#!/usr/bin/env python3 """ Extra gRPC server for MusicgenForConditionalGeneration models. """ from concurrent import futures import argparse import signal import sys import os import time import backend_pb2 import backend_pb2_grpc import grpc from scipy.io.wavfile import write as write_wav from transformers import AutoProcessor, MusicgenForConditionalGeneration _ONE_DAY_IN_SECONDS = 60 * 60 * 24 # If MAX_WORKERS are specified in the environment use it, otherwise default to 1 MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1')) # Implement the BackendServicer class with the service methods class BackendServicer(backend_pb2_grpc.BackendServicer): """ A gRPC servicer for the backend service. This class implements the gRPC methods for the backend service, including Health, LoadModel, and Embedding. """ def Health(self, request, context): """ A gRPC method that returns the health status of the backend service. Args: request: A HealthRequest object that contains the request parameters. context: A grpc.ServicerContext object that provides information about the RPC. Returns: A Reply object that contains the health status of the backend service. """ return backend_pb2.Reply(message=bytes("OK", 'utf-8')) def LoadModel(self, request, context): """ A gRPC method that loads a model into memory. Args: request: A LoadModelRequest object that contains the request parameters. context: A grpc.ServicerContext object that provides information about the RPC. Returns: A Result object that contains the result of the LoadModel operation. """ model_name = request.Model try: self.processor = AutoProcessor.from_pretrained(model_name) self.model = MusicgenForConditionalGeneration.from_pretrained(model_name) 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 TTS(self, request, context): model_name = request.model if model_name == "": return backend_pb2.Result(success=False, message="request.model is required") try: self.processor = AutoProcessor.from_pretrained(model_name) self.model = MusicgenForConditionalGeneration.from_pretrained(model_name) inputs = self.processor( text=[request.text], padding=True, return_tensors="pt", ) tokens = 256 # TODO get tokens from request? audio_values = self.model.generate(**inputs, max_new_tokens=tokens) print("[transformers-musicgen] TTS generated!", file=sys.stderr) sampling_rate = self.model.config.audio_encoder.sampling_rate write_wav(request.dst, rate=sampling_rate, data=audio_values[0, 0].numpy()) print("[transformers-musicgen] TTS saved to", request.dst, file=sys.stderr) print("[transformers-musicgen] TTS for", file=sys.stderr) print(request, file=sys.stderr) except Exception as err: return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}") return backend_pb2.Result(success=True) def serve(address): server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS)) backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server) server.add_insecure_port(address) server.start() print("[transformers-musicgen] Server started. Listening on: " + address, file=sys.stderr) # Define the signal handler function def signal_handler(sig, frame): print("[transformers-musicgen] 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() print(f"[transformers-musicgen] startup: {args}", file=sys.stderr) serve(args.addr)