# Copyright 2021-2022 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
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# ============================================================================
"""
Implementation of Actor base class.
"""
import mindspore.nn as nn
[docs]class Actor(nn.Cell):
r"""
Base class for all actors. Actor is a class used to interact with the environment and generate data.
Examples:
>>> from mindspore_rl.agent.actor import Actor
>>> from mindspore_rl.network import FullyConnectedNet
>>> from mindspore_rl.environment import GymEnvironment
>>> class MyActor(Actor):
... def __init__(self):
... super(MyActor, self).__init__()
... self.argmax = P.Argmax()
... self.actor_net = FullyConnectedNet(4, 10, 2)
... self.env = GymEnvironment({'name': 'CartPole-v0'})
>>> my_actor = MyActor()
>>> print(my_actor)
MyActor<
(actor_net): FullyConnectedNet<
(linear1): Dense<input_channels=4, output_channels=10, has_bias=True>
(linear2): Dense<input_channels=10, output_channels=2, has_bias=True>
(relu): ReLU<>
>
(environment): GymEnvironment<>
"""
def __init__(self):
super(Actor, self).__init__(auto_prefix=False)
[docs] def get_action(self, phase, params):
"""
get_action is the method used to obtain the action.
User will need to overload this function according to
the algorithm. But argument of this function should be
phase and params. This interface will not interact with
environment
Args:
phase (enum): A enumerate value states for init, collect, eval or other user-defined stage.
params (tuple(Tensor)): A tuple of tensor as input, which is used to calculate action
Returns:
tuple(Tensor), a tuple of tensor as output, containing actions and other data.
"""
raise NotImplementedError("Method should be overridden by subclass.")
[docs] def act(self, phase, params):
"""
The act function will take an enumerate value and observation or other data which is needed during
calculating the action. It will return a set of output which contains new observation, or other
experience. In this function, agent will interact with environment.
Args:
phase (enum): A enumerate value states for init, collect, eval or other user-defined stage.
params (tuple(Tensor)): A tuple of tensor as input, which is used to calculate action
Returns:
tuple(Tensor), a tuple of tensor as output, which states for experience data.
"""
raise NotImplementedError("Method should be overridden by subclass.")