ray/rllib/utils/__init__.py

import logging
import os

from ray.rllib.utils.filter_manager import FilterManager
from ray.rllib.utils.filter import Filter
from ray.rllib.utils.policy_client import PolicyClient
from ray.rllib.utils.policy_server import PolicyServer
from ray.tune.util import merge_dicts, deep_update

logger = logging.getLogger(__name__)


def renamed_class(cls, old_name):
    """Helper class for renaming classes with a warning."""

    class DeprecationWrapper(cls):
        # note: **kw not supported for ray.remote classes
        def __init__(self, *args, **kw):
            new_name = cls.__module__ + "." + cls.__name__
            logger.warn("DeprecationWarning: {} has been renamed to {}. ".
                        format(old_name, new_name) +
                        "This will raise an error in the future.")
            cls.__init__(self, *args, **kw)

    DeprecationWrapper.__name__ = cls.__name__

    return DeprecationWrapper


def add_mixins(base, mixins):
    """Returns a new class with mixins applied in priority order."""

    mixins = list(mixins or [])

    while mixins:

        class new_base(mixins.pop(), base):
            pass

        base = new_base

    return base


def renamed_agent(cls):
    """Helper class for renaming Agent => Trainer with a warning."""

    class DeprecationWrapper(cls):
        def __init__(self, config=None, env=None, logger_creator=None):
            old_name = cls.__name__.replace("Trainer", "Agent")
            new_name = cls.__module__ + "." + cls.__name__
            logger.warn("DeprecationWarning: {} has been renamed to {}. ".
                        format(old_name, new_name) +
                        "This will raise an error in the future.")
            cls.__init__(self, config, env, logger_creator)

    DeprecationWrapper.__name__ = cls.__name__

    return DeprecationWrapper


def try_import_tf():
    if "RLLIB_TEST_NO_TF_IMPORT" in os.environ:
        logger.warning("Not importing TensorFlow for test purposes")
        return None

    try:
        if "TF_CPP_MIN_LOG_LEVEL" not in os.environ:
            os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
        import tensorflow.compat.v1 as tf
        tf.logging.set_verbosity(tf.logging.ERROR)
        tf.disable_v2_behavior()
        return tf
    except ImportError:
        try:
            import tensorflow as tf
            return tf
        except ImportError:
            return None


def try_import_tfp():
    if "RLLIB_TEST_NO_TF_IMPORT" in os.environ:
        logger.warning(
            "Not importing TensorFlow Probability for test purposes.")
        return None

    try:
        import tensorflow_probability as tfp
        return tfp
    except ImportError:
        return None


__all__ = [
    "Filter",
    "FilterManager",
    "PolicyClient",
    "PolicyServer",
    "merge_dicts",
    "deep_update",
    "renamed_class",
    "try_import_tf",
]