file_path stringlengths 3 280 | file_language stringclasses 66
values | content stringlengths 1 1.04M | repo_name stringlengths 5 92 | repo_stars int64 0 154k | repo_description stringlengths 0 402 | repo_primary_language stringclasses 108
values | developer_username stringlengths 1 25 | developer_name stringlengths 0 30 | developer_company stringlengths 0 82 |
|---|---|---|---|---|---|---|---|---|---|
python/ray/tune/suggest/nevergrad.py | Python | import logging
import pickle
try:
import nevergrad as ng
except ImportError:
ng = None
from ray.tune.suggest.suggestion import SuggestionAlgorithm
logger = logging.getLogger(__name__)
class NevergradSearch(SuggestionAlgorithm):
"""A wrapper around Nevergrad to provide trial suggestions.
Requires Ne... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/suggest/search.py | Python | class SearchAlgorithm:
"""Interface of an event handler API for hyperparameter search.
Unlike TrialSchedulers, SearchAlgorithms will not have the ability
to modify the execution (i.e., stop and pause trials).
Trials added manually (i.e., via the Client API) will also notify
this class upon new eve... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/suggest/sigopt.py | Python | import copy
import os
import logging
import pickle
try:
import sigopt as sgo
except ImportError:
sgo = None
from ray.tune.suggest.suggestion import SuggestionAlgorithm
logger = logging.getLogger(__name__)
class SigOptSearch(SuggestionAlgorithm):
"""A wrapper around SigOpt to provide trial suggestions.
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/suggest/skopt.py | Python | import logging
import pickle
try:
import skopt as sko
except ImportError:
sko = None
from ray.tune.suggest.suggestion import SuggestionAlgorithm
logger = logging.getLogger(__name__)
def _validate_warmstart(parameter_names, points_to_evaluate,
evaluated_rewards):
if points_to_eval... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/suggest/suggestion.py | Python | import itertools
import copy
from ray.tune.error import TuneError
from ray.tune.experiment import convert_to_experiment_list
from ray.tune.config_parser import make_parser, create_trial_from_spec
from ray.tune.suggest.search import SearchAlgorithm
from ray.tune.suggest.variant_generator import format_vars, resolve_nes... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/suggest/variant_generator.py | Python | import copy
import logging
import numpy
import random
import types
from ray.tune import TuneError
from ray.tune.sample import sample_from
logger = logging.getLogger(__name__)
def generate_variants(unresolved_spec):
"""Generates variants from a spec (dict) with unresolved values.
There are two types of unre... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/sync_client.py | Python | import distutils
import distutils.spawn
import logging
import subprocess
import tempfile
import types
from shlex import quote
from ray.tune.error import TuneError
logger = logging.getLogger(__name__)
S3_PREFIX = "s3://"
GS_PREFIX = "gs://"
ALLOWED_REMOTE_PREFIXES = (S3_PREFIX, GS_PREFIX)
noop_template = ": {target... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/syncer.py | Python | import distutils
import logging
import os
import time
from shlex import quote
from ray import services
from ray.tune.cluster_info import get_ssh_key, get_ssh_user
from ray.tune.sync_client import (CommandBasedClient, get_sync_client,
get_cloud_sync_client, NOOP)
logger = logging.get... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/example.py | Python | # flake8: noqa
# This is an example quickstart for Tune.
# To connect to a cluster, uncomment below:
# import ray
# import argparse
# parser = argparse.ArgumentParser()
# parser.add_argument("--address")
# args = parser.parse_args()
# ray.init(address=args.address)
# __quick_start_begin__
import torch.optim as optim... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_actor_reuse.py | Python | import unittest
import ray
from ray.tune import Trainable, run_experiments
from ray.tune.error import TuneError
from ray.tune.schedulers.trial_scheduler import FIFOScheduler, TrialScheduler
class FrequentPausesScheduler(FIFOScheduler):
def on_trial_result(self, trial_runner, trial, result):
return TrialS... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_api.py | Python | import shutil
import copy
import os
import time
import unittest
from unittest.mock import patch
import ray
from ray.rllib import _register_all
from ray import tune
from ray.tune import DurableTrainable, Trainable, TuneError
from ray.tune import register_env, register_trainable, run_experiments
from ray.tune.schedule... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_automl_searcher.py | Python | import random
import unittest
from ray.tune import register_trainable
from ray.tune.automl import SearchSpace, DiscreteSpace, GridSearch
class AutoMLSearcherTest(unittest.TestCase):
def setUp(self):
def dummy_train(config, reporter):
reporter(timesteps_total=100, done=True)
register_... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_checkpoint_manager.py | Python | # coding: utf-8
import random
import sys
import unittest
from unittest.mock import patch
from ray.tune.checkpoint_manager import Checkpoint, CheckpointManager, logger
class CheckpointManagerTest(unittest.TestCase):
@staticmethod
def mock_result(i):
return {"i": i}
def checkpoint_manager(self, ke... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_cluster.py | Python | import inspect
import json
import time
import os
import pytest
import shutil
import sys
from unittest.mock import MagicMock, patch
import ray
from ray import tune
from ray.rllib import _register_all
from ray.cluster_utils import Cluster
from ray.test_utils import run_string_as_driver_nonblocking
from ray.tune import r... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_commands.py | Python | import click
import os
import pytest
import subprocess
import sys
import time
try:
from cStringIO import StringIO
except ImportError:
from io import StringIO
import ray
from ray import tune
from ray.rllib import _register_all
from ray.tune import commands
from ray.tune.result import CONFIG_PREFIX
class Captu... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_dependency.py | Python | #!/usr/bin/env python
import sys
import ray
from ray.tune import register_trainable, run_experiments
def f(config, reporter):
reporter(timesteps_total=1)
if __name__ == "__main__":
ray.init()
register_trainable("my_class", f)
run_experiments({
"test": {
"run": "my_class",
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_experiment.py | Python | import unittest
import ray
from ray.rllib import _register_all
from ray.tune import register_trainable
from ray.tune.experiment import Experiment, convert_to_experiment_list
from ray.tune.error import TuneError
class ExperimentTest(unittest.TestCase):
def tearDown(self):
ray.shutdown()
_register_... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_experiment_analysis.py | Python | import unittest
import shutil
import tempfile
import random
import os
import pandas as pd
import ray
from ray.tune import run, sample_from
from ray.tune.examples.async_hyperband_example import MyTrainableClass
class ExperimentAnalysisSuite(unittest.TestCase):
def setUp(self):
ray.init(local_mode=False)
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_experiment_analysis_mem.py | Python | import unittest
import shutil
import tempfile
import random
import pandas as pd
import ray
from ray.tune import run, Trainable, sample_from, Analysis, grid_search
from ray.tune.examples.async_hyperband_example import MyTrainableClass
class ExperimentAnalysisInMemorySuite(unittest.TestCase):
def setUp(self):
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_logger.py | Python | from collections import namedtuple
import unittest
import tempfile
import shutil
from ray.tune.logger import tf2_compat_logger, JsonLogger, CSVLogger, TBXLogger
Trial = namedtuple("MockTrial", ["evaluated_params", "trial_id"])
def result(t, rew):
return dict(
time_total_s=t,
episode_reward_mean=... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_progress_reporter.py | Python | import collections
import time
import unittest
from unittest.mock import MagicMock
from ray.tune.trial import Trial
from ray.tune.progress_reporter import _fair_filter_trials
class ProgressReporterTest(unittest.TestCase):
def mock_trial(self, status, start_time):
mock = MagicMock()
mock.status = ... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_ray_trial_executor.py | Python | # coding: utf-8
import json
import unittest
import ray
from ray.rllib import _register_all
from ray.tune import Trainable
from ray.tune.ray_trial_executor import RayTrialExecutor
from ray.tune.registry import _global_registry, TRAINABLE_CLASS
from ray.tune.suggest import BasicVariantGenerator
from ray.tune.trial impor... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_run_experiment.py | Python | import os
import unittest
import ray
from ray.rllib import _register_all
from ray.tune.result import TIMESTEPS_TOTAL
from ray.tune import Trainable, TuneError
from ray.tune import register_trainable, run_experiments
from ray.tune.logger import Logger
from ray.tune.experiment import Experiment
from ray.tune.trial impo... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_sync.py | Python | import glob
import os
import shutil
import sys
import tempfile
import unittest
from unittest.mock import patch
import ray
from ray.rllib import _register_all
from ray import tune
from ray.tune import TuneError
from ray.tune.syncer import CommandBasedClient
class TestSyncFunctionality(unittest.TestCase):
def set... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_track.py | Python | import os
import pandas as pd
import unittest
import ray
from ray import tune
from ray.tune import track
from ray.tune.result import EXPR_PARAM_FILE, EXPR_RESULT_FILE
def _check_json_val(fname, key, val):
with open(fname, "r") as f:
df = pd.read_json(f, typ="frame", lines=True)
return key in df.c... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_trainable_util.py | Python | import os
import pickle
import shutil
import unittest
from ray.tune.trainable import TrainableUtil
class TrainableUtilTest(unittest.TestCase):
def setUp(self):
self.checkpoint_dir = "/tmp/tune/MyTrainable123"
TrainableUtil.make_checkpoint_dir(self.checkpoint_dir)
def tearDown(self):
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_trial_runner.py | Python | import sys
import unittest
import ray
from ray.rllib import _register_all
from ray import tune
from ray.tune import TuneError, register_trainable
from ray.tune.ray_trial_executor import RayTrialExecutor
from ray.tune.schedulers import TrialScheduler, FIFOScheduler
from ray.tune.trial import Trial
from ray.tune.trial_... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_trial_runner_2.py | Python | import os
import sys
import unittest
from unittest.mock import patch
import ray
from ray.rllib import _register_all
from ray.tune import TuneError
from ray.tune.schedulers import FIFOScheduler
from ray.tune.result import DONE
from ray.tune.registry import _global_registry, TRAINABLE_CLASS
from ray.tune.trial import T... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_trial_runner_3.py | Python | import os
import shutil
import sys
import tempfile
import unittest
import ray
from ray.rllib import _register_all
from ray.tune import TuneError
from ray.tune.schedulers import TrialScheduler, FIFOScheduler
from ray.tune.experiment import Experiment
from ray.tune.trial import Trial
from ray.tune.trial_runner import T... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_trial_scheduler.py | Python | import os
import json
import random
import unittest
import numpy as np
import sys
import tempfile
import shutil
from unittest.mock import MagicMock
import ray
from ray.tune.result import TRAINING_ITERATION
from ray.tune.schedulers import (HyperBandScheduler, AsyncHyperBandScheduler,
Po... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_tune_restore.py | Python | # coding: utf-8
import os
import shutil
import tempfile
import unittest
import skopt
import numpy as np
from hyperopt import hp
from nevergrad.optimization import optimizerlib
import ray
from ray import tune
from ray.test_utils import recursive_fnmatch
from ray.rllib import _register_all
from ray.tune.suggest.hyperopt... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_tune_save_restore.py | Python | # coding: utf-8
import os
import pickle
import shutil
import tempfile
import unittest
import ray
from ray import tune
from ray.rllib import _register_all
from ray.tune import Trainable
class SerialTuneRelativeLocalDirTest(unittest.TestCase):
local_mode = True
prefix = "Serial"
class MockTrainable(Traina... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_tune_server.py | Python | import unittest
import socket
import subprocess
import json
import ray
from ray.rllib import _register_all
from ray.tune.trial import Trial, Resources
from ray.tune.web_server import TuneClient
from ray.tune.trial_runner import TrialRunner
def get_valid_port():
port = 4321
while True:
try:
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/test_var.py | Python | import os
import numpy as np
import unittest
import ray
from ray.rllib import _register_all
from ray import tune
from ray.tune.result import DEFAULT_RESULTS_DIR
from ray.tune.experiment import Experiment
from ray.tune.suggest import grid_search, BasicVariantGenerator
from ray.tune.suggest.suggestion import _MockSugge... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tests/tutorial.py | Python | # flake8: noqa
# Original Code: https://github.com/pytorch/examples/blob/master/mnist/main.py
# yapf: disable
# __tutorial_imports_begin__
import numpy as np
import torch
import torch.optim as optim
from torchvision import datasets
from ray import tune
from ray.tune import track
from ray.tune.schedulers import ASHASc... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/track/__init__.py | Python | import logging
from ray.tune.track.session import TrackSession
logger = logging.getLogger(__name__)
_session = None
def get_session():
global _session
if not _session:
raise ValueError("Session not detected. Try `track.init()`?")
return _session
def init(ignore_reinit_error=True, **session_kw... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/track/session.py | Python | import os
from datetime import datetime
from ray.tune.trial import Trial
from ray.tune.result import DEFAULT_RESULTS_DIR, TRAINING_ITERATION
from ray.tune.logger import UnifiedLogger, Logger
class _ReporterHook(Logger):
def __init__(self, tune_reporter):
self.tune_reporter = tune_reporter
def on_res... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/trainable.py | Python | from datetime import datetime
import copy
import io
import logging
import glob
import os
import pickle
import pandas as pd
from six import string_types
import shutil
import tempfile
import time
import uuid
import ray
from ray.tune.logger import UnifiedLogger
from ray.tune.result import (DEFAULT_RESULTS_DIR, TIME_THIS... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/trial.py | Python | import ray.cloudpickle as cloudpickle
import copy
from datetime import datetime
import logging
import shutil
import uuid
import time
import tempfile
import os
from numbers import Number
from ray.tune import TuneError
from ray.tune.checkpoint_manager import Checkpoint, CheckpointManager
from ray.tune.durable_trainable i... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/trial_executor.py | Python | # coding: utf-8
import logging
from ray.tune.trial import Trial, Checkpoint
from ray.tune.error import TuneError
logger = logging.getLogger(__name__)
class TrialExecutor:
"""Manages platform-specific details such as resource handling
and starting/stopping trials.
"""
def __init__(self, queue_trials... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/trial_runner.py | Python | import click
from datetime import datetime
import json
import logging
import os
import time
import traceback
import types
import ray.cloudpickle as cloudpickle
from ray.tune import TuneError
from ray.tune.progress_reporter import trial_progress_str
from ray.tune.ray_trial_executor import RayTrialExecutor
from ray.tune... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/tune.py | Python | import logging
import time
import six
from ray.tune.error import TuneError
from ray.tune.experiment import convert_to_experiment_list, Experiment
from ray.tune.analysis import ExperimentAnalysis
from ray.tune.suggest import BasicVariantGenerator
from ray.tune.trial import Trial, DEBUG_PRINT_INTERVAL
from ray.tune.trai... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/utils/__init__.py | Python | from ray.tune.utils.util import (deep_update, flatten_dict, get_pinned_object,
merge_dicts, pin_in_object_store, UtilMonitor,
validate_save_restore, warn_if_slow)
__all__ = [
"deep_update", "flatten_dict", "get_pinned_object", "merge_dicts",
"pi... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/utils/mock.py | Python | import os
from ray.rllib.agents.mock import _MockTrainer
from ray.tune import DurableTrainable
from ray.tune.sync_client import get_sync_client
from ray.tune.syncer import NodeSyncer
MOCK_REMOTE_DIR = "/tmp/mock-tune-remote/"
# Sync and delete templates that operate on local directories.
LOCAL_SYNC_TEMPLATE = "mkdir ... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/utils/util.py | Python | import copy
import logging
import threading
import time
from collections import defaultdict
from threading import Thread
import numpy as np
import ray
logger = logging.getLogger(__name__)
try:
import psutil
except ImportError:
psutil = None
try:
import GPUtil
except ImportError:
GPUtil = None
_pinn... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/utils/visual_utils.py | Python | import pandas as pd
from pandas.api.types import is_string_dtype, is_numeric_dtype
import logging
import os
import os.path as osp
import numpy as np
import json
from ray.tune.utils import flatten_dict
logger = logging.getLogger(__name__)
logger.warning("This module will be deprecated in a future version of Tune.")
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/tune/web_server.py | Python | import json
import logging
import threading
from urllib.parse import urljoin, urlparse
from http.server import SimpleHTTPRequestHandler, HTTPServer
import ray.cloudpickle as cloudpickle
from ray.tune import TuneError
from ray.tune.suggest import BasicVariantGenerator
from ray.utils import binary_to_hex, hex_to_binary... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/utils.py | Python | import binascii
import errno
import hashlib
import inspect
import logging
import numpy as np
import os
import six
import subprocess
import sys
import threading
import time
import uuid
import ray.gcs_utils
import ray.ray_constants as ray_constants
def _random_string():
id_hash = hashlib.sha1()
id_hash.update(... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/worker.py | Python | from contextlib import contextmanager
import colorama
import atexit
import faulthandler
import hashlib
import inspect
import io
import json
import logging
import os
import redis
import signal
from six.moves import queue
import sys
import threading
import time
import traceback
import random
# Ray modules
import ray.clo... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/ray/workers/default_worker.py | Python | import argparse
import json
import ray
import ray.actor
import ray.node
import ray.ray_constants as ray_constants
import ray.utils
from ray.parameter import RayParams
parser = argparse.ArgumentParser(
description=("Parse addresses for the worker "
"to connect to."))
parser.add_argument(
"--no... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
python/setup.py | Python | from itertools import chain
import os
import re
import shutil
import subprocess
import sys
from setuptools import setup, find_packages, Distribution
import setuptools.command.build_ext as _build_ext
# Ideally, we could include these files by putting them in a
# MANIFEST.in or using the package_data argument to setup,... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/__init__.py | Python | import logging
# Note: do not introduce unnecessary library dependencies here, e.g. gym.
# This file is imported from the tune module in order to register RLlib agents.
from ray.rllib.env.base_env import BaseEnv
from ray.rllib.env.external_env import ExternalEnv
from ray.rllib.env.multi_agent_env import MultiAgentEnv
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/__init__.py | Python | from ray.rllib.agents.trainer import Trainer, with_common_config
from ray.rllib.agents.agent import Agent
__all__ = ["Agent", "Trainer", "with_common_config"]
| zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/a3c/__init__.py | Python | from ray.rllib.agents.a3c.a3c import A3CTrainer, DEFAULT_CONFIG
from ray.rllib.agents.a3c.a2c import A2CTrainer
from ray.rllib.utils import renamed_agent
A2CAgent = renamed_agent(A2CTrainer)
A3CAgent = renamed_agent(A3CTrainer)
__all__ = [
"A2CAgent", "A3CAgent", "A2CTrainer", "A3CTrainer", "DEFAULT_CONFIG"
]
| zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/a3c/a2c.py | Python | from ray.rllib.agents.a3c.a3c import DEFAULT_CONFIG as A3C_CONFIG, \
validate_config, get_policy_class
from ray.rllib.optimizers import SyncSamplesOptimizer, MicrobatchOptimizer
from ray.rllib.agents.a3c.a3c_tf_policy import A3CTFPolicy
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.util... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/a3c/a3c.py | Python | from ray.rllib.agents.a3c.a3c_tf_policy import A3CTFPolicy
from ray.rllib.agents.trainer import with_common_config
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.optimizers import AsyncGradientsOptimizer
# yapf: disable
# __sphinx_doc_begin__
DEFAULT_CONFIG = with_common_config({
# Size... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/a3c/a3c_tf_policy.py | Python | """Note: Keep in sync with changes to VTraceTFPolicy."""
import ray
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.utils.explained_variance import explained_variance
from ray.rllib.evaluation.postprocessing import compute_advantages, \
Postprocessing
from ray.rllib.policy.tf_policy_template i... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/a3c/a3c_torch_policy.py | Python | import ray
from ray.rllib.evaluation.postprocessing import compute_advantages, \
Postprocessing
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.policy.torch_policy_template import build_torch_policy
from ray.rllib.utils.framework import try_import_torch
torch, nn = try_import_torch()
F = nn.fu... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/agent.py | Python | from ray.rllib.agents.trainer import Trainer
from ray.rllib.utils import renamed_agent
Agent = renamed_agent(Trainer)
| zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ars/__init__.py | Python | from ray.rllib.agents.ars.ars import (ARSTrainer, DEFAULT_CONFIG)
from ray.rllib.utils import renamed_agent
ARSAgent = renamed_agent(ARSTrainer)
__all__ = ["ARSAgent", "ARSTrainer", "DEFAULT_CONFIG"]
| zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ars/ars.py | Python | # Code in this file is copied and adapted from
# https://github.com/openai/evolution-strategies-starter and from
# https://github.com/modestyachts/ARS
from collections import namedtuple
import logging
import numpy as np
import time
import ray
from ray.rllib.agents import Trainer, with_common_config
from ray.rllib.ag... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ars/optimizers.py | Python | # Code in this file is copied and adapted from
# https://github.com/openai/evolution-strategies-starter.
import numpy as np
class Optimizer:
def __init__(self, policy):
self.policy = policy
self.dim = policy.num_params
self.t = 0
def update(self, globalg):
self.t += 1
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ars/policies.py | Python | # Code in this file is copied and adapted from
# https://github.com/openai/evolution-strategies-starter.
import gym
import numpy as np
import ray
import ray.experimental.tf_utils
from ray.rllib.evaluation.sampler import _unbatch_tuple_actions
from ray.rllib.utils.filter import get_filter
from ray.rllib.models import ... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ars/utils.py | Python | # Code in this file is copied and adapted from
# https://github.com/openai/evolution-strategies-starter.
import numpy as np
from ray.rllib.utils import try_import_tf
tf = try_import_tf()
def compute_ranks(x):
"""Returns ranks in [0, len(x))
Note: This is different from scipy.stats.rankdata, which returns r... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ddpg/__init__.py | Python | from ray.rllib.agents.ddpg.apex import ApexDDPGTrainer
from ray.rllib.agents.ddpg.ddpg import DDPGTrainer, DEFAULT_CONFIG
from ray.rllib.agents.ddpg.td3 import TD3Trainer
from ray.rllib.utils import renamed_agent
ApexDDPGAgent = renamed_agent(ApexDDPGTrainer)
DDPGAgent = renamed_agent(DDPGTrainer)
__all__ = [
"DD... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ddpg/apex.py | Python | from ray.rllib.agents.dqn.apex import APEX_TRAINER_PROPERTIES
from ray.rllib.agents.ddpg.ddpg import DDPGTrainer, \
DEFAULT_CONFIG as DDPG_CONFIG
from ray.rllib.utils import merge_dicts
APEX_DDPG_DEFAULT_CONFIG = merge_dicts(
DDPG_CONFIG, # see also the options in ddpg.py, which are also supported
{
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ddpg/ddpg.py | Python | from ray.rllib.agents.trainer import with_common_config
from ray.rllib.agents.dqn.dqn import GenericOffPolicyTrainer, \
update_worker_explorations
from ray.rllib.agents.ddpg.ddpg_policy import DDPGTFPolicy
from ray.rllib.utils.schedules import ConstantSchedule, LinearSchedule
# yapf: disable
# __sphinx_doc_begin__... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ddpg/ddpg_policy.py | Python | from gym.spaces import Box
import numpy as np
import ray
import ray.experimental.tf_utils
from ray.rllib.agents.dqn.dqn_policy import _postprocess_dqn
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.evaluation.metrics import LEARNER_STATS_KEY
from ray.rllib.models import ModelCatalog
from ray.rlli... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ddpg/noop_model.py | Python | from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.utils.annotations import override
from ray.rllib.utils import try_import_tf
tf = try_import_tf()
class NoopModel(TFModelV2):
"""Trivial model that just returns the obs flattened.
This is the model used if use_state_preprocessor=False."""
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ddpg/td3.py | Python | """A more stable successor to TD3.
By default, this uses a near-identical configuration to that reported in the
TD3 paper.
"""
from ray.rllib.agents.ddpg.ddpg import DDPGTrainer, \
DEFAULT_CONFIG as DDPG_CONFIG
from ray.rllib.utils import merge_dicts
TD3_DEFAULT_CONFIG = merge_dicts(
DDPG_CONFIG,
{
... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/dqn/__init__.py | Python | from ray.rllib.agents.dqn.apex import ApexTrainer
from ray.rllib.agents.dqn.dqn import DQNTrainer, SimpleQTrainer, DEFAULT_CONFIG
from ray.rllib.utils import renamed_agent
DQNAgent = renamed_agent(DQNTrainer)
ApexAgent = renamed_agent(ApexTrainer)
__all__ = [
"DQNAgent", "ApexAgent", "ApexTrainer", "DQNTrainer", ... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/dqn/apex.py | Python | from ray.rllib.agents.dqn.dqn import DQNTrainer, DEFAULT_CONFIG as DQN_CONFIG
from ray.rllib.optimizers import AsyncReplayOptimizer
from ray.rllib.utils import merge_dicts
# yapf: disable
# __sphinx_doc_begin__
APEX_DEFAULT_CONFIG = merge_dicts(
DQN_CONFIG, # see also the options in dqn.py, which are also support... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/dqn/distributional_q_model.py | Python | import numpy as np
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.utils import try_import_tf
tf = try_import_tf()
class DistributionalQModel(TFModelV2):
"""Extension of standard TFModel to provide distributional Q values.
It also supports options for noisy nets and parameter space nois... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/dqn/dqn.py | Python | import logging
from ray.rllib.agents.trainer import with_common_config
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.agents.dqn.dqn_policy import DQNTFPolicy
from ray.rllib.agents.dqn.simple_q_policy import SimpleQPolicy
from ray.rllib.optimizers import SyncReplayOptimizer
from ray.rllib.p... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/dqn/dqn_policy.py | Python | from gym.spaces import Discrete
import numpy as np
from scipy.stats import entropy
import ray
from ray.rllib.agents.dqn.distributional_q_model import DistributionalQModel
from ray.rllib.agents.dqn.simple_q_policy import ExplorationStateMixin, \
TargetNetworkMixin
from ray.rllib.policy.sample_batch import SampleBat... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/dqn/simple_q_model.py | Python | from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.utils import try_import_tf
tf = try_import_tf()
class SimpleQModel(TFModelV2):
"""Extension of standard TFModel to provide Q values.
Data flow:
obs -> forward() -> model_out
model_out -> get_q_values() -> Q(s, a)
Note t... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/dqn/simple_q_policy.py | Python | """Basic example of a DQN policy without any optimizations."""
from gym.spaces import Discrete
import logging
import ray
from ray.rllib.agents.dqn.simple_q_model import SimpleQModel
from ray.rllib.policy.policy import Policy
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.models import ModelCatal... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/es/__init__.py | Python | from ray.rllib.agents.es.es import (ESTrainer, DEFAULT_CONFIG)
from ray.rllib.utils import renamed_agent
ESAgent = renamed_agent(ESTrainer)
__all__ = ["ESAgent", "ESTrainer", "DEFAULT_CONFIG"]
| zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/es/es.py | Python | # Code in this file is copied and adapted from
# https://github.com/openai/evolution-strategies-starter.
from collections import namedtuple
import logging
import numpy as np
import time
import ray
from ray.rllib.agents import Trainer, with_common_config
from ray.rllib.agents.es import optimizers
from ray.rllib.agent... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/es/optimizers.py | Python | # Code in this file is copied and adapted from
# https://github.com/openai/evolution-strategies-starter.
import numpy as np
class Optimizer:
def __init__(self, pi):
self.pi = pi
self.dim = pi.num_params
self.t = 0
def update(self, globalg):
self.t += 1
step = self._co... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/es/policies.py | Python | # Code in this file is copied and adapted from
# https://github.com/openai/evolution-strategies-starter.
import gym
import numpy as np
import ray
import ray.experimental.tf_utils
from ray.rllib.evaluation.sampler import _unbatch_tuple_actions
from ray.rllib.models import ModelCatalog
from ray.rllib.utils.filter impor... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/es/utils.py | Python | # Code in this file is copied and adapted from
# https://github.com/openai/evolution-strategies-starter.
import numpy as np
from ray.rllib.utils import try_import_tf
tf = try_import_tf()
def compute_ranks(x):
"""Returns ranks in [0, len(x))
Note: This is different from scipy.stats.rankdata, which returns r... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/impala/__init__.py | Python | from ray.rllib.agents.impala.impala import ImpalaTrainer, DEFAULT_CONFIG
from ray.rllib.utils import renamed_agent
ImpalaAgent = renamed_agent(ImpalaTrainer)
__all__ = ["ImpalaAgent", "ImpalaTrainer", "DEFAULT_CONFIG"]
| zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/impala/impala.py | Python | from ray.rllib.agents.a3c.a3c_tf_policy import A3CTFPolicy
from ray.rllib.agents.impala.vtrace_policy import VTraceTFPolicy
from ray.rllib.agents.trainer import Trainer, with_common_config
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.optimizers import AsyncSamplesOptimizer
from ray.rllib.o... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/impala/vtrace.py | Python | # Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/impala/vtrace_policy.py | Python | """Adapted from A3CTFPolicy to add V-trace.
Keep in sync with changes to A3CTFPolicy and VtraceSurrogatePolicy."""
import numpy as np
import logging
import gym
import ray
from ray.rllib.agents.impala import vtrace
from ray.rllib.models.tf.tf_action_dist import Categorical
from ray.rllib.policy.sample_batch import Sa... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/impala/vtrace_test.py | Python | # Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/marwil/__init__.py | Python | from ray.rllib.agents.marwil.marwil import MARWILTrainer, DEFAULT_CONFIG
__all__ = ["MARWILTrainer", "DEFAULT_CONFIG"]
| zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/marwil/marwil.py | Python | from ray.rllib.agents.trainer import with_common_config
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.agents.marwil.marwil_policy import MARWILPolicy
from ray.rllib.optimizers import SyncBatchReplayOptimizer
# yapf: disable
# __sphinx_doc_begin__
DEFAULT_CONFIG = with_common_config({
#... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/marwil/marwil_policy.py | Python | import ray
from ray.rllib.models import ModelCatalog
from ray.rllib.evaluation.postprocessing import compute_advantages, \
Postprocessing
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.evaluation.metrics import LEARNER_STATS_KEY
from ray.rllib.utils.annotations import override
from ray.rllib.p... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/mock.py | Python | import os
import pickle
import numpy as np
from ray.tune import result as tune_result
from ray.rllib.agents.trainer import Trainer, with_common_config
class _MockTrainer(Trainer):
"""Mock trainer for use in tests"""
_name = "MockTrainer"
_default_config = with_common_config({
"mock_error": False... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/pg/__init__.py | Python | from ray.rllib.agents.pg.pg import PGTrainer, DEFAULT_CONFIG
from ray.rllib.agents.pg.pg_tf_policy import pg_tf_loss, \
post_process_advantages
from ray.rllib.agents.pg.pg_torch_policy import pg_torch_loss
__all__ = ["PGTrainer", "pg_tf_loss", "pg_torch_loss",
"post_process_advantages", "DEFAULT_CONFIG"... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/pg/pg.py | Python | from ray.rllib.agents.trainer import with_common_config
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.agents.pg.pg_tf_policy import PGTFPolicy
# yapf: disable
# __sphinx_doc_begin__
DEFAULT_CONFIG = with_common_config({
# No remote workers by default.
"num_workers": 0,
# Learni... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/pg/pg_tf_policy.py | Python | import ray
from ray.rllib.evaluation.postprocessing import Postprocessing, \
compute_advantages
from ray.rllib.policy.tf_policy_template import build_tf_policy
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.utils import try_import_tf
tf = try_import_tf()
def post_process_advantages(policy, ... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/pg/pg_torch_policy.py | Python | import ray
from ray.rllib.agents.pg.pg_tf_policy import post_process_advantages
from ray.rllib.evaluation.postprocessing import Postprocessing
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.policy.torch_policy_template import build_torch_policy
from ray.rllib.utils.framework import try_import_torc... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/pg/tests/test_pg.py | Python | import numpy as np
import unittest
import ray
import ray.rllib.agents.pg as pg
from ray.rllib.evaluation.postprocessing import Postprocessing
from ray.rllib.models.tf.tf_action_dist import Categorical
from ray.rllib.models.torch.torch_action_dist import TorchCategorical
from ray.rllib.policy.sample_batch import Sample... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ppo/__init__.py | Python | from ray.rllib.agents.ppo.ppo import PPOTrainer, DEFAULT_CONFIG
from ray.rllib.agents.ppo.appo import APPOTrainer
from ray.rllib.utils import renamed_agent
PPOAgent = renamed_agent(PPOTrainer)
__all__ = ["PPOAgent", "APPOTrainer", "PPOTrainer", "DEFAULT_CONFIG"]
| zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ppo/appo.py | Python | from ray.rllib.agents.ppo.appo_policy import AsyncPPOTFPolicy
from ray.rllib.agents.trainer import with_base_config
from ray.rllib.agents.ppo.ppo import update_kl
from ray.rllib.agents import impala
# yapf: disable
# __sphinx_doc_begin__
DEFAULT_CONFIG = with_base_config(impala.DEFAULT_CONFIG, {
# Whether to use V... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ppo/appo_policy.py | Python | """Adapted from VTraceTFPolicy to use the PPO surrogate loss.
Keep in sync with changes to VTraceTFPolicy."""
import numpy as np
import logging
import gym
from ray.rllib.agents.impala import vtrace
from ray.rllib.agents.impala.vtrace_policy import _make_time_major, \
BEHAVIOUR_LOGITS, clip_gradients, validat... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta | |
rllib/agents/ppo/ppo.py | Python | import logging
from ray.rllib.agents import with_common_config
from ray.rllib.agents.ppo.ppo_policy import PPOTFPolicy
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.optimizers import SyncSamplesOptimizer, LocalMultiGPUOptimizer
from ray.rllib.utils import try_import_tf
tf = try_import_tf(... | zhuohan123/hoplite-rllib | 3 | Python | zhuohan123 | Zhuohan Li | vLLM / Meta |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.