mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
104 lines
2.8 KiB
Python
104 lines
2.8 KiB
Python
import logging
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import os
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from ray.rllib.utils.filter_manager import FilterManager
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from ray.rllib.utils.filter import Filter
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from ray.rllib.utils.policy_client import PolicyClient
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from ray.rllib.utils.policy_server import PolicyServer
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from ray.tune.util import merge_dicts, deep_update
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logger = logging.getLogger(__name__)
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def renamed_class(cls, old_name):
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"""Helper class for renaming classes with a warning."""
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class DeprecationWrapper(cls):
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# note: **kw not supported for ray.remote classes
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def __init__(self, *args, **kw):
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new_name = cls.__module__ + "." + cls.__name__
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logger.warning("DeprecationWarning: {} has been renamed to {}. ".
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format(old_name, new_name) +
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"This will raise an error in the future.")
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cls.__init__(self, *args, **kw)
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DeprecationWrapper.__name__ = cls.__name__
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return DeprecationWrapper
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def add_mixins(base, mixins):
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"""Returns a new class with mixins applied in priority order."""
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mixins = list(mixins or [])
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while mixins:
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class new_base(mixins.pop(), base):
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pass
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base = new_base
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return base
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def renamed_agent(cls):
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"""Helper class for renaming Agent => Trainer with a warning."""
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class DeprecationWrapper(cls):
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def __init__(self, config=None, env=None, logger_creator=None):
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old_name = cls.__name__.replace("Trainer", "Agent")
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new_name = cls.__module__ + "." + cls.__name__
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logger.warning("DeprecationWarning: {} has been renamed to {}. ".
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format(old_name, new_name) +
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"This will raise an error in the future.")
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cls.__init__(self, config, env, logger_creator)
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DeprecationWrapper.__name__ = cls.__name__
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return DeprecationWrapper
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def try_import_tf():
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if "RLLIB_TEST_NO_TF_IMPORT" in os.environ:
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logger.warning("Not importing TensorFlow for test purposes")
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return None
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try:
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if "TF_CPP_MIN_LOG_LEVEL" not in os.environ:
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os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
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import tensorflow.compat.v1 as tf
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tf.logging.set_verbosity(tf.logging.ERROR)
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tf.disable_v2_behavior()
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return tf
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except ImportError:
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try:
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import tensorflow as tf
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return tf
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except ImportError:
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return None
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def try_import_tfp():
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if "RLLIB_TEST_NO_TF_IMPORT" in os.environ:
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logger.warning(
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"Not importing TensorFlow Probability for test purposes.")
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return None
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try:
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import tensorflow_probability as tfp
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return tfp
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except ImportError:
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return None
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__all__ = [
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"Filter",
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"FilterManager",
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"PolicyClient",
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"PolicyServer",
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"merge_dicts",
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"deep_update",
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"renamed_class",
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"try_import_tf",
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]
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