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move carla example too
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doc/source/rllib-env.rst

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OpenAI Gym
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----------
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RLlib uses Gym as its environment interface for single-agent training. For more information on how to implement a custom Gym environment, see the `gym.Env class definition <https://github.com/openai/gym/blob/master/gym/core.py>`__. You may also find the `SimpleCorridor <https://github.com/ray-project/ray/blob/master/python/ray/rllib/examples/custom_env.py>`__ and `Carla simulator <https://github.com/ray-project/ray/blob/master/examples/carla/env.py>`__ example env implementations useful as a reference.
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RLlib uses Gym as its environment interface for single-agent training. For more information on how to implement a custom Gym environment, see the `gym.Env class definition <https://github.com/openai/gym/blob/master/gym/core.py>`__. You may also find the `SimpleCorridor <https://github.com/ray-project/ray/blob/master/python/ray/rllib/examples/custom_env.py>`__ and `Carla simulator <https://github.com/ray-project/ray/blob/master/python/ray/rllib/examples/carla/env.py>`__ example env implementations useful as a reference.
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Performance
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~~~~~~~~~~~

doc/source/rllib-models.rst

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})
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For a full example of a custom model in code, see the `Carla RLlib model <https://github.com/ray-project/ray/blob/master/examples/carla/models.py>`__ and associated `training scripts <https://github.com/ray-project/ray/tree/master/examples/carla>`__. The ``CarlaModel`` class defined there operates over a composite (Tuple) observation space including both images and scalar measurements.
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For a full example of a custom model in code, see the `Carla RLlib model <https://github.com/ray-project/ray/blob/master/python/ray/rllib/examples/carla/models.py>`__ and associated `training scripts <https://github.com/ray-project/ray/tree/master/python/ray/rllib/examples/carla>`__. The ``CarlaModel`` class defined there operates over a composite (Tuple) observation space including both images and scalar measurements.
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Custom Preprocessors
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--------------------
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examples/carla/a3c_lane_keep.py renamed to python/ray/rllib/examples/carla/a3c_lane_keep.py

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"carla-a3c": {
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"run": "A3C",
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"env": "carla_env",
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"trial_resources": {"cpu": 4, "gpu": 1},
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"config": {
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"env_config": env_config,
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"model": {

examples/carla/dqn_lane_keep.py renamed to python/ray/rllib/examples/carla/dqn_lane_keep.py

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"carla-dqn": {
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"run": "DQN",
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"env": "carla_env",
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"trial_resources": {"cpu": 4, "gpu": 1},
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"config": {
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"env_config": env_config,
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"model": {
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"learning_starts": 1000,
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"schedule_max_timesteps": 100000,
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"gamma": 0.8,
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"tf_session_args": {
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"gpu_options": {"allow_growth": True},
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},
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},
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},
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})
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examples/carla/ppo_lane_keep.py renamed to python/ray/rllib/examples/carla/ppo_lane_keep.py

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"carla-ppo": {
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"run": "PPO",
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"env": "carla_env",
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"trial_resources": {"cpu": 4, "gpu": 1},
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"config": {
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"env_config": env_config,
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"model": {
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examples/carla/train_a3c.py renamed to python/ray/rllib/examples/carla/train_a3c.py

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"carla-a3c": {
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"run": "A3C",
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"env": "carla_env",
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"trial_resources": {"cpu": 5, "extra_gpu": 2},
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"config": {
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"env_config": env_config,
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"use_gpu_for_workers": True,

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