move (first pass)

docs/Learning-Environment-Executable.md

 'file_name' of the `UnityEnvironment`. For instance:
 
 ```python
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
 env = UnityEnvironment(file_name=<env_name>)
 ```
 

docs/Migrating.md

 * `UnitySDK/Assets/ML-Agents/Scripts/Communicator.cs` and its class `Communicator` have been renamed to `UnitySDK/Assets/ML-Agents/Scripts/ICommunicator.cs` and `ICommunicator` respectively.
 * The `SpaceType` Enums `discrete`, and `continuous` have been renamed to `Discrete` and `Continuous`.
 * We have removed the `Done` call as well as the capacity to set `Max Steps` on the Academy. Therefore an AcademyReset will never be triggered from C# (only from Python). If you want to reset the simulation after a fixed number of steps, or when an event in the simulation occurs, we recommend looking at our multi-agent example environments (such as BananaCollector). In our examples, groups of Agents can be reset through an "Area" that can reset groups of Agents.
-* The import for `mlagents.envs.UnityEnvironment` was removed. If you are using the Python API, change `from mlagents.envs import UnityEnvironment` to `from mlagents.envs.environment import UnityEnvironment`.
+* The import for `mlagents.envs.UnityEnvironment` was removed. If you are using the Python API, change `from mlagents_envs import UnityEnvironment` to `from mlagents_envs.environment import UnityEnvironment`.
 
 
 ## Migrating from ML-Agents toolkit v0.8 to v0.9

docs/Python-API.md

 of your Unity environment is 3DBall.app, in python, run:
 
 ```python
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
 env = UnityEnvironment(file_name="3DBall", base_port=5005, seed=1, side_channels=[])
 ```
 
 
 For example :
 ```python
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.side_channel.engine_configuration_channel import EngineConfigurationChannel
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.side_channel.engine_configuration_channel import EngineConfigurationChannel
 
 channel = EngineConfigurationChannel()
 
  * `list_properties` Returns a list of all the string identifiers of the properties
 
 ```python
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
 
 channel = FloatPropertiesChannel()
 

docs/Training-on-Amazon-Web-Service.md

 9. Test the instance setup from Python using:
 
     ```python
-    from mlagents.envs.environment import UnityEnvironment
+    from mlagents_envs.environment import UnityEnvironment
 
     env = UnityEnvironment(<your_env>)
     ```

docs/Training-on-Microsoft-Azure.md

 7. Test the instance setup from Python using:
 
 ```python
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
 
 env = UnityEnvironment(<your_env>)
 ```

gym-unity/gym_unity/envs/__init__.py

 import itertools
 import gym
 import numpy as np
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
 from gym import error, spaces
 
 

gym-unity/gym_unity/tests/test_gym.py

 
 from gym import spaces
 from gym_unity.envs import UnityEnv, UnityGymException
-from mlagents.envs.base_env import AgentGroupSpec, ActionType, BatchedStepResult
+from mlagents_envs.base_env import AgentGroupSpec, ActionType, BatchedStepResult
 
 
 @mock.patch("gym_unity.envs.UnityEnvironment")

ml-agents-envs/setup.py

 import sys
 from setuptools import setup
 from setuptools.command.install import install
-import mlagents.envs
+import mlagents_envs
 
 VERSION = mlagents.envs.__version__
 

ml-agents/mlagents/trainers/brain.py

 import numpy as np
 import io
 
-from mlagents.envs.communicator_objects.agent_info_pb2 import AgentInfoProto
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
-from mlagents.envs.communicator_objects.observation_pb2 import ObservationProto
-from mlagents.envs.timers import hierarchical_timer, timed
+from mlagents_envs.communicator_objects.agent_info_pb2 import AgentInfoProto
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.communicator_objects.observation_pb2 import ObservationProto
+from mlagents_envs.timers import hierarchical_timer, timed
 from typing import Dict, List, NamedTuple, Collection
 from PIL import Image
 

ml-agents/mlagents/trainers/brain_conversion_utils.py

 from mlagents.trainers.brain import BrainInfo, BrainParameters, CameraResolution
-from mlagents.envs.base_env import BatchedStepResult, AgentGroupSpec
-from mlagents.envs.exception import UnityEnvironmentException
+from mlagents_envs.base_env import BatchedStepResult, AgentGroupSpec
+from mlagents_envs.exception import UnityEnvironmentException
 import numpy as np
 from typing import List
 

ml-agents/mlagents/trainers/buffer.py

 import h5py
 from typing import List, BinaryIO
 
-from mlagents.envs.exception import UnityException
+from mlagents_envs.exception import UnityException
 
 
 class BufferException(UnityException):

ml-agents/mlagents/trainers/demo_loader.py

 from mlagents.trainers.buffer import AgentBuffer
 from mlagents.trainers.agent_processor import ProcessingBuffer
 from mlagents.trainers.brain import BrainParameters, BrainInfo
-from mlagents.envs.communicator_objects.agent_info_action_pair_pb2 import (
+from mlagents_envs.communicator_objects.agent_info_action_pair_pb2 import (
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
-from mlagents.envs.communicator_objects.demonstration_meta_pb2 import (
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.communicator_objects.demonstration_meta_pb2 import (
-from mlagents.envs.timers import timed, hierarchical_timer
+from mlagents_envs.timers import timed, hierarchical_timer
 from google.protobuf.internal.decoder import _DecodeVarint32  # type: ignore
 
 

ml-agents/mlagents/trainers/learn.py

 from typing import Any, Callable, Optional, List, NamedTuple
 
 import mlagents.trainers
-import mlagents.envs
+import mlagents_envs
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
-from mlagents.envs.base_env import BaseEnv
+from mlagents_envs.base_env import BaseEnv
-from mlagents.envs.side_channel.side_channel import SideChannel
-from mlagents.envs.side_channel.engine_configuration_channel import EngineConfig
+from mlagents_envs.side_channel.side_channel import SideChannel
+from mlagents_envs.side_channel.engine_configuration_channel import EngineConfig
 
 
 class CommandLineOptions(NamedTuple):

ml-agents/mlagents/trainers/ppo/multi_gpu_policy.py

 
 from tensorflow.python.client import device_lib
 from mlagents.trainers.brain import BrainParameters
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
 from mlagents.trainers.models import EncoderType, LearningRateSchedule
 from mlagents.trainers.ppo.policy import PPOPolicy
 from mlagents.trainers.ppo.models import PPOModel

ml-agents/mlagents/trainers/ppo/policy.py

 
 from mlagents.tf_utils import tf
 
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
 from mlagents.trainers.brain import BrainInfo, BrainParameters
 from mlagents.trainers.models import EncoderType, LearningRateSchedule
 from mlagents.trainers.ppo.models import PPOModel

ml-agents/mlagents/trainers/sac/policy.py

 import numpy as np
 from mlagents.tf_utils import tf
 
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
 from mlagents.trainers.brain import BrainInfo, BrainParameters
 from mlagents.trainers.models import EncoderType, LearningRateSchedule
 from mlagents.trainers.sac.models import SACModel

ml-agents/mlagents/trainers/sac/trainer.py

 
 from mlagents.trainers.brain import BrainInfo
 from mlagents.trainers.action_info import ActionInfoOutputs
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
 from mlagents.trainers.sac.policy import SACPolicy
 from mlagents.trainers.rl_trainer import RLTrainer, AllRewardsOutput
 

ml-agents/mlagents/trainers/simple_env_manager.py

 from typing import Dict, List
 
-from mlagents.envs.base_env import BaseEnv
+from mlagents_envs.base_env import BaseEnv
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
 from mlagents.trainers.brain_conversion_utils import (
     step_result_to_brain_info,
     group_spec_to_brain_parameters,

ml-agents/mlagents/trainers/subprocess_env_manager.py

 from typing import Dict, NamedTuple, List, Any, Optional, Callable, Set
 import cloudpickle
 
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.exception import UnityCommunicationException, UnityTimeOutException
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.exception import UnityCommunicationException, UnityTimeOutException
-from mlagents.envs.base_env import BaseEnv
+from mlagents_envs.base_env import BaseEnv
-from mlagents.envs.timers import (
+from mlagents_envs.timers import (
     TimerNode,
     timed,
     hierarchical_timer,
 from mlagents.trainers.brain import AllBrainInfo, BrainParameters
 from mlagents.trainers.action_info import ActionInfo
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
-from mlagents.envs.side_channel.engine_configuration_channel import (
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.side_channel.engine_configuration_channel import (
-from mlagents.envs.side_channel.side_channel import SideChannel
+from mlagents_envs.side_channel.side_channel import SideChannel
 from mlagents.trainers.brain_conversion_utils import (
     step_result_to_brain_info,
     group_spec_to_brain_parameters,

ml-agents/mlagents/trainers/tests/test_ppo.py

 from mlagents.trainers.rl_trainer import AllRewardsOutput
 from mlagents.trainers.components.reward_signals import RewardSignalResult
 from mlagents.trainers.brain import BrainParameters
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.mock_communicator import MockCommunicator
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.mock_communicator import MockCommunicator
 from mlagents.trainers.tests import mock_brain as mb
 from mlagents.trainers.tests.mock_brain import make_brain_parameters
 from mlagents.trainers.brain_conversion_utils import (

ml-agents/mlagents/trainers/tests/test_simple_rl.py

 
 from mlagents.trainers.trainer_controller import TrainerController
 from mlagents.trainers.trainer_util import TrainerFactory
-from mlagents.envs.base_env import (
+from mlagents_envs.base_env import (
     BaseEnv,
     AgentGroupSpec,
     BatchedStepResult,
 from mlagents.trainers.simple_env_manager import SimpleEnvManager
 from mlagents.trainers.sampler_class import SamplerManager
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
 
 BRAIN_NAME = __name__
 OBS_SIZE = 1

ml-agents/mlagents/trainers/tests/test_subprocess_env_manager.py

     EnvironmentResponse,
     StepResponse,
 )
-from mlagents.envs.base_env import BaseEnv
-from mlagents.envs.side_channel.engine_configuration_channel import EngineConfig
+from mlagents_envs.base_env import BaseEnv
+from mlagents_envs.side_channel.engine_configuration_channel import EngineConfig
 
 
 def mock_env_factory(worker_id):

ml-agents/mlagents/trainers/tf_policy.py

 import numpy as np
 from mlagents.tf_utils import tf
 
-from mlagents.envs.exception import UnityException
+from mlagents_envs.exception import UnityException
 from mlagents.trainers.policy import Policy
 from mlagents.trainers.action_info import ActionInfo
 from tensorflow.python.platform import gfile

ml-agents/mlagents/trainers/trainer.py

 from collections import deque, defaultdict
 
 from mlagents.trainers.action_info import ActionInfoOutputs
-from mlagents.envs.exception import UnityException
-from mlagents.envs.timers import set_gauge
+from mlagents_envs.exception import UnityException
+from mlagents_envs.timers import set_gauge
 from mlagents.trainers.trainer_metrics import TrainerMetrics
 from mlagents.trainers.tf_policy import TFPolicy
 from mlagents.trainers.brain import BrainParameters, BrainInfo

ml-agents/mlagents/trainers/trainer_controller.py

 from time import time
 
 from mlagents.trainers.env_manager import EnvManager, EnvironmentStep
-from mlagents.envs.exception import (
+from mlagents_envs.exception import (
-from mlagents.envs.timers import hierarchical_timer, get_timer_tree, timed
+from mlagents_envs.timers import hierarchical_timer, get_timer_tree, timed
 from mlagents.trainers.trainer import Trainer, TrainerMetrics
 from mlagents.trainers.meta_curriculum import MetaCurriculum
 from mlagents.trainers.trainer_util import TrainerFactory

notebooks/getting-started.ipynb

     "import numpy as np\n",
     "import sys\n",
     "\n",
-    "from mlagents.envs.environment import UnityEnvironment\n",
-    "from mlagents.envs.side_channel.engine_configuration_channel import EngineConfig, EngineConfigurationChannel\n",
+    "from mlagents_envs.environment import UnityEnvironment\n",
+    "from mlagents_envs.side_channel.engine_configuration_channel import EngineConfig, EngineConfigurationChannel\n",
     "\n",
     "%matplotlib inline\n",
     "\n",

ml-agents-envs/mlagents_envs/communicator.py

 import logging
 from typing import Optional
 
-from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutputProto
-from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInputProto
+from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
+from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
 
 logger = logging.getLogger("mlagents.envs")
 

ml-agents-envs/mlagents_envs/environment.py

 import subprocess
 from typing import Dict, List, Optional, Any
 
-from mlagents.envs.side_channel.side_channel import SideChannel
+from mlagents_envs.side_channel.side_channel import SideChannel
-from mlagents.envs.base_env import (
+from mlagents_envs.base_env import (
     BaseEnv,
     BatchedStepResult,
     AgentGroupSpec,
-from mlagents.envs.timers import timed, hierarchical_timer
-from mlagents.envs.exception import (
+from mlagents_envs.timers import timed, hierarchical_timer
+from mlagents_envs.exception import (
     UnityEnvironmentException,
     UnityCommunicationException,
     UnityActionException,
-from mlagents.envs.communicator_objects.command_pb2 import STEP, RESET
-from mlagents.envs.rpc_utils import (
+from mlagents_envs.communicator_objects.command_pb2 import STEP, RESET
+from mlagents_envs.rpc_utils import (
-from mlagents.envs.communicator_objects.unity_rl_input_pb2 import UnityRLInputProto
-from mlagents.envs.communicator_objects.unity_rl_output_pb2 import UnityRLOutputProto
-from mlagents.envs.communicator_objects.agent_action_pb2 import AgentActionProto
-from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutputProto
-from mlagents.envs.communicator_objects.unity_rl_initialization_input_pb2 import (
+from mlagents_envs.communicator_objects.unity_rl_input_pb2 import UnityRLInputProto
+from mlagents_envs.communicator_objects.unity_rl_output_pb2 import UnityRLOutputProto
+from mlagents_envs.communicator_objects.agent_action_pb2 import AgentActionProto
+from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
+from mlagents_envs.communicator_objects.unity_rl_initialization_input_pb2 import (
-from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInputProto
+from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
 
 from .rpc_communicator import RpcCommunicator
 from sys import platform

ml-agents-envs/mlagents_envs/mock_communicator.py

 from .communicator import Communicator
 from .environment import UnityEnvironment
-from mlagents.envs.communicator_objects.unity_rl_output_pb2 import UnityRLOutputProto
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
-from mlagents.envs.communicator_objects.unity_rl_initialization_output_pb2 import (
+from mlagents_envs.communicator_objects.unity_rl_output_pb2 import UnityRLOutputProto
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.communicator_objects.unity_rl_initialization_output_pb2 import (
-from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInputProto
-from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutputProto
-from mlagents.envs.communicator_objects.agent_info_pb2 import AgentInfoProto
-from mlagents.envs.communicator_objects.observation_pb2 import (
+from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
+from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
+from mlagents_envs.communicator_objects.agent_info_pb2 import AgentInfoProto
+from mlagents_envs.communicator_objects.observation_pb2 import (
-from mlagents.envs.communicator_objects.space_type_pb2 import discrete, continuous
+from mlagents_envs.communicator_objects.space_type_pb2 import discrete, continuous
 
 
 class MockCommunicator(Communicator):

ml-agents-envs/mlagents_envs/rpc_communicator.py

 from concurrent.futures import ThreadPoolExecutor
 
 from .communicator import Communicator
-from mlagents.envs.communicator_objects.unity_to_external_pb2_grpc import (
+from mlagents_envs.communicator_objects.unity_to_external_pb2_grpc import (
-from mlagents.envs.communicator_objects.unity_message_pb2 import UnityMessageProto
-from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInputProto
-from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutputProto
+from mlagents_envs.communicator_objects.unity_message_pb2 import UnityMessageProto
+from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
+from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
 from .exception import UnityTimeOutException, UnityWorkerInUseException
 
 logger = logging.getLogger("mlagents.envs")

ml-agents-envs/mlagents_envs/rpc_utils.py

-from mlagents.envs.base_env import AgentGroupSpec, ActionType, BatchedStepResult
-from mlagents.envs.timers import hierarchical_timer, timed
-from mlagents.envs.communicator_objects.agent_info_pb2 import AgentInfoProto
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.base_env import AgentGroupSpec, ActionType, BatchedStepResult
+from mlagents_envs.timers import hierarchical_timer, timed
+from mlagents_envs.communicator_objects.agent_info_pb2 import AgentInfoProto
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
 import logging
 import numpy as np
 import io

ml-agents-envs/mlagents_envs/tests/test_envs.py

 
 import numpy as np
 
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.base_env import BatchedStepResult
-from mlagents.envs.exception import UnityEnvironmentException, UnityActionException
-from mlagents.envs.mock_communicator import MockCommunicator
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.base_env import BatchedStepResult
+from mlagents_envs.exception import UnityEnvironmentException, UnityActionException
+from mlagents_envs.mock_communicator import MockCommunicator
 
 
 @mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")

ml-agents-envs/mlagents_envs/tests/test_rpc_communicator.py

 import pytest
 
-from mlagents.envs.rpc_communicator import RpcCommunicator
-from mlagents.envs.exception import UnityWorkerInUseException
+from mlagents_envs.rpc_communicator import RpcCommunicator
+from mlagents_envs.exception import UnityWorkerInUseException
 
 
 def test_rpc_communicator_checks_port_on_create():

ml-agents-envs/mlagents_envs/tests/test_rpc_utils.py

 from typing import List, Tuple
-from mlagents.envs.communicator_objects.agent_info_pb2 import AgentInfoProto
-from mlagents.envs.communicator_objects.observation_pb2 import (
+from mlagents_envs.communicator_objects.agent_info_pb2 import AgentInfoProto
+from mlagents_envs.communicator_objects.observation_pb2 import (
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
-from mlagents.envs.base_env import AgentGroupSpec, ActionType
+from mlagents_envs.base_env import AgentGroupSpec, ActionType
-from mlagents.envs.rpc_utils import (
+from mlagents_envs.rpc_utils import (
     agent_group_spec_from_proto,
     process_pixels,
     _process_visual_observation,

ml-agents-envs/mlagents_envs/tests/test_side_channel.py

 import struct
-from mlagents.envs.side_channel.side_channel import SideChannel
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
-from mlagents.envs.side_channel.raw_bytes_channel import RawBytesChannel
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.side_channel.side_channel import SideChannel
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.side_channel.raw_bytes_channel import RawBytesChannel
+from mlagents_envs.environment import UnityEnvironment
 
 
 class IntChannel(SideChannel):

ml-agents-envs/mlagents_envs/tests/test_timers.py

 from unittest import mock
 
-from mlagents.envs import timers
+from mlagents_envs import timers
 
 
 @timers.timed

ml-agents-envs/mlagents_envs/side_channel/engine_configuration_channel.py

-from mlagents.envs.side_channel.side_channel import SideChannel, SideChannelType
-from mlagents.envs.exception import UnityCommunicationException
+from mlagents_envs.side_channel.side_channel import SideChannel, SideChannelType
+from mlagents_envs.exception import UnityCommunicationException
 import struct
 from typing import NamedTuple
 

ml-agents-envs/mlagents_envs/side_channel/float_properties_channel.py

-from mlagents.envs.side_channel.side_channel import SideChannel, SideChannelType
+from mlagents_envs.side_channel.side_channel import SideChannel, SideChannelType
 import struct
 from typing import Dict, Tuple, Optional, List
 

ml-agents-envs/mlagents_envs/side_channel/raw_bytes_channel.py

-from mlagents.envs.side_channel.side_channel import SideChannel, SideChannelType
+from mlagents_envs.side_channel.side_channel import SideChannel, SideChannelType
 from typing import List
 
 

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_action_pair_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import agent_info_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2
-from mlagents.envs.communicator_objects import agent_action_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2
+from mlagents_envs.communicator_objects import agent_info_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2
+from mlagents_envs.communicator_objects import agent_action_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_action_pair_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.agent_action_pb2 import (
+from mlagents_envs.communicator_objects.agent_action_pb2 import (
-from mlagents.envs.communicator_objects.agent_info_pb2 import (
+from mlagents_envs.communicator_objects.agent_info_pb2 import (
     AgentInfoProto as mlagents___envs___communicator_objects___agent_info_pb2___AgentInfoProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import observation_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_observation__pb2
+from mlagents_envs.communicator_objects import observation_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_observation__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.observation_pb2 import (
+from mlagents_envs.communicator_objects.observation_pb2 import (
     ObservationProto as mlagents___envs___communicator_objects___observation_pb2___ObservationProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/brain_parameters_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import space_type_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_space__type__pb2
+from mlagents_envs.communicator_objects import space_type_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_space__type__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/brain_parameters_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.space_type_pb2 import (
+from mlagents_envs.communicator_objects.space_type_pb2 import (
     SpaceTypeProto as mlagents___envs___communicator_objects___space_type_pb2___SpaceTypeProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/unity_input_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import unity_rl_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__input__pb2
-from mlagents.envs.communicator_objects import unity_rl_initialization_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__input__pb2
+from mlagents_envs.communicator_objects import unity_rl_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__input__pb2
+from mlagents_envs.communicator_objects import unity_rl_initialization_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__input__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/unity_input_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.unity_rl_initialization_input_pb2 import (
+from mlagents_envs.communicator_objects.unity_rl_initialization_input_pb2 import (
-from mlagents.envs.communicator_objects.unity_rl_input_pb2 import (
+from mlagents_envs.communicator_objects.unity_rl_input_pb2 import (
     UnityRLInputProto as mlagents___envs___communicator_objects___unity_rl_input_pb2___UnityRLInputProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/unity_message_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import unity_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__output__pb2
-from mlagents.envs.communicator_objects import unity_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__input__pb2
-from mlagents.envs.communicator_objects import header_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_header__pb2
+from mlagents_envs.communicator_objects import unity_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__output__pb2
+from mlagents_envs.communicator_objects import unity_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__input__pb2
+from mlagents_envs.communicator_objects import header_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_header__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/unity_message_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.header_pb2 import (
+from mlagents_envs.communicator_objects.header_pb2 import (
-from mlagents.envs.communicator_objects.unity_input_pb2 import (
+from mlagents_envs.communicator_objects.unity_input_pb2 import (
-from mlagents.envs.communicator_objects.unity_output_pb2 import (
+from mlagents_envs.communicator_objects.unity_output_pb2 import (
     UnityOutputProto as mlagents___envs___communicator_objects___unity_output_pb2___UnityOutputProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/unity_output_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import unity_rl_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__output__pb2
-from mlagents.envs.communicator_objects import unity_rl_initialization_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__output__pb2
+from mlagents_envs.communicator_objects import unity_rl_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__output__pb2
+from mlagents_envs.communicator_objects import unity_rl_initialization_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__output__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/unity_output_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.unity_rl_initialization_output_pb2 import (
+from mlagents_envs.communicator_objects.unity_rl_initialization_output_pb2 import (
-from mlagents.envs.communicator_objects.unity_rl_output_pb2 import (
+from mlagents_envs.communicator_objects.unity_rl_output_pb2 import (
     UnityRLOutputProto as mlagents___envs___communicator_objects___unity_rl_output_pb2___UnityRLOutputProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_output_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import brain_parameters_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_brain__parameters__pb2
+from mlagents_envs.communicator_objects import brain_parameters_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_brain__parameters__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_output_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import (
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import (
     BrainParametersProto as mlagents___envs___communicator_objects___brain_parameters_pb2___BrainParametersProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_input_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import agent_action_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2
-from mlagents.envs.communicator_objects import command_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_command__pb2
+from mlagents_envs.communicator_objects import agent_action_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2
+from mlagents_envs.communicator_objects import command_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_command__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_input_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.agent_action_pb2 import (
+from mlagents_envs.communicator_objects.agent_action_pb2 import (
-from mlagents.envs.communicator_objects.command_pb2 import (
+from mlagents_envs.communicator_objects.command_pb2 import (
     CommandProto as mlagents___envs___communicator_objects___command_pb2___CommandProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_output_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import agent_info_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2
+from mlagents_envs.communicator_objects import agent_info_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_output_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.agent_info_pb2 import (
+from mlagents_envs.communicator_objects.agent_info_pb2 import (
     AgentInfoProto as mlagents___envs___communicator_objects___agent_info_pb2___AgentInfoProto,
 )
 

ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2.py

 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import unity_message_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__message__pb2
+from mlagents_envs.communicator_objects import unity_message_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__message__pb2
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2_grpc.py

 # Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
 import grpc
 
-from mlagents.envs.communicator_objects import unity_message_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__message__pb2
+from mlagents_envs.communicator_objects import unity_message_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__message__pb2
 
 
 class UnityToExternalProtoStub(object):