
self.cache_config = vllm_config.cache_config
self.lora_config = vllm_config.lora_config
self.load_config = vllm_config.load_config
self.parallel_config = vllm_config.parallel_config
self.scheduler_config = vllm_config.scheduler_config
self.device_config = vllm_config.device_config
self.speculative_config = vllm_config.speculative_config
self.prompt_adapter_config = vllm_config.prompt_adapter_config
self.observability_config = vllm_config.observability_config
self.local_rank = local_rank
self.rank = rank
self.distributed_init_method = distributed_init_method
self.lora_config = lora_config
self.speculative_config = speculative_config
self.prompt_adapter_config = prompt_adapter_config
self.observability_config = observability_config
if self.model_config.trust_remote_code:
# note: lazy import to avoid importing torch before initializing
from vllm.utils import init_cached_hf_modules
init_cached_hf_modules()
self.model_runner = GPUModelRunner(
model_config,
parallel_config,
scheduler_config,
device_config,
cache_config,
load_config,
lora_config=lora_config,
)
self.model_runner = GPUModelRunner(vllm_config)
def initialize(self):
if self.device_config.device.type == "cuda":