code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
value |
|---|---|---|---|---|---|
from collections import defaultdict, deque
import datetime
import math
import time
import torch
import torch.distributed as dist
import errno
import os
class ConfusionMatrix(object):
def __init__(self, num_classes):
self.num_classes = num_classes
self.mat = None
def update(self, a, b):
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/util/sgd/torch/examples/segmentation/utils.py | 0.700895 | 0.335569 | utils.py | pypi |
import argparse
import logging
import json
import os
import time
from filelock import FileLock
from dataclasses import dataclass, field
from typing import Optional
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler
from tqdm import trange
import torch.distributed as di... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/util/sgd/torch/examples/transformers/transformers_example.py | 0.815416 | 0.19853 | transformers_example.py | pypi |
import glob
import logging
import os
from tqdm import tqdm
from filelock import FileLock
import numpy as np
import torch
from torch.utils.data import (DataLoader, SequentialSampler, TensorDataset)
from transformers import glue_processors as processors
from transformers import glue_compute_metrics as compute_metrics
f... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/util/sgd/torch/examples/transformers/utils.py | 0.790975 | 0.353958 | utils.py | pypi |
from ray.util.iter import ParallelIterator, from_iterators
class Dataset():
"""A simple Dataset abstraction for RaySGD.
This dataset is designed to work with RaySGD trainers (currently just
Torch) to provide support for streaming large external datasets, and built
in sharding.
.. code-block:: py... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/util/sgd/data/dataset.py | 0.881647 | 0.585486 | dataset.py | pypi |
import inspect
import os
from typing import Any, Callable, Dict, Iterable, Optional
import ray
import tqdm
from ray._private.worker import BaseContext
from .remote_as_local import remote_actor_as_local
from .utils import overload
def init(config: str = "ray", *args: Any, **kwargs: Any) -> Optional[BaseContext]:
... | /ray_ease-0.1.2-py3-none-any.whl/ray_ease/core.py | 0.922929 | 0.300309 | core.py | pypi |
import inspect
from typing import Any, Callable
import ray
from ray.actor import ActorClass
from .utils import memoize
@memoize
def remote_actor_as_local(base_cls: Callable[..., Any]) -> Callable[..., Any]:
"""Closure to give a base class from which the RemoteActorAsLocal wrapper will inherite.
:param base... | /ray_ease-0.1.2-py3-none-any.whl/ray_ease/remote_as_local.py | 0.897212 | 0.188324 | remote_as_local.py | pypi |
import ray.worker
import logging
from ray._private.client_mode_hook import client_mode_hook
from ray.runtime_env import RuntimeEnv
from ray.util.annotations import PublicAPI
logger = logging.getLogger(__name__)
@PublicAPI(stability="beta")
class RuntimeContext(object):
"""A class used for getting runtime context... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/runtime_context.py | 0.866345 | 0.245596 | runtime_context.py | pypi |
from typing import Any, Dict, Optional, Union
import uuid
import ray._private.gcs_utils as gcs_utils
class JobConfig:
"""A class used to store the configurations of a job.
Attributes:
num_java_workers_per_process (int): The number of java workers per
worker process.
jvm_options (... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/job_config.py | 0.870432 | 0.245153 | job_config.py | pypi |
import abc
import logging
import os
import shutil
import random
import time
import urllib
from collections import namedtuple
from typing import List, IO, Tuple
import ray
from ray.ray_constants import DEFAULT_OBJECT_PREFIX
from ray._raylet import ObjectRef
ParsedURL = namedtuple("ParsedURL", "base_url, offset, size")... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/external_storage.py | 0.886991 | 0.296578 | external_storage.py | pypi |
from collections import deque, OrderedDict
import numpy as np
from ray.rllib.utils import force_list
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
def unflatten(vector, shapes):
i = 0
arrays = []
for shape in shapes:
size = np.prod(shape, dtype=np.int)
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/tf_utils.py | 0.934238 | 0.547404 | tf_utils.py | pypi |
from typing import List, Union, Optional
from ray._private.client_mode_hook import client_mode_hook
from ray._private.gcs_utils import GcsClient
_initialized = False
global_gcs_client = None
def _internal_kv_reset():
global global_gcs_client, _initialized
global_gcs_client = None
_initialized = False
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/internal_kv.py | 0.940585 | 0.278628 | internal_kv.py | pypi |
import time
from typing import List, Iterable, Tuple, Callable, Any, Union
import ray
from ray.cluster_utils import Cluster
from ray import ObjectRef
# TODO(ekl) why doesn't TypeVar() deserialize properly in Ray?
# The type produced by the input reader function.
InType = Any
# The type produced by the output writer f... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/shuffle.py | 0.662469 | 0.465266 | shuffle.py | pypi |
import argparse
import time
import ray
import ray.experimental.internal_kv as ray_kv
@ray.remote
class StepActor:
def __init__(self, interval_s=1, total_steps=3):
self.interval_s = interval_s
self.stopped = False
self.current_step = 1
self.total_steps = total_steps
worker... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/job/example_job/demo_script.py | 0.61115 | 0.162181 | demo_script.py | pypi |
import ray
from ray.experimental.dag.py_obj_scanner import _PyObjScanner
from ray.experimental.dag.constants import DAGNODE_TYPE_KEY
from typing import (
Optional,
Union,
List,
Tuple,
Dict,
Any,
TypeVar,
Callable,
Set,
)
import uuid
import json
T = TypeVar("T")
class DAGNode:
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/dag/dag_node.py | 0.92657 | 0.383324 | dag_node.py | pypi |
import ray
import uuid
import io
import sys
# For python < 3.8 we need to explicitly use pickle5 to support protocol 5
if sys.version_info < (3, 8):
try:
import pickle5 as pickle # noqa: F401
except ImportError:
import pickle # noqa: F401
else:
import pickle # noqa: F401
from typing im... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/dag/py_obj_scanner.py | 0.601242 | 0.232463 | py_obj_scanner.py | pypi |
from typing import Any, Dict, List, Union
from ray.experimental.dag import DAGNode
from ray.experimental.dag.format_utils import get_dag_node_str
from ray.experimental.dag.constants import DAGNODE_TYPE_KEY
IN_CONTEXT_MANAGER = "__in_context_manager__"
class InputNode(DAGNode):
"""Ray dag node used in DAG buildi... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/dag/input_node.py | 0.937612 | 0.511229 | input_node.py | pypi |
import ray
from ray.experimental.dag.dag_node import DAGNode
from ray.experimental.dag.input_node import InputNode
from ray.experimental.dag.format_utils import get_dag_node_str
from ray.experimental.dag.constants import (
PARENT_CLASS_NODE_KEY,
PREV_CLASS_METHOD_CALL_KEY,
DAGNODE_TYPE_KEY,
)
from typing i... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/dag/class_node.py | 0.923135 | 0.229865 | class_node.py | pypi |
from typing import Any, Dict, List
import ray
from ray.experimental.dag.dag_node import DAGNode
from ray.experimental.dag.format_utils import get_dag_node_str
from ray.experimental.dag.constants import DAGNODE_TYPE_KEY
class FunctionNode(DAGNode):
"""Represents a bound task node in a Ray task DAG."""
def _... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/experimental/dag/function_node.py | 0.928644 | 0.332365 | function_node.py | pypi |
import argparse
import os
from pathlib import Path
import yaml
import ray
from ray.tune.config_parser import make_parser
from ray.tune.progress_reporter import CLIReporter, JupyterNotebookReporter
from ray.tune.result import DEFAULT_RESULTS_DIR
from ray.tune.resources import resources_to_json
from ray.tune.tune impor... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/train.py | 0.659844 | 0.161982 | train.py | pypi |
from abc import ABC
import numpy as np
from ray.rllib.models.modelv2 import restore_original_dimensions
from ray.rllib.models.preprocessors import get_preprocessor
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils.framework import try_import_torch
torch, nn = try_import_torch()
def ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/contrib/alpha_zero/models/custom_torch_models.py | 0.960943 | 0.353345 | custom_torch_models.py | pypi |
from copy import deepcopy
import numpy as np
class RankedRewardsBuffer:
def __init__(self, buffer_max_length, percentile):
self.buffer_max_length = buffer_max_length
self.percentile = percentile
self.buffer = []
def add_reward(self, reward):
if len(self.buffer) < self.buffer_... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/contrib/alpha_zero/core/ranked_rewards.py | 0.618896 | 0.201332 | ranked_rewards.py | pypi |
import argparse
import numpy as np
from scipy.stats import sem
import ray
from ray import tune
from ray.rllib.agents import slateq
from ray.rllib.agents import dqn
from ray.rllib.examples.env.recommender_system_envs_with_recsim import (
InterestEvolutionRecSimEnv,
InterestExplorationRecSimEnv,
LongTermSati... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/recommender_system_with_recsim_and_slateq.py | 0.6973 | 0.230822 | recommender_system_with_recsim_and_slateq.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.tune.registry import register_env
from ray.rllib.examples.env.repeat_after_me_env import RepeatAfterMeEnv
from ray.rllib.examples.env.repeat_initial_obs_env import RepeatInitialObsEnv
from ray.rllib.examples.models.rnn_model import RNNModel, TorchRNNM... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_rnn_model.py | 0.721841 | 0.19235 | custom_rnn_model.py | pypi |
import argparse
import os
import ray
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.examples.policy.bare_metal_policy_with_custom_view_reqs import (
BareMetalPolicyWithCustomViewReqs,
)
from ray import tune
def get_cli_args():
"""Create CLI parser and return parsed arguments"""
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/bare_metal_policy_with_custom_view_reqs.py | 0.712332 | 0.192634 | bare_metal_policy_with_custom_view_reqs.py | pypi |
import argparse
from gym.spaces import Box, Discrete
import numpy as np
from ray.rllib.examples.models.custom_model_api import (
DuelingQModel,
TorchDuelingQModel,
ContActionQModel,
TorchContActionQModel,
)
from ray.rllib.models.catalog import ModelCatalog, MODEL_DEFAULTS
from ray.rllib.policy.sample_b... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_model_api.py | 0.848125 | 0.333422 | custom_model_api.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.env.wrappers.unity3d_env import Unity3DEnv
from ray.rllib.utils.test_utils import check_learning_achieved
parser = argparse.ArgumentParser()
parser.add_argument(
"--env",
type=str,
default="3DBall",
choices=[
"3DBall",
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/unity3d_env_local.py | 0.695855 | 0.251246 | unity3d_env_local.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.offline import JsonReader, ShuffledInput, IOContext, InputReader
from ray.tune.registry import register_input
parser = argparse.ArgumentParser()
parser.add_argument(
"--run", type=str, default="CQL", help="The RLlib-registered algorithm to u... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_input_api.py | 0.784855 | 0.236021 | custom_input_api.py | pypi |
from abc import ABC
import ray
import numpy as np
from ray.rllib import Policy
from ray.rllib.agents import with_common_config
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.evaluation.worker_set import WorkerSet
from ray.rllib.execution.metric_ops import StandardMetricsReporting
from ray... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/random_parametric_agent.py | 0.894965 | 0.197386 | random_parametric_agent.py | pypi |
from typing import Dict
import argparse
import numpy as np
import os
import ray
from ray import tune
from ray.rllib.agents.callbacks import DefaultCallbacks
from ray.rllib.env import BaseEnv
from ray.rllib.evaluation import Episode, RolloutWorker
from ray.rllib.policy import Policy
from ray.rllib.policy.sample_batch i... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_metrics_and_callbacks.py | 0.903011 | 0.239644 | custom_metrics_and_callbacks.py | pypi |
import argparse
from gym.spaces import Discrete, Tuple
import logging
import os
import ray
from ray import tune
from ray.tune import function
from ray.rllib.examples.env.windy_maze_env import WindyMazeEnv, HierarchicalWindyMazeEnv
from ray.rllib.utils.test_utils import check_learning_achieved
parser = argparse.Argume... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/hierarchical_training.py | 0.698741 | 0.183703 | hierarchical_training.py | pypi |
from gym.spaces import Box, Discrete
import numpy as np
from rllib.models.tf.attention_net import TrXLNet
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
def bit_shift_generator(seq_length, shift, batch_size):
while True:
values = np.array([0.0, 1.0], dtype=np.float32)... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/attention_net_supervised.py | 0.920375 | 0.351367 | attention_net_supervised.py | pypi |
import argparse
import os
parser = argparse.ArgumentParser()
parser.add_argument(
"--run", type=str, default="PPO", help="The RLlib-registered algorithm to use."
)
parser.add_argument("--num-cpus", type=int, default=0)
parser.add_argument(
"--framework",
choices=["tf", "tf2", "tfe", "torch"],
default="... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/vizdoom_with_attention_net.py | 0.706292 | 0.157817 | vizdoom_with_attention_net.py | pypi |
import argparse
import gym
import os
import ray
from ray.rllib.agents.dqn import DQNTrainer, DQNTFPolicy, DQNTorchPolicy
from ray.rllib.agents.ppo import PPOTrainer, PPOTFPolicy, PPOTorchPolicy
from ray.rllib.examples.env.multi_agent import MultiAgentCartPole
from ray.tune.logger import pretty_print
from ray.tune.regi... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/multi_agent_two_trainers.py | 0.793666 | 0.224501 | multi_agent_two_trainers.py | pypi |
import argparse
import numpy as np
from gym.spaces import Discrete
import os
import ray
from ray import tune
from ray.rllib.agents.maml.maml_torch_policy import KLCoeffMixin as TorchKLCoeffMixin
from ray.rllib.agents.ppo.ppo import PPOTrainer
from ray.rllib.agents.ppo.ppo_tf_policy import (
PPOTFPolicy,
KLCoef... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/centralized_critic.py | 0.890366 | 0.220217 | centralized_critic.py | pypi |
import numpy as np
import os
from ray.rllib.agents import cql as cql
from ray.rllib.utils.framework import try_import_torch
torch, _ = try_import_torch()
if __name__ == "__main__":
# See rllib/tuned_examples/cql/pendulum-cql.yaml for comparison.
config = cql.CQL_DEFAULT_CONFIG.copy()
config["num_worker... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/offline_rl.py | 0.779406 | 0.246222 | offline_rl.py | pypi |
import argparse
from gym.spaces import Discrete, Box
import numpy as np
import os
from ray import tune
from ray.rllib.examples.env.random_env import RandomEnv
from ray.rllib.examples.models.mobilenet_v2_with_lstm_models import (
MobileV2PlusRNNModel,
TorchMobileV2PlusRNNModel,
)
from ray.rllib.models import M... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/mobilenet_v2_with_lstm.py | 0.786418 | 0.212436 | mobilenet_v2_with_lstm.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.agents.pg import PGTrainer
from ray.rllib.examples.env.matrix_sequential_social_dilemma import (
IteratedPrisonersDilemma,
)
parser = argparse.ArgumentParser()
parser.add_argument(
"--framework",
choices=["tf", "tf2", "tfe", "torch"]... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/iterated_prisoners_dilemma_env.py | 0.60964 | 0.158695 | iterated_prisoners_dilemma_env.py | pypi |
import argparse
from gym.spaces import Dict, Discrete, Tuple, MultiDiscrete
import os
import ray
from ray import tune
from ray.tune import register_env
from ray.rllib.env.multi_agent_env import ENV_STATE
from ray.rllib.examples.env.two_step_game import TwoStepGame
from ray.rllib.policy.policy import PolicySpec
from ra... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/two_step_game.py | 0.696887 | 0.255646 | two_step_game.py | pypi |
import argparse
import gym
import numpy as np
import ray
from gym.spaces import Box, Discrete
from ray import tune
from ray.rllib.env.multi_agent_env import make_multi_agent
parser = argparse.ArgumentParser()
parser.add_argument(
"--framework",
choices=["tf", "tf2", "tfe", "torch"],
default="tf",
hel... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env_rendering_and_recording.py | 0.920629 | 0.360433 | env_rendering_and_recording.py | pypi |
import argparse
import os
import random
import ray
from ray import tune
from ray.rllib.examples.env.multi_agent import MultiAgentCartPole
from ray.rllib.examples.models.shared_weights_model import (
SharedWeightsModel1,
SharedWeightsModel2,
TF2SharedWeightsModel,
TorchSharedWeightsModel,
)
from ray.rll... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/multi_agent_cartpole.py | 0.737536 | 0.186003 | multi_agent_cartpole.py | pypi |
import argparse
import gym
import os
import random
import ray
from ray import tune
from ray.rllib.agents.ppo import PPOTrainer
from ray.rllib.examples.env.multi_agent import MultiAgentCartPole
from ray.rllib.utils.framework import try_import_tf
from ray.rllib.utils.test_utils import check_learning_achieved
tf1, tf, t... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/restore_1_of_n_agents_from_checkpoint.py | 0.718989 | 0.170888 | restore_1_of_n_agents_from_checkpoint.py | pypi |
import argparse
import ray
from ray import tune
from ray.rllib.examples.env.gpu_requiring_env import GPURequiringEnv
from ray.rllib.utils.framework import try_import_tf, try_import_torch
from ray.rllib.utils.test_utils import check_learning_achieved
tf1, tf, tfv = try_import_tf()
torch, nn = try_import_torch()
parse... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/fractional_gpus.py | 0.737442 | 0.230952 | fractional_gpus.py | pypi |
import argparse
import os
from gym.spaces import Box, Discrete
import ray
from ray import tune
from ray.rllib.agents import ppo
from ray.rllib.examples.env.action_mask_env import ActionMaskEnv
from ray.rllib.examples.models.action_mask_model import (
ActionMaskModel,
TorchActionMaskModel,
)
from ray.tune.logge... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/action_masking.py | 0.791459 | 0.223758 | action_masking.py | pypi |
import argparse
import os
import numpy as np
import ray
from ray import tune
from ray.rllib.agents import ppo
from ray.rllib.examples.env.look_and_push import LookAndPush, OneHot
from ray.rllib.examples.env.repeat_after_me_env import RepeatAfterMeEnv
from ray.rllib.examples.env.repeat_initial_obs_env import RepeatIni... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/attention_net.py | 0.761804 | 0.247771 | attention_net.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.examples.env.mock_env import MockVectorEnv
from ray.rllib.utils.framework import try_import_tf, try_import_torch
from ray.rllib.utils.test_utils import check_learning_achieved
tf1, tf, tfv = try_import_tf()
torch, nn = try_import_torch()
parser... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_vector_env.py | 0.70253 | 0.218836 | custom_vector_env.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.agents import ppo
from ray.rllib.examples.env.correlated_actions_env import CorrelatedActionsEnv
from ray.rllib.examples.models.autoregressive_action_model import (
AutoregressiveActionModel,
TorchAutoregressiveActionModel,
)
from ray.rll... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/autoregressive_action_dist.py | 0.728845 | 0.199854 | autoregressive_action_dist.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.agents.ppo import PPOTrainer
from ray.rllib.examples.env.coin_game_non_vectorized_env import CoinGame, AsymCoinGame
parser = argparse.ArgumentParser()
parser.add_argument("--tf", action="store_true")
parser.add_argument("--stop-iters", type=int,... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/coin_game_env.py | 0.638272 | 0.223663 | coin_game_env.py | pypi |
import argparse
import numpy as np
import os
import ray
from ray import tune
def on_episode_start(info):
episode = info["episode"]
print("episode {} started".format(episode.episode_id))
episode.user_data["pole_angles"] = []
episode.hist_data["pole_angles"] = []
def on_episode_step(info):
episo... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_metrics_and_callbacks_legacy.py | 0.666605 | 0.34668 | custom_metrics_and_callbacks_legacy.py | pypi |
import argparse
import gym
import os
import ray
from ray.rllib.agents.callbacks import DefaultCallbacks
from ray.rllib.env.apis.task_settable_env import TaskSettableEnv
from ray.rllib.utils.test_utils import check_learning_achieved
from ray import tune
parser = argparse.ArgumentParser()
parser.add_argument(
"--ru... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/remote_base_env_with_custom_api.py | 0.827166 | 0.272257 | remote_base_env_with_custom_api.py | pypi |
import argparse
import os
from ray.rllib.examples.env.stateless_cartpole import StatelessCartPole
from ray.rllib.utils.test_utils import check_learning_achieved
parser = argparse.ArgumentParser()
parser.add_argument(
"--run", type=str, default="PPO", help="The RLlib-registered algorithm to use."
)
parser.add_argu... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/cartpole_lstm.py | 0.739611 | 0.185799 | cartpole_lstm.py | pypi |
import argparse
from gym.spaces import Dict, Tuple, Box, Discrete
import os
import ray
import ray.tune as tune
from ray.tune.registry import register_env
from ray.rllib.examples.env.nested_space_repeat_after_me_env import (
NestedSpaceRepeatAfterMeEnv,
)
from ray.rllib.utils.test_utils import check_learning_achiev... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/nested_action_spaces.py | 0.722821 | 0.205396 | nested_action_spaces.py | pypi |
import numpy as np
import ray
import ray.rllib.agents.ppo as ppo
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.models.catalog import ModelCatalog
from ray.rllib.utils.framework import try_import_torch
torch, _ = try_import_torch()
# __sphinx_doc_begin__
# The custom model that will b... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/lstm_auto_wrapping.py | 0.796925 | 0.271559 | lstm_auto_wrapping.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.agents.dqn.distributional_q_tf_model import DistributionalQTFModel
from ray.rllib.models import ModelCatalog
from ray.rllib.models.tf.misc import normc_initializer
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.tf.vis... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_keras_model.py | 0.877536 | 0.178383 | custom_keras_model.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.examples.models.batch_norm_model import (
BatchNormModel,
KerasBatchNormModel,
TorchBatchNormModel,
)
from ray.rllib.models import ModelCatalog
from ray.rllib.utils.framework import try_import_tf
from ray.rllib.utils.test_utils impor... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/batch_norm_model.py | 0.71423 | 0.160069 | batch_norm_model.py | pypi |
from ray.rllib.agents.callbacks import DefaultCallbacks
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.evaluation.postprocessing import Postprocessing
from ray.rllib.utils.annotations import override
import numpy as np
class MyCallbacks(DefaultCallbacks):
@override(DefaultCallbacks)
def ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/compute_adapted_gae_on_postprocess_trajectory.py | 0.928141 | 0.378201 | compute_adapted_gae_on_postprocess_trajectory.py | pypi |
import argparse
import os
import ray
from ray import tune
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.agents.dqn.dqn import DEFAULT_CONFIG as DQN_CONFIG
from ray.rllib.agents.dqn.dqn_tf_policy import DQNTFPolicy
from ray.rllib.agents.dqn.dqn_torch_policy import DQNTorchPolicy
from ray.rl... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/two_trainer_workflow.py | 0.771672 | 0.162115 | two_trainer_workflow.py | pypi |
import argparse
import numpy as np
import ray
from ray import tune
from ray.rllib.utils.filter import Filter
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
parser = argparse.ArgumentParser()
parser.add_argument(
"--run", type=str, default="PPO", help="The RLlib-registered algo... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_observation_filters.py | 0.849191 | 0.261254 | custom_observation_filters.py | pypi |
import argparse
import numpy as np
import ray
from ray.rllib.agents.ppo import PPOTrainer
from ray.rllib.examples.env.stateless_cartpole import StatelessCartPole
from ray.rllib.examples.models.trajectory_view_utilizing_models import (
FrameStackingCartPoleModel,
TorchFrameStackingCartPoleModel,
)
from ray.rlli... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/trajectory_view_api.py | 0.768733 | 0.248366 | trajectory_view_api.py | pypi |
import argparse
import os
from pettingzoo.classic import rps_v2
import random
import ray
from ray import tune
from ray.rllib.agents.pg import PGTrainer, PGTFPolicy, PGTorchPolicy
from ray.rllib.agents.registry import get_trainer_class
from ray.rllib.env import PettingZooEnv
from ray.rllib.examples.policy.rock_paper_sc... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/rock_paper_scissors_multiagent.py | 0.727007 | 0.266257 | rock_paper_scissors_multiagent.py | pypi |
import argparse
from pathlib import Path
import os
import ray
from ray import tune
from ray.rllib.examples.models.custom_loss_model import (
CustomLossModel,
TorchCustomLossModel,
)
from ray.rllib.models import ModelCatalog
from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID
from ray.rllib.utils.framew... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/custom_model_loss_and_metrics.py | 0.731922 | 0.201185 | custom_model_loss_and_metrics.py | pypi |
from gym.spaces import Dict
from ray.rllib.models.tf.fcnet import FullyConnectedNetwork
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.models.torch.fcnet import FullyConnectedNetwork as TorchFC
from ray.rllib.utils.framework import try_... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/action_mask_model.py | 0.957883 | 0.562537 | action_mask_model.py | pypi |
from gym.spaces import Discrete, Tuple
from ray.rllib.models.tf.misc import normc_initializer
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.torch.misc import normc_initializer as normc_init_torch
from ray.rllib.models.torch.misc import SlimFC
from ray.rllib.models.torch.torch_modelv2 impor... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/autoregressive_action_model.py | 0.945789 | 0.375964 | autoregressive_action_model.py | pypi |
from gym.spaces import Box
from ray.rllib.agents.dqn.distributional_q_tf_model import DistributionalQTFModel
from ray.rllib.agents.dqn.dqn_torch_model import DQNTorchModel
from ray.rllib.models.tf.fcnet import FullyConnectedNetwork
from ray.rllib.models.torch.fcnet import FullyConnectedNetwork as TorchFC
from ray.rlli... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/parametric_actions_model.py | 0.950903 | 0.392395 | parametric_actions_model.py | pypi |
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.tf.fcnet import FullyConnectedNetwork as TFFCNet
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.models.torch.fcnet import FullyConnectedNetwork as TorchFCNet
from ray.rllib.utils.framework import try_import_tf, try_... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/simple_rpg_model.py | 0.954742 | 0.342957 | simple_rpg_model.py | pypi |
import numpy as np
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.torch.misc import SlimFC
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils.annotations import override
from ray.rllib.utils.framework import try_im... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/shared_weights_model.py | 0.918192 | 0.328799 | shared_weights_model.py | pypi |
import random
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.fcnet import FullyConnectedNetwork
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.utils.annotations import override
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
class EagerM... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/eager_model.py | 0.899226 | 0.376709 | eager_model.py | pypi |
from collections import OrderedDict
import gym
from typing import Union, Dict, List, Tuple
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.models.torch.misc import SlimFC
from ray.rllib.utils.framework import try_import_torch
from ray.rllib.utils.typing import ModelConfigDict, TensorType
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/neural_computer.py | 0.933172 | 0.542197 | neural_computer.py | pypi |
from ray.rllib.models.tf.tf_action_dist import Categorical, ActionDistribution
from ray.rllib.models.torch.torch_action_dist import (
TorchCategorical,
TorchDistributionWrapper,
)
from ray.rllib.utils.framework import try_import_tf, try_import_torch
tf1, tf, tfv = try_import_tf()
torch, nn = try_import_torch()... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/autoregressive_action_dist.py | 0.942546 | 0.480235 | autoregressive_action_dist.py | pypi |
import numpy as np
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.recurrent_net import RecurrentNetwork
from ray.rllib.models.torch.misc import SlimFC
from ray.rllib.models.torch.recurrent_net import RecurrentNetwork as TorchRNN
from ray.rllib.utils.annotations import override
from ray.rllib.uti... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/mobilenet_v2_with_lstm_models.py | 0.910749 | 0.397734 | mobilenet_v2_with_lstm_models.py | pypi |
import numpy as np
import pickle
import ray
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.misc import normc_initializer
from ray.rllib.models.tf.recurrent_net import RecurrentNetwork
from ray.rllib.utils.annotations import override
from ray.rllib.utils.framework import try_import_tf
tf1, tf, t... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/rnn_spy_model.py | 0.926329 | 0.303396 | rnn_spy_model.py | pypi |
import numpy as np
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.utils.framework import try_import_tf, try_import_torch
tf1, tf, tfv = try_import_tf()
torch, nn = try_import_torch()
class RNNModel(tf.keras.models.Model if tf else object):
"""Example of using the Keras functional API to de... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/modelv3.py | 0.904702 | 0.326352 | modelv3.py | pypi |
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.torch.misc import SlimFC
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.policy.view_requirement import ViewRequirement
from ray.rllib.utils.framework import try_import_tf, try_import_torch
from ray.rllib.utils.tf_ut... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/trajectory_view_utilizing_models.py | 0.962303 | 0.407982 | trajectory_view_utilizing_models.py | pypi |
import numpy as np
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.preprocessors import get_preprocessor
from ray.rllib.models.tf.recurrent_net import RecurrentNetwork
from ray.rllib.models.torch.recurrent_net import RecurrentNetwork as TorchRNN
from ray.rllib.utils.annotations import override
from ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/rnn_model.py | 0.912309 | 0.465205 | rnn_model.py | pypi |
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.torch.misc import SlimFC
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils.annotations import override
from ray.rllib.utils.framework import try_import_tf, try_import_... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/models/fast_model.py | 0.926678 | 0.390592 | fast_model.py | pypi |
import numpy as np
from gym.spaces import Box
from ray.rllib.policy import Policy
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.policy.view_requirement import ViewRequirement
from ray.rllib.utils.annotations import override
from ray.rllib.utils.typing import ModelWeights
class BareMetalPolicyW... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/policy/bare_metal_policy_with_custom_view_reqs.py | 0.884595 | 0.415907 | bare_metal_policy_with_custom_view_reqs.py | pypi |
import gym
import numpy as np
import random
from ray.rllib.policy.policy import Policy
from ray.rllib.policy.view_requirement import ViewRequirement
ROCK = 0
PAPER = 1
SCISSORS = 2
class AlwaysSameHeuristic(Policy):
"""Pick a random move and stick with it for the entire episode."""
def __init__(self, *args,... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/policy/rock_paper_scissors_dummies.py | 0.800458 | 0.205675 | rock_paper_scissors_dummies.py | pypi |
from gym.spaces import Box
import numpy as np
from ray.rllib.examples.policy.random_policy import RandomPolicy
from ray.rllib.policy.policy import Policy
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.policy.view_requirement import ViewRequirement
from ray.rllib.utils.annotations import override
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/policy/episode_env_aware_policy.py | 0.915493 | 0.238883 | episode_env_aware_policy.py | pypi |
import random
import numpy as np
from gym.spaces import Box
from ray.rllib.policy.policy import Policy
from ray.rllib.utils.annotations import override
from ray.rllib.utils.typing import ModelWeights
class RandomPolicy(Policy):
"""Hand-coded policy that returns random actions."""
def __init__(self, *args, ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/policy/random_policy.py | 0.862294 | 0.214157 | random_policy.py | pypi |
from ray.rllib.env.wrappers.dm_control_wrapper import DMCEnv
"""
8 Environments from Deepmind Control Suite
"""
def acrobot_swingup(
from_pixels=True, height=64, width=64, frame_skip=2, channels_first=True
):
return DMCEnv(
"acrobot",
"swingup",
from_pixels=from_pixels,
height... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/dm_control_suite.py | 0.902968 | 0.261923 | dm_control_suite.py | pypi |
from gym.envs.classic_control import PendulumEnv, CartPoleEnv
import numpy as np
# MuJoCo may not be installed.
HalfCheetahEnv = HopperEnv = None
try:
from gym.envs.mujoco import HalfCheetahEnv, HopperEnv
except Exception:
pass
class CartPoleWrapper(CartPoleEnv):
"""Wrapper for the Cartpole-v0 environme... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/mbmpo_env.py | 0.859015 | 0.66842 | mbmpo_env.py | pypi |
import logging
from abc import ABC
from collections import Iterable
from typing import Dict, Optional
import numpy as np
from gym.spaces import Discrete
from gym.utils import seeding
from ray.rllib.env.multi_agent_env import MultiAgentEnv
from ray.rllib.examples.env.utils.interfaces import InfoAccumulationInterface
f... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/matrix_sequential_social_dilemma.py | 0.928797 | 0.407746 | matrix_sequential_social_dilemma.py | pypi |
from gym.envs.mujoco.mujoco_env import MujocoEnv
from gym.utils import EzPickle
import numpy as np
from ray.rllib.env.apis.task_settable_env import TaskSettableEnv
class AntRandGoalEnv(EzPickle, MujocoEnv, TaskSettableEnv):
"""Ant Environment that randomizes goals as tasks
Goals are randomly sampled 2D posi... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/ant_rand_goal.py | 0.861392 | 0.435421 | ant_rand_goal.py | pypi |
import copy
import gym
from gym.spaces import Box, Discrete
import numpy as np
import random
class SimpleContextualBandit(gym.Env):
"""Simple env w/ 2 states and 3 actions (arms): 0, 1, and 2.
Episodes last only for one timestep, possible observations are:
[-1.0, 1.0] and [1.0, -1.0], where the first ele... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/bandit_envs_discrete.py | 0.850298 | 0.627637 | bandit_envs_discrete.py | pypi |
from gym.envs.classic_control.cartpole import CartPoleEnv
from gym.utils import seeding
import ray
@ray.remote
class ParameterStorage:
def get_params(self, rng):
return {
"MASSCART": rng.uniform(low=0.5, high=2.0),
}
class CartPoleWithRemoteParamServer(CartPoleEnv):
"""CartPoleM... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/env_using_remote_actor.py | 0.906299 | 0.33674 | env_using_remote_actor.py | pypi |
import gym
from gym.spaces import Box, Dict, Discrete
import numpy as np
import random
class ParametricActionsCartPole(gym.Env):
"""Parametric action version of CartPole.
In this env there are only ever two valid actions, but we pretend there are
actually up to `max_avail_actions` actions that can be tak... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/parametric_actions_cartpole.py | 0.908608 | 0.667005 | parametric_actions_cartpole.py | pypi |
from gym.spaces import Dict, Discrete, MultiDiscrete, Tuple
import numpy as np
from ray.rllib.env.multi_agent_env import MultiAgentEnv, ENV_STATE
class TwoStepGame(MultiAgentEnv):
action_space = Discrete(2)
def __init__(self, env_config):
super().__init__()
self.action_space = Discrete(2)
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/two_step_game.py | 0.764628 | 0.391726 | two_step_game.py | pypi |
from gym.envs.mujoco.mujoco_env import MujocoEnv
from gym.utils import EzPickle
import numpy as np
from ray.rllib.env.apis.task_settable_env import TaskSettableEnv
class HalfCheetahRandDirecEnv(MujocoEnv, EzPickle, TaskSettableEnv):
"""HalfCheetah Environment with two diff tasks, moving forwards or backwards
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/halfcheetah_rand_direc.py | 0.910619 | 0.392191 | halfcheetah_rand_direc.py | pypi |
import gym
from typing import Type
class ActionTransform(gym.ActionWrapper):
def __init__(self, env, low, high):
super().__init__(env)
self._low = low
self._high = high
self.action_space = type(env.action_space)(
self._low, self._high, env.action_space.shape, env.action... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/transformed_action_space_env.py | 0.93273 | 0.513242 | transformed_action_space_env.py | pypi |
import gym
import numpy as np
from ray.rllib.env.multi_agent_env import MultiAgentEnv
class DebugCounterEnv(gym.Env):
"""Simple Env that yields a ts counter as observation (0-based).
Actions have no effect.
The episode length is always 15.
Reward is always: current ts % 3.
"""
def __init__(... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/debug_counter_env.py | 0.719876 | 0.356559 | debug_counter_env.py | pypi |
import gym
import random
from ray.rllib.env.apis.task_settable_env import TaskSettableEnv
from ray.rllib.env.env_context import EnvContext
from ray.rllib.utils.annotations import override
class CurriculumCapableEnv(TaskSettableEnv):
"""Example of a curriculum learning capable env.
This simply wraps a Frozen... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/curriculum_capable_env.py | 0.816809 | 0.296069 | curriculum_capable_env.py | pypi |
import copy
from collections import Iterable
import gym
import logging
import numpy as np
from gym.spaces import Discrete
from gym.utils import seeding
from ray.rllib.env.multi_agent_env import MultiAgentEnv
from ray.rllib.utils import override
from typing import Dict, Optional
from ray.rllib.examples.env.utils.inte... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/coin_game_non_vectorized_env.py | 0.886365 | 0.347177 | coin_game_non_vectorized_env.py | pypi |
import gym
import numpy as np
import random
from ray.rllib.env.multi_agent_env import MultiAgentEnv, make_multi_agent
from ray.rllib.examples.env.mock_env import MockEnv, MockEnv2
from ray.rllib.examples.env.stateless_cartpole import StatelessCartPole
from ray.rllib.utils.deprecation import Deprecated
@Deprecated(
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/multi_agent.py | 0.815673 | 0.330809 | multi_agent.py | pypi |
import gym
import numpy as np
from typing import Optional
from ray.rllib.utils.numpy import softmax
class ParametricRecSys(gym.Env):
"""A recommendation environment which generates items with visible features
randomly (parametric actions).
The environment can be configured to be multi-user, i.e. differen... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/bandit_envs_recommender_system.py | 0.905333 | 0.553264 | bandit_envs_recommender_system.py | pypi |
import copy
from collections import Iterable
import numpy as np
from numba import jit, prange
from numba.typed import List
from ray.rllib.examples.env.coin_game_non_vectorized_env import CoinGame
from ray.rllib.utils import override
class VectorizedCoinGame(CoinGame):
"""
Vectorized Coin Game environment.
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/coin_game_vectorized_env.py | 0.815857 | 0.411406 | coin_game_vectorized_env.py | pypi |
from abc import ABC
from ray.rllib.examples.env.utils.interfaces import InfoAccumulationInterface
class TwoPlayersTwoActionsInfoMixin(InfoAccumulationInterface, ABC):
"""
Mixin class to add logging capability in a two player discrete game.
Logs the frequency of each state.
"""
def _init_info(sel... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/examples/env/utils/mixins.py | 0.760117 | 0.32822 | mixins.py | pypi |
import numpy as np
import gym
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.utils.annotations import DeveloperAPI
from ray.rllib.utils.typing import TensorType, List, Union, ModelConfigDict
@DeveloperAPI
class ActionDistribution:
"""The policy action distribution of an agent.
Attributes:
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/models/action_dist.py | 0.910369 | 0.709409 | action_dist.py | pypi |
from functools import partial
import gym
from gym.spaces import Box, Dict, Discrete, MultiDiscrete, Tuple
import logging
import numpy as np
import tree # pip install dm_tree
from typing import List, Optional, Type, Union
from ray.tune.registry import (
RLLIB_MODEL,
RLLIB_PREPROCESSOR,
RLLIB_ACTION_DIST,
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/models/catalog.py | 0.932779 | 0.355831 | catalog.py | pypi |
from typing import Optional
from ray.rllib.utils.framework import try_import_jax, try_import_tf, try_import_torch
def get_activation_fn(name: Optional[str] = None, framework: str = "tf"):
"""Returns a framework specific activation function, given a name string.
Args:
name (Optional[str]): One of "re... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/models/utils.py | 0.954711 | 0.556882 | utils.py | pypi |
from typing import List
from ray.rllib.utils.annotations import PublicAPI
from ray.rllib.utils.typing import TensorType, TensorStructType
@PublicAPI
class RepeatedValues:
"""Represents a variable-length list of items from spaces.Repeated.
RepeatedValues are created when you use spaces.Repeated, and are
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/models/repeated_values.py | 0.86431 | 0.661146 | repeated_values.py | pypi |
from collections import OrderedDict
import logging
import numpy as np
import gym
from typing import Any, List
from ray.rllib.utils.annotations import override, PublicAPI
from ray.rllib.utils.spaces.repeated import Repeated
from ray.rllib.utils.typing import TensorType
from ray.rllib.utils.images import resize
from ray... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/rllib/models/preprocessors.py | 0.944228 | 0.414721 | preprocessors.py | pypi |
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