How to use gym-unity - 10 common examples
To help you get started, we’ve selected a few gym-unity examples, based on popular ways it is used in public projects.
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Unity-Technologies / ml-agents / gym-unity / gym_unity / envs / unity_env.py View on Github 
def _check_agents(self, n_agents):
if not self._multiagent and n_agents > 1:
raise UnityGymException(
"The environment was launched as a single-agent environment, however"
"there is more than one agent in the scene."
)
elif self._multiagent and n_agents <= 1:
raise UnityGymException(
"The environment was launched as a mutli-agent environment, however"
"there is only one agent in the scene."
)
if self._n_agents is None:
self._n_agents = n_agents
logger.info("{} agents within environment.".format(n_agents))
elif self._n_agents != n_agents:
raise UnityGymException(
"The number of agents in the environment has changed since "
"initialization. This is not supported."def _check_agents(self, n_agents):
if not self._multiagent and n_agents > 1:
raise UnityGymException(
"The environment was launched as a single-agent environment, however"
"there is more than one agent in the scene."
)
elif self._multiagent and n_agents <= 1:
raise UnityGymException(
"The environment was launched as a mutli-agent environment, however"
"there is only one agent in the scene."
)
if self._n_agents is None:
self._n_agents = n_agents
logger.info("{} agents within environment.".format(n_agents))
elif self._n_agents != n_agents:
raise UnityGymException(
"The number of agents in the environment has changed since "
"initialization. This is not supported."def _check_agents(self, n_agents):
if not self._multiagent and n_agents > 1:
raise UnityGymException(
"The environment was launched as a single-agent environment, however"
"there is more than one agent in the scene.")
elif self._multiagent and n_agents <= 1:
raise UnityGymException(
"The environment was launched as a mutli-agent environment, however"
"there is only one agent in the scene.")
if self._n_agents is None:
self._n_agents = n_agents
logger.info("{} agents within environment.".format(n_agents))
elif self._n_agents != n_agents:
raise UnityGymException("The number of agents in the environment has changed since "
"initialization. This is not supported.")def _check_agents(self, n_agents):
if not self._multiagent and n_agents > 1:
raise UnityGymException(
"The environment was launched as a single-agent environment, however"
"there is more than one agent in the scene."
)
elif self._multiagent and n_agents <= 1:
raise UnityGymException(
"The environment was launched as a mutli-agent environment, however"
"there is only one agent in the scene."
)
if self._n_agents is None:
self._n_agents = n_agents
logger.info("{} agents within environment.".format(n_agents))
elif self._n_agents != n_agents:
raise UnityGymException(
"The number of agents in the environment has changed since "
"initialization. This is not supported."environment_filename, worker_id, no_graphics=no_graphics
)
self.name = self._env.academy_name
self.visual_obs = None
self._current_state = None
self._n_agents = None
self._multiagent = multiagent
self._flattener = None
self.game_over = (
False
) # Hidden flag used by Atari environments to determine if the game is over
self._allow_multiple_visual_obs = allow_multiple_visual_obs
# Check brain configuration
if len(self._env.brains) != 1:
raise UnityGymException(
"There can only be one brain in a UnityEnvironment "
"if it is wrapped in a gym."
)
if len(self._env.external_brain_names) <= 0:
raise UnityGymException(
"There are not any external brain in the UnityEnvironment"
)
self.brain_name = self._env.external_brain_names[0]
brain = self._env.brains[self.brain_name]
if use_visual and brain.number_visual_observations == 0:
raise UnityGymException(
"`use_visual` was set to True, however there are no"
" visual observations as part of this environment."
)def _check_agents(self, n_agents):
if not self._multiagent and n_agents > 1:
raise UnityGymException(
"The environment was launched as a single-agent environment, however"
"there is more than one agent in the scene."
)
elif self._multiagent and n_agents <= 1:
raise UnityGymException(
"The environment was launched as a mutli-agent environment, however"
"there is only one agent in the scene."
)
if self._n_agents is None:
self._n_agents = n_agents
logger.info("{} agents within environment.".format(n_agents))
elif self._n_agents != n_agents:
raise UnityGymException(
"The number of agents in the environment has changed since "
"initialization. This is not supported."def _check_agents(self, n_agents):
if not self._multiagent and n_agents > 1:
raise UnityGymException(
"The environment was launched as a single-agent environment, however"
"there is more than one agent in the scene."
)
elif self._multiagent and n_agents <= 1:
raise UnityGymException(
"The environment was launched as a mutli-agent environment, however"
"there is only one agent in the scene."
)
if self._n_agents is None:
self._n_agents = n_agents
logger.info("{} agents within environment.".format(n_agents))
elif self._n_agents != n_agents:
raise UnityGymException(
"The number of agents in the environment has changed since "
"initialization. This is not supported."def _check_agents(self, n_agents):
if not self._multiagent and n_agents > 1:
raise UnityGymException(
"The environment was launched as a single-agent environment, however"
"there is more than one agent in the scene."
)
elif self._multiagent and n_agents <= 1:
raise UnityGymException(
"The environment was launched as a mutli-agent environment, however"
"there is only one agent in the scene."
)
if self._n_agents is None:
self._n_agents = n_agents
logger.info("{} agents within environment.".format(n_agents))
elif self._n_agents != n_agents:
raise UnityGymException(
"The number of agents in the environment has changed since "
"initialization. This is not supported."def _check_agents(self, n_agents):
if not self._multiagent and n_agents > 1:
raise UnityGymException(
"The environment was launched as a single-agent environment, however"
"there is more than one agent in the scene."
)
elif self._multiagent and n_agents <= 1:
raise UnityGymException(
"The environment was launched as a mutli-agent environment, however"
"there is only one agent in the scene."
)
if self._n_agents is None:
self._n_agents = n_agents
logger.info("{} agents within environment.".format(n_agents))
elif self._n_agents != n_agents:
raise UnityGymException(
"The number of agents in the environment has changed since "
"initialization. This is not supported."self.game_over = False
self._allow_multiple_visual_obs = allow_multiple_visual_obs
# Check brain configuration
if len(self._env.get_agent_groups()) != 1:
raise UnityGymException(
"There can only be one brain in a UnityEnvironment "
"if it is wrapped in a gym."
)
self.brain_name = self._env.get_agent_groups()[0]
self.name = self.brain_name
self.group_spec = self._env.get_agent_group_spec(self.brain_name)
if use_visual and self._get_n_vis_obs() == 0:
raise UnityGymException(
"`use_visual` was set to True, however there are no"
" visual observations as part of this environment."
)
self.use_visual = self._get_n_vis_obs() >= 1 and use_visual
if not use_visual and uint8_visual:
logger.warning(
"`uint8_visual was set to true, but visual observations are not in use. "
"This setting will not have any effect."
)
else:
self.uint8_visual = uint8_visual
if self._get_n_vis_obs() > 1 and not self._allow_multiple_visual_obs:
logger.warning(
"The environment contains more than one visual observation. "gym-unity
Unity Machine Learning Agents Gym Interface
