mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
173f1d629a
Remove rllib dep: trainable is now a standalone abstract class that can be easily subclassed. Clean up hyperband: fix debug string and add an example. Remove YAML api / ScriptRunner: this was never really used. Move ray.init() out of run_experiments(): This provides greater flexibility and should be less confusing since there isn't an implicit init() done there. Note that this is a breaking API change for tune.
60 lines
1.7 KiB
Python
60 lines
1.7 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import ray
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from ray.tune import register_env, run_experiments
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from env import CarlaEnv, ENV_CONFIG
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from models import register_carla_model
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from scenarios import TOWN2_ONE_CURVE
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env_name = "carla_env"
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env_config = ENV_CONFIG.copy()
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env_config.update({
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"verbose": False,
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"x_res": 80,
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"y_res": 80,
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"discrete_actions": True,
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"server_map": "/Game/Maps/Town02",
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"reward_function": "custom",
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"scenarios": TOWN2_ONE_CURVE,
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})
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register_env(env_name, lambda env_config: CarlaEnv(env_config))
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register_carla_model()
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ray.init()
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run_experiments({
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"carla-dqn": {
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"run": "DQN",
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"env": "carla_env",
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"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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"custom_model": "carla",
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"custom_options": {
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"image_shape": [
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80, 80,
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lambda spec: spec.config.env_config.framestack * (
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spec.config.env_config.use_depth_camera and 1 or 3
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),
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],
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},
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"conv_filters": [
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[16, [8, 8], 4],
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[32, [4, 4], 2],
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[512, [10, 10], 1],
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],
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},
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"timesteps_per_iteration": 100,
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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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