You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
182 lines
5.9 KiB
182 lines
5.9 KiB
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
from dataclasses import dataclass
|
|
from io import BytesIO
|
|
from typing import Any, Callable, Dict
|
|
|
|
import torch
|
|
import zmq
|
|
|
|
|
|
class TorchSerializer:
|
|
@staticmethod
|
|
def to_bytes(data: dict) -> bytes:
|
|
buffer = BytesIO()
|
|
torch.save(data, buffer)
|
|
return buffer.getvalue()
|
|
|
|
@staticmethod
|
|
def from_bytes(data: bytes) -> dict:
|
|
buffer = BytesIO(data)
|
|
obj = torch.load(buffer, weights_only=False)
|
|
return obj
|
|
|
|
|
|
@dataclass
|
|
class EndpointHandler:
|
|
handler: Callable
|
|
requires_input: bool = True
|
|
|
|
|
|
class BaseInferenceServer:
|
|
"""
|
|
An inference server that spin up a ZeroMQ socket and listen for incoming requests.
|
|
Can add custom endpoints by calling `register_endpoint`.
|
|
"""
|
|
|
|
def __init__(self, host: str = "*", port: int = 5555):
|
|
self.running = True
|
|
self.context = zmq.Context()
|
|
self.socket = self.context.socket(zmq.REP)
|
|
self.socket.bind(f"tcp://{host}:{port}")
|
|
self._endpoints: dict[str, EndpointHandler] = {}
|
|
|
|
# Register the ping endpoint by default
|
|
self.register_endpoint("ping", self._handle_ping, requires_input=False)
|
|
self.register_endpoint("kill", self._kill_server, requires_input=False)
|
|
|
|
def _kill_server(self):
|
|
"""
|
|
Kill the server.
|
|
"""
|
|
self.running = False
|
|
|
|
def _handle_ping(self) -> dict:
|
|
"""
|
|
Simple ping handler that returns a success message.
|
|
"""
|
|
return {"status": "ok", "message": "Server is running"}
|
|
|
|
def register_endpoint(self, name: str, handler: Callable, requires_input: bool = True):
|
|
"""
|
|
Register a new endpoint to the server.
|
|
|
|
Args:
|
|
name: The name of the endpoint.
|
|
handler: The handler function that will be called when the endpoint is hit.
|
|
requires_input: Whether the handler requires input data.
|
|
"""
|
|
self._endpoints[name] = EndpointHandler(handler, requires_input)
|
|
|
|
def run(self):
|
|
addr = self.socket.getsockopt_string(zmq.LAST_ENDPOINT)
|
|
print(f"Server is ready and listening on {addr}")
|
|
while self.running:
|
|
try:
|
|
message = self.socket.recv()
|
|
request = TorchSerializer.from_bytes(message)
|
|
endpoint = request.get("endpoint", "get_action")
|
|
|
|
if endpoint not in self._endpoints:
|
|
raise ValueError(f"Unknown endpoint: {endpoint}")
|
|
|
|
handler = self._endpoints[endpoint]
|
|
result = (
|
|
handler.handler(request.get("data", {}))
|
|
if handler.requires_input
|
|
else handler.handler()
|
|
)
|
|
self.socket.send(TorchSerializer.to_bytes(result))
|
|
except Exception as e:
|
|
print(f"Error in server: {e}")
|
|
import traceback
|
|
|
|
print(traceback.format_exc())
|
|
self.socket.send(b"ERROR")
|
|
|
|
|
|
class BaseInferenceClient:
|
|
def __init__(self, host: str = "localhost", port: int = 5555, timeout_ms: int = 15000):
|
|
self.context = zmq.Context()
|
|
self.host = host
|
|
self.port = port
|
|
self.timeout_ms = timeout_ms
|
|
self._init_socket()
|
|
|
|
def _init_socket(self):
|
|
"""Initialize or reinitialize the socket with current settings"""
|
|
self.socket = self.context.socket(zmq.REQ)
|
|
self.socket.connect(f"tcp://{self.host}:{self.port}")
|
|
|
|
def ping(self) -> bool:
|
|
try:
|
|
self.call_endpoint("ping", requires_input=False)
|
|
return True
|
|
except zmq.error.ZMQError:
|
|
self._init_socket() # Recreate socket for next attempt
|
|
return False
|
|
|
|
def kill_server(self):
|
|
"""
|
|
Kill the server.
|
|
"""
|
|
self.call_endpoint("kill", requires_input=False)
|
|
|
|
def call_endpoint(
|
|
self, endpoint: str, data: dict | None = None, requires_input: bool = True
|
|
) -> dict:
|
|
"""
|
|
Call an endpoint on the server.
|
|
|
|
Args:
|
|
endpoint: The name of the endpoint.
|
|
data: The input data for the endpoint.
|
|
requires_input: Whether the endpoint requires input data.
|
|
"""
|
|
request: dict = {"endpoint": endpoint}
|
|
if requires_input:
|
|
request["data"] = data
|
|
|
|
self.socket.send(TorchSerializer.to_bytes(request))
|
|
message = self.socket.recv()
|
|
if message == b"ERROR":
|
|
raise RuntimeError("Server error")
|
|
return TorchSerializer.from_bytes(message)
|
|
|
|
def __del__(self):
|
|
"""Cleanup resources on destruction"""
|
|
self.socket.close()
|
|
self.context.term()
|
|
|
|
|
|
class ExternalRobotInferenceClient(BaseInferenceClient):
|
|
"""
|
|
Client for communicating with the RealRobotServer
|
|
"""
|
|
|
|
def set_observation(self, observation: dict[str, Any]):
|
|
self.call_endpoint("set_observation", data=observation)
|
|
|
|
def get_action(self, time: float | None = None) -> Dict[str, Any]:
|
|
"""
|
|
Get the action from the server.
|
|
The exact definition of the observations is defined
|
|
by the policy, which contains the modalities configuration.
|
|
"""
|
|
return self.call_endpoint("get_action", data={"time": time})
|
|
|
|
def get_modality_config(self) -> dict[str, Any]:
|
|
return self.call_endpoint("get_modality_config")
|