# Copyright 2021 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""
Implementation of Agent base class.
"""
import mindspore.nn as nn
[docs]class Agent(nn.Cell):
r"""
The base class for the Agent.
Args:
num_actor(int): The actor numbers in this agent.
actors(object): The actor instance.
learner(object): The learner instance.
Examples:
>>> from mindspore_rl.agent.learner import Learner
>>> from mindspore_rl.agent.actor import Actor
>>> from mindspore_rl.agent.agent import Agent
>>> actor_num = 1
>>> actors = Actor()
>>> learner = Learner()
>>> agent = Agent(actor_num, actors, learner)
>>> print(agent)
Agent<
(_actors): Actor<>
(_learner): Learner<>
>
"""
def __init__(self, num_actor, actors, learner):
super(Agent, self).__init__(auto_prefix=False)
self._actors = actors
self._num_actor = num_actor
self._learner = learner
[docs] def init(self):
"""
Initialize the agent, reset all the actors in agent.
"""
self.reset_all()
[docs] def reset_all(self):
"""
Reset the all the actors in agent, and return the reset `state`
and the flag `done`.
Returns:
- state (Tensor), the state of the reset environment in actor.
- done (Tensor), a false flag of `done`.
"""
state, done = self._actors.reset()
return state, done
[docs] def act(self):
"""
The act function interface.
"""
raise NotImplementedError("Method should be overridden by subclass.")
[docs] def learn(self, samples):
"""
The learn function interface.
Args:
samples (Tensor): the sample from replay buffer.
"""
raise NotImplementedError("Method should be overridden by subclass.")
[docs] def update(self):
"""
The update function interface.
"""
raise NotImplementedError("Method should be overridden by subclass.")
[docs] def env_setter(self, env):
"""
Set the agent environment for actors in agent.
Args:
env (object): the input environment.
"""
self._actors.env_setter(env)
@property
def actors(self):
"""
Get the instance of actors in the agent.
Returns:
actors (object), actors object created by class `Actor`.
"""
return self._actors
@property
def num_actor(self):
"""
Get the number of the actors of the agent.
Returns:
num_actor (int), actor numbers.
"""
return self._num_actor
@property
def learner(self):
"""
Get the instance of learner in the agent.
Returns:
learner (object), learner object created by class `Learner`.
"""
return self._learner