LocalAI/extra/grpc/autogptq/autogptq.py
Ettore Di Giacinto 3c8fc37c56 feat: Add UseFastTokenizer
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2023-08-08 01:10:05 +02:00

104 lines
3.4 KiB
Python
Executable File

#!/usr/bin/env python3
import grpc
from concurrent import futures
import time
import backend_pb2
import backend_pb2_grpc
import argparse
import signal
import sys
import os
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
from pathlib import Path
from transformers import AutoTokenizer
from transformers import TextGenerationPipeline
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
# Implement the BackendServicer class with the service methods
class BackendServicer(backend_pb2_grpc.BackendServicer):
def Health(self, request, context):
return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
def LoadModel(self, request, context):
try:
device = "cuda:0"
if request.Device != "":
device = request.Device
tokenizer = AutoTokenizer.from_pretrained(request.Model, use_fast=request.UseFastTokenizer)
model = AutoGPTQForCausalLM.from_quantized(request.Model,
model_basename=request.ModelBaseName,
use_safetensors=True,
trust_remote_code=True,
device=device,
use_triton=request.UseTriton,
quantize_config=None)
self.model = model
self.tokenizer = tokenizer
except Exception as err:
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
return backend_pb2.Result(message="Model loaded successfully", success=True)
def Predict(self, request, context):
penalty = 1.0
if request.Penalty != 0.0:
penalty = request.Penalty
tokens = 512
if request.Tokens != 0:
tokens = request.Tokens
top_p = 0.95
if request.TopP != 0.0:
top_p = request.TopP
# Implement Predict RPC
pipeline = TextGenerationPipeline(
model=self.model,
tokenizer=self.tokenizer,
max_new_tokens=tokens,
temperature=request.Temperature,
top_p=top_p,
repetition_penalty=penalty,
)
return backend_pb2.Result(message=bytes(pipeline(request.Prompt)[0]["generated_text"]))
def PredictStream(self, request, context):
# Implement PredictStream RPC
#for reply in some_data_generator():
# yield reply
# Not implemented yet
return self.Predict(request, context)
def serve(address):
server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
server.add_insecure_port(address)
server.start()
print("Server started. Listening on: " + address, file=sys.stderr)
# Define the signal handler function
def signal_handler(sig, frame):
print("Received termination signal. Shutting down...")
server.stop(0)
sys.exit(0)
# Set the signal handlers for SIGINT and SIGTERM
signal.signal(signal.SIGINT, signal_handler)
signal.signal(signal.SIGTERM, signal_handler)
try:
while True:
time.sleep(_ONE_DAY_IN_SECONDS)
except KeyboardInterrupt:
server.stop(0)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run the gRPC server.")
parser.add_argument(
"--addr", default="localhost:50051", help="The address to bind the server to."
)
args = parser.parse_args()
serve(args.addr)