Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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from typing import Callable, Optional
from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
# Function to call while waiting for a connection timeout.
# This should raise an exception if it needs to break from waiting for the timeout.
PollCallback = Callable[[], None]
class Communicator:
def __init__(self, worker_id=0, base_port=5005):
"""
Python side of the communication. Must be used in pair with the right Unity Communicator equivalent.
:int worker_id: Offset from base_port. Used for training multiple environments simultaneously.
:int base_port: Baseline port number to connect to Unity environment over. worker_id increments over this.
"""
def initialize(
self, inputs: UnityInputProto, poll_callback: Optional[PollCallback] = None
) -> UnityOutputProto:
"""
Used to exchange initialization parameters between Python and the Environment
:param inputs: The initialization input that will be sent to the environment.
:param poll_callback: Optional callback to be used while polling the connection.
:return: UnityOutput: The initialization output sent by Unity
"""
def exchange(
self, inputs: UnityInputProto, poll_callback: Optional[PollCallback] = None
) -> Optional[UnityOutputProto]:
"""
Used to send an input and receive an output from the Environment
:param inputs: The UnityInput that needs to be sent the Environment
:param poll_callback: Optional callback to be used while polling the connection.
:return: The UnityOutputs generated by the Environment
"""
def close(self):
"""
Sends a shutdown signal to the unity environment, and closes the connection.
"""