92 lines
2.5 KiB
Python
92 lines
2.5 KiB
Python
import pathlib
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from fastapi import APIRouter, HTTPException, Response, status as Status
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from pydantic import BaseModel
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from utils.rwkv import *
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from utils.torch import *
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import global_var
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import GPUtil
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router = APIRouter()
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def get_tokens_path(model_path: str):
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model_path = model_path.lower()
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default_tokens_path = (
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f"{pathlib.Path(__file__).parent.parent.resolve()}/rwkv_pip/20B_tokenizer.json"
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)
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if "raven" in model_path:
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return default_tokens_path
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elif "world" in model_path:
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return "rwkv_vocab_v20230424"
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else:
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return default_tokens_path
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class SwitchModelBody(BaseModel):
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model: str
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strategy: str
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customCuda: bool = False
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@router.post("/switch-model")
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def switch_model(body: SwitchModelBody, response: Response):
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if global_var.get(global_var.Model_Status) is global_var.ModelStatus.Loading:
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response.status_code = Status.HTTP_304_NOT_MODIFIED
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return
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global_var.set(global_var.Model_Status, global_var.ModelStatus.Offline)
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global_var.set(global_var.Model, None)
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torch_gc()
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os.environ["RWKV_CUDA_ON"] = "1" if body.customCuda else "0"
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global_var.set(global_var.Model_Status, global_var.ModelStatus.Loading)
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try:
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global_var.set(
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global_var.Model,
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RWKV(
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model=body.model,
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strategy=body.strategy,
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tokens_path=get_tokens_path(body.model),
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),
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)
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except Exception as e:
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print(e)
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global_var.set(global_var.Model_Status, global_var.ModelStatus.Offline)
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raise HTTPException(Status.HTTP_500_INTERNAL_SERVER_ERROR, "failed to load")
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if global_var.get(global_var.Model_Config) is None:
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global_var.set(
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global_var.Model_Config, get_rwkv_config(global_var.get(global_var.Model))
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)
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global_var.set(global_var.Model_Status, global_var.ModelStatus.Working)
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return "success"
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@router.post("/update-config")
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def update_config(body: ModelConfigBody):
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"""
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Will not update the model config immediately, but set it when completion called to avoid modifications during generation
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"""
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print(body)
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global_var.set(global_var.Model_Config, body)
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return "success"
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@router.get("/status")
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def status():
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gpus = GPUtil.getGPUs()
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if len(gpus) == 0:
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device_name = "CPU"
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else:
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device_name = gpus[0].name
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return {
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"status": global_var.get(global_var.Model_Status),
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"pid": os.getpid(),
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"device_name": device_name,
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}
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