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https://github.com/gryf/coach.git
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125c7ee38d
Main changes are detailed below: New features - * CARLA 0.7 simulator integration * Human control of the game play * Recording of human game play and storing / loading the replay buffer * Behavioral cloning agent and presets * Golden tests for several presets * Selecting between deep / shallow image embedders * Rendering through pygame (with some boost in performance) API changes - * Improved environment wrapper API * Added an evaluate flag to allow convenient evaluation of existing checkpoints * Improve frameskip definition in Gym Bug fixes - * Fixed loading of checkpoints for agents with more than one network * Fixed the N Step Q learning agent python3 compatibility
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
#
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# Copyright (c) 2017 Intel Corporation
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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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#
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from logger import *
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from utils import Enum, get_open_port
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from environments.gym_environment_wrapper import *
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from environments.doom_environment_wrapper import *
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from environments.carla_environment_wrapper import *
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class EnvTypes(Enum):
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Doom = "DoomEnvironmentWrapper"
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Gym = "GymEnvironmentWrapper"
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Carla = "CarlaEnvironmentWrapper"
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def create_environment(tuning_parameters):
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env_type_name, env_type = EnvTypes().verify(tuning_parameters.env.type)
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env = eval(env_type)(tuning_parameters)
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return env
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