mirror of
https://github.com/vale981/ray
synced 2025-03-06 02:21:39 -05:00
60d4d5e1aa
* Remove all __future__ imports from RLlib. * Remove (object) again from tf_run_builder.py::TFRunBuilder. * Fix 2xLINT warnings. * Fix broken appo_policy import (must be appo_tf_policy) * Remove future imports from all other ray files (not just RLlib). * Remove future imports from all other ray files (not just RLlib). * Remove future import blocks that contain `unicode_literals` as well. Revert appo_tf_policy.py to appo_policy.py (belongs to another PR). * Add two empty lines before Schedule class. * Put back __future__ imports into determine_tests_to_run.py. Fails otherwise on a py2/print related error.
74 lines
2.3 KiB
Python
74 lines
2.3 KiB
Python
import logging
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# Note: do not introduce unnecessary library dependencies here, e.g. gym.
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# This file is imported from the tune module in order to register RLlib agents.
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from ray.rllib.env.base_env import BaseEnv
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from ray.rllib.env.external_env import ExternalEnv
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from ray.rllib.env.multi_agent_env import MultiAgentEnv
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from ray.rllib.env.vector_env import VectorEnv
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from ray.rllib.evaluation.policy_graph import PolicyGraph
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from ray.rllib.evaluation.rollout_worker import RolloutWorker
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from ray.rllib.evaluation.tf_policy_graph import TFPolicyGraph
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from ray.rllib.policy.policy import Policy
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from ray.rllib.policy.sample_batch import SampleBatch
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from ray.rllib.policy.tf_policy import TFPolicy
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from ray.tune.registry import register_trainable
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def _setup_logger():
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logger = logging.getLogger("ray.rllib")
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handler = logging.StreamHandler()
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handler.setFormatter(
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logging.Formatter(
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"%(asctime)s\t%(levelname)s %(filename)s:%(lineno)s -- %(message)s"
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))
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logger.addHandler(handler)
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logger.propagate = False
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def _register_all():
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from ray.rllib.agents.trainer import Trainer, with_common_config
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from ray.rllib.agents.registry import ALGORITHMS, get_agent_class
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from ray.rllib.contrib.registry import CONTRIBUTED_ALGORITHMS
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for key in list(ALGORITHMS.keys()) + list(CONTRIBUTED_ALGORITHMS.keys(
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)) + ["__fake", "__sigmoid_fake_data", "__parameter_tuning"]:
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register_trainable(key, get_agent_class(key))
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def _see_contrib(name):
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"""Returns dummy agent class warning algo is in contrib/."""
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class _SeeContrib(Trainer):
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_name = "SeeContrib"
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_default_config = with_common_config({})
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def _setup(self, config):
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raise NameError(
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"Please run `contrib/{}` instead.".format(name))
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return _SeeContrib
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# also register the aliases minus contrib/ to give a good error message
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for key in list(CONTRIBUTED_ALGORITHMS.keys()):
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assert key.startswith("contrib/")
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alias = key.split("/", 1)[1]
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register_trainable(alias, _see_contrib(alias))
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_setup_logger()
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_register_all()
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__all__ = [
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"Policy",
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"PolicyGraph",
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"TFPolicy",
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"TFPolicyGraph",
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"RolloutWorker",
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"PolicyEvaluator",
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"SampleBatch",
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"BaseEnv",
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"MultiAgentEnv",
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"VectorEnv",
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"ExternalEnv",
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]
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