mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 09:07:10 +08:00
547 lines
19 KiB
Python
547 lines
19 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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Inter-process communication utilities for FastDeploy server.
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This module provides:
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- ZeroMQ-based client/server communication
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- Shared memory utilities for numpy arrays
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- Process-safe task queues
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"""
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import os
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import threading
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import socket
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import json
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import time
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import numpy as np
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from multiprocessing.managers import (AcquirerProxy, BaseManager, ListProxy,
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Value, ValueProxy)
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from queue import Queue
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import zmq
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import time
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from multiprocessing.shared_memory import SharedMemory
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from typing import Optional, Dict, Tuple, List, Any
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from fastdeploy.utils import llm_logger
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def shared_memory_exists(name: str) -> bool:
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"""Check if a shared memory block with the given name exists.
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Args:
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name (str): The unique identifier of the shared memory block.
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Returns:
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bool: True if the shared memory exists, False otherwise.
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"""
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try:
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shm = SharedMemory(name=name, create=False)
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shm.close()
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return True
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except FileNotFoundError:
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return False
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except Exception as e:
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print(f"Unexpected error: {e}")
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return False
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class ZmqClient:
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"""ZeroMQ client for inter-process communication.
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Provides both client and server capabilities using ZeroMQ sockets.
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Supports JSON and Python object serialization.
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Attributes:
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context (zmq.Context): ZeroMQ context
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socket (zmq.Socket): Primary communication socket
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file_name (str): IPC socket file path
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router_path (str): Router IPC file path
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mutex (threading.Lock): Thread synchronization lock
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req_dict (dict): Request tracking dictionary
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router (zmq.Socket): Router socket for multi-client communication
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poller (zmq.Poller): Socket poller for event monitoring
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"""
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def __init__(self, name, mode):
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self.context = zmq.Context()
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self.socket = self.context.socket(mode)
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self.file_name = f"/dev/shm/{name}.socket"
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self.router_path = f"/dev/shm/router_{name}.ipc"
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self.mutex = threading.Lock()
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self.req_dict = dict()
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self.router = None
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self.poller = None
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def connect(self):
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"""Connect to the ZeroMQ server.
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Uses the IPC file path specified during initialization.
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"""
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self.socket.connect(f"ipc://{self.file_name}")
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def start_server(self):
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"""Start a ZeroMQ server.
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Binds to the IPC file path specified during initialization.
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Also initializes a poller for the socket.
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"""
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self.socket.bind(f"ipc://{self.file_name}")
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self.poller = zmq.Poller()
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self.poller.register(self.socket, zmq.POLLIN)
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def create_router(self):
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"""Create and bind a ROUTER socket.
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The router socket enables handling multiple client connections.
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Uses the router path specified during initialization.
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"""
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self.router = self.context.socket(zmq.ROUTER)
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self.router.bind(f"ipc://{self.router_path}")
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def send_json(self, data):
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"""Send JSON data through the socket.
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Args:
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data: JSON-serializable object to send
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"""
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self.socket.send_json(data)
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def recv_json(self):
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"""Receive JSON data from the socket.
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Returns:
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object: Deserialized JSON data
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"""
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return self.socket.recv_json()
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def send_pyobj(self, data):
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"""Send a Python object through the socket.
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Args:
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data: Pickle-serializable Python object
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"""
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self.socket.send_pyobj(data)
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def recv_pyobj(self):
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"""Receive a Python object from the socket.
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Returns:
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object: Deserialized Python object
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"""
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return self.socket.recv_pyobj()
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def send_multipart(self, req_id, data):
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"""Send a multipart message through the router socket.
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Args:
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req_id (str): Request identifier
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data: Data to send (will be JSON-serialized)
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Raises:
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RuntimeError: If router socket is not initialized
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"""
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if self.router is None:
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raise RuntimeError("Router socket not created. Call create_router() first.")
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while True:
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with self.mutex:
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if req_id not in self.req_dict:
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try:
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client, _, request_id = self.router.recv_multipart(flags=zmq.NOBLOCK)
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req_id_str = request_id.decode('utf-8')
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self.req_dict[req_id_str] = client
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except zmq.Again:
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continue
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else:
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break
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try:
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result = json.dumps(data.to_dict()).encode('utf-8')
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self.router.send_multipart([self.req_dict[req_id], b'', result], zmq.DONTWAIT)
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except Exception as e:
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llm_logger.error(f"Send result to zmq client failed: {e}")
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if data["finished"]:
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with self.mutex:
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self.req_dict.pop(data["request_id"], None)
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def send_multipart2(self, get_results_handler):
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"""Batch send multipart messages through the router socket.
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Args:
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get_results_handler (callable): Function that takes request IDs and
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returns a dict mapping request IDs to response data
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Raises:
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RuntimeError: If router socket is not initialized
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"""
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if self.router is None:
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raise RuntimeError("Router socket not created. Call create_router() first.")
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while True:
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with self.mutex:
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try:
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flags = 0 if len(self.req_dict) == 0 else zmq.NOBLOCK
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client, _, request_id = self.router.recv_multipart(flags=flags)
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req_id_str = request_id.decode('utf-8')
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self.req_dict[req_id_str] = client
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except zmq.Again:
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time.sleep(0.01)
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break
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req_dict_copy = dict()
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with self.mutex:
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req_dict_copy = self.req_dict.copy()
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finished_req = []
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req_ids = list(req_dict_copy.keys())
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results = get_results_handler(req_ids)
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for req_id, contents in results.items():
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client = req_dict_copy[req_id]
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for data in contents:
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if data["finished"]:
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finished_req.append(data["request_id"])
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result = json.dumps(data).encode('utf-8')
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try:
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self.router.send_multipart([client, b'', result], zmq.DONTWAIT)
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except Exception as e:
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llm_logger.error(f"Send result to zmq client2 failed: {e}")
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if len(finished_req) > 0:
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with self.mutex:
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for req_id in finished_req:
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self.req_dict.pop(req_id, None)
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def receive_json_once(self, block=False):
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"""Receive a single JSON message from the socket.
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Args:
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block (bool): Whether to block waiting for message
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Returns:
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tuple: (error_message, data) where data is None if no message received
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"""
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if self.socket is None or self.socket.closed:
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return "zmp socket has closed", None
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try:
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flags = zmq.NOBLOCK if not block else 0
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return None, self.socket.recv_json(flags=flags)
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except zmq.Again:
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return None, None
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except Exception as e:
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self.close()
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llm_logger.warning(f"{e}")
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return str(e), None
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def receive_pyobj_once(self, block=False):
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"""Receive a single Python object from the socket.
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Args:
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block (bool): Whether to block waiting for message
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Returns:
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tuple: (error_message, data) where data is None if no message received
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"""
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if self.socket is None or self.socket.closed:
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return "zmp socket has closed", None
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try:
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flags = zmq.NOBLOCK if not block else 0
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return None, self.socket.recv_pyobj(flags=flags)
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except zmq.Again:
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return None, None
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except Exception as e:
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self.close()
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llm_logger.warning(f"{e}")
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return str(e), None
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def _clear_ipc(self, name):
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"""Clean up IPC file.
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Args:
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name (str): Path to IPC file to remove
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"""
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if os.path.exists(name):
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try:
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os.remove(name)
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except OSError as e:
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llm_logger.warning(f"Failed to remove IPC file {name} - {e}")
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def close(self):
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"""Clean up all resources.
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Closes sockets, terminates context, and removes IPC files.
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Safe to call multiple times.
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"""
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if hasattr(self, 'socket') and not self.socket.closed:
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self.socket.close()
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if self.router is not None and not self.router.closed:
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self.router.close()
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if not self.context.closed:
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self.context.term()
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self._clear_ipc(self.file_name)
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self._clear_ipc(self.router_path)
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def __exit__(self, exc_type, exc_val, exc_tb):
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self.close()
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class IPCSignal:
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"""Shared memory wrapper for numpy array IPC.
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Provides process-safe shared memory access to numpy arrays.
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Attributes:
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shm (SharedMemory): Underlying shared memory block
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value (np.ndarray): Numpy array view of shared memory
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"""
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def __init__(self,
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name: str,
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array: np.ndarray,
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dtype: np.dtype,
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suffix: int = None,
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create: bool = True) -> None:
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"""Initialize or connect to a shared memory block.
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Args:
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name: Unique identifier for the shared memory block.
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array: Numpy array template defining shape and data type.
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dtype: Data type of the array (must match array.dtype).
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suffix: Suffix number that will be appended to the name.
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create: If True, creates new memory block; otherwise connects to existing.
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Raises:
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AssertionError: If create=True but memory already exists, or dtype mismatch.
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"""
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assert isinstance(array, np.ndarray), "Input must be a numpy array"
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assert dtype == array.dtype, "Specified dtype must match array dtype"
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# Set a suffix for name to avoid name conflict while there are multiple engine launched
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if suffix is not None:
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name = name + f".{suffix}"
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if create:
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assert not shared_memory_exists(
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name), f"ShareMemory: {name} already exists"
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self.shm = SharedMemory(create=True, size=array.nbytes, name=name)
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self.value: np.ndarray = np.ndarray(array.shape,
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dtype=array.dtype,
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buffer=self.shm.buf)
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self.value[:] = array # Initialize with input array data
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else:
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self.shm = SharedMemory(name=name)
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self.value: np.ndarray = np.ndarray(array.shape,
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dtype=array.dtype,
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buffer=self.shm.buf)
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def clear(self) -> None:
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"""Release system resources and unlink the shared memory block."""
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self.shm.close()
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self.shm.unlink()
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class EngineWorkerQueue:
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"""Process-safe task queue for engine-worker communication.
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Implements a multi-producer, multi-consumer queue using:
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- Multiprocessing managers for shared state
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- Thread locks for synchronization
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- Network sockets for cross-machine operation
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Attributes:
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address (tuple): (host, port) for network binding
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authkey (bytes): Authentication key
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num_client (int): Expected number of clients
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client_id (int): Unique client identifier (-1 for server)
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manager (BaseManager): Proxy manager instance
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tasks (ListProxy): Shared task list
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client_read_flag (ListProxy): Client read status flags
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lock (AcquirerProxy): Synchronization lock
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read_finish_flag (ValueProxy): Completion flag
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connected_client_counter (ValueProxy): Active client count
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"""
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def __init__(self,
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address: Tuple[str, int] = ('0.0.0.0', 5000),
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authkey: bytes = b'secret_key',
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is_server: bool = False,
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num_client: int = 1,
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client_id: int = -1) -> None:
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"""
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Initialize the communication queue.
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Args:
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address: Network address (IP, port) for the queue server
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authkey: Authentication key for secure connection
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is_server: Whether this instance acts as a server
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num_client: Total number of expected clients
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client_id: Unique identifier for client instances
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"""
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self.address: Tuple[str, int] = address
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self.authkey: bytes = authkey
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self.num_client: int = num_client
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self.client_id: int = client_id
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# Custom QueueManager for proxy object registration
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class QueueManager(BaseManager):
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pass
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if is_server:
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# Server-side initialization for shared resources
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self.tasks_init: List[Any] = list()
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self.client_read_flag_init: List[int] = [1] * self.num_client
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self.lock_init: threading.Lock = threading.Lock()
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self.read_finish_flag_init: Value = Value("i", 0)
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self.connected_client_counter_init: Value = Value("i", 0)
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# Register shared objects with proxy types
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QueueManager.register("get_tasks",
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callable=lambda: self.tasks_init,
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proxytype=ListProxy)
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QueueManager.register("get_client_read_flag",
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callable=lambda: self.client_read_flag_init,
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proxytype=ListProxy)
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QueueManager.register("get_lock",
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callable=lambda: self.lock_init,
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proxytype=AcquirerProxy)
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QueueManager.register("get_read_finish_flag",
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callable=lambda: self.read_finish_flag_init,
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proxytype=ValueProxy)
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QueueManager.register(
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"get_connected_client_counter",
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callable=lambda: self.connected_client_counter_init,
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proxytype=ValueProxy)
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self.manager: BaseManager = QueueManager(address=self.address,
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authkey=self.authkey)
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self.manager.start()
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else:
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# Client-side connection setup
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assert self.client_id >= 0 and self.client_id < self.num_client, (
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f"self.client_id={self.client_id}, self.num_client={self.num_client}"
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)
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QueueManager.register("get_tasks")
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QueueManager.register("get_client_read_flag")
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QueueManager.register("get_lock")
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QueueManager.register("get_read_finish_flag")
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QueueManager.register("get_connected_client_counter")
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self.manager = QueueManager(address=self.address,
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authkey=self.authkey)
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self._connect_with_retry()
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# Get proxy objects for shared resources
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self.tasks: ListProxy = self.manager.get_tasks()
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self.client_read_flag: ListProxy = self.manager.get_client_read_flag()
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self.lock: AcquirerProxy = self.manager.get_lock()
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self.read_finish_flag: ValueProxy = self.manager.get_read_finish_flag()
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self.connected_client_counter: ValueProxy = self.manager.get_connected_client_counter(
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)
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assert self.num_client == len(self.client_read_flag)
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if is_server:
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llm_logger.info(f"EngineWorkerQueue server started.")
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else:
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# Update client connection counter
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self.lock.acquire()
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self.connected_client_counter.set(
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self.connected_client_counter.get() + 1)
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self.lock.release()
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llm_logger.info((
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f"Connected EngineWorkerQueue client_id: {self.client_id}, number "
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f"of connected clients: {self.connected_client_counter.get()}"
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))
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def _connect_with_retry(self,
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max_retries: int = 5,
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interval: int = 3) -> None:
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"""Connect to server with retry logic.
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Args:
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max_retries (int): Maximum connection attempts. Default: 5
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interval (int): Seconds between retries. Default: 3
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Raises:
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ConnectionError: If all retries fail
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"""
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for _ in range(max_retries):
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try:
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self.manager.connect()
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return
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except ConnectionRefusedError:
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time.sleep(interval)
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raise ConnectionError(f"TaskQueue cannot connect {self.address}")
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def put_tasks(self, tasks: List[Any]) -> None:
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"""Add tasks to the shared queue.
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Waits until all clients have read previous tasks before adding new ones.
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Thread-safe operation.
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Args:
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tasks (list): Tasks to add to queue
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"""
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self.lock.acquire()
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while sum(self.client_read_flag) < self.num_client:
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self.lock.release()
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time.sleep(0.001)
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self.lock.acquire()
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self.tasks[:] = list()
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self.client_read_flag[:] = [0] * self.num_client
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self.tasks.append(tasks)
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self.lock.release()
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def get_tasks(self) -> Tuple[List[Any], bool]:
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"""Retrieve tasks from shared queue.
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Updates read status for this client.
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Thread-safe operation.
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Returns:
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tuple: (tasks, all_read) where:
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tasks (list): Retrieved tasks
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all_read (bool): True if all clients have read
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"""
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tasks: List[Any] = list()
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self.lock.acquire()
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tasks.extend(self.tasks)
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self.client_read_flag[self.client_id] = 1
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all_client_read: bool = np.sum(
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self.client_read_flag) == self.num_client
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if all_client_read:
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self.tasks[:] = list()
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self.lock.release()
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return tasks, all_client_read
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def num_tasks(self) -> int:
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"""Get current task count in queue.
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Thread-safe operation.
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Returns:
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int: Number of tasks currently in queue
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"""
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self.lock.acquire()
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total_num: int = len(self.tasks)
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self.lock.release()
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return total_num
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