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 |
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import numpy as np
import pprint
from typing import Mapping
from ray.rllib.policy.sample_batch import SampleBatch, MultiAgentBatch
_printer = pprint.PrettyPrinter(indent=2, width=60)
def summarize(obj):
"""Return a pretty-formatted string for an object.
This has special handling for pretty-formatting of co... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/debug.py | 0.816113 | 0.330633 | debug.py | pypi |
import gym
from gym.spaces import Discrete, MultiDiscrete
import numpy as np
import tree
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
def convert_to_non_tf_type(stats):
"""Converts values in `stats` to non-Tensor numpy or python types.
Args:
stats (any): Any (p... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/tf_ops.py | 0.910012 | 0.491822 | tf_ops.py | pypi |
from typing import Any, Dict, List, Tuple, Union
import gym
# Represents a fully filled out config of a Trainer class.
# Note: Policy config dicts are usually the same as TrainerConfigDict, but
# parts of it may sometimes be altered in e.g. a multi-agent setup,
# where we have >1 Policies in the same Trainer.
TrainerC... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/typing.py | 0.931719 | 0.483039 | typing.py | pypi |
import numpy as np
def aligned_array(size, dtype, align=64):
"""Returns an array of a given size that is 64-byte aligned.
The returned array can be efficiently copied into GPU memory by TensorFlow.
"""
n = size * dtype.itemsize
empty = np.empty(n + (align - 1), dtype=np.uint8)
data_align = e... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/memory.py | 0.822653 | 0.734 | memory.py | pypi |
import logging
import numpy as np
import os
import sys
from typing import Any, Optional
from ray.rllib.utils.deprecation import deprecation_warning
from ray.rllib.utils.typing import TensorStructType, TensorShape, TensorType
logger = logging.getLogger(__name__)
# Represents a generic tensor type.
TensorType = Tensor... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/framework.py | 0.805364 | 0.42483 | framework.py | pypi |
from ray.rllib.utils.deprecation import deprecation_warning
class UsageTrackingDict(dict):
"""DEPRECATED class: Use SampleBatch instead!
Dict that tracks which keys have been accessed.
It can also intercept gets and allow an arbitrary callback to be applied
(i.e., to lazily convert numpy arrays to T... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/tracking_dict.py | 0.899094 | 0.334318 | tracking_dict.py | pypi |
import logging
import os
import time
from ray.util.debug import log_once
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
logger = logging.getLogger(__name__)
class TFRunBuilder:
"""Used to incrementally build up a TensorFlow run.
This is particularly useful for batching o... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/tf_run_builder.py | 0.537284 | 0.206334 | tf_run_builder.py | pypi |
import numpy as np
import logging
from collections import defaultdict
import random
from ray.util import log_once
from ray.rllib.evaluation.metrics import LEARNER_STATS_KEY
from ray.rllib.policy.sample_batch import SampleBatch, DEFAULT_POLICY_ID, \
MultiAgentBatch
logger = logging.getLogger(__name__)
def avera... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/sgd.py | 0.923601 | 0.45175 | sgd.py | pypi |
import logging
import numpy as np
import threading
logger = logging.getLogger(__name__)
class Filter:
"""Processes input, possibly statefully."""
def apply_changes(self, other, *args, **kwargs):
"""Updates self with "new state" from other filter."""
raise NotImplementedError
def copy(se... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/filter.py | 0.85962 | 0.390592 | filter.py | pypi |
from gym.spaces import Discrete, MultiDiscrete
import numpy as np
import tree
import warnings
from ray.rllib.models.repeated_values import RepeatedValues
from ray.rllib.utils.framework import try_import_torch
torch, nn = try_import_torch()
# Limit values suitable for use as close to a -inf logit. These are useful
# ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/torch_ops.py | 0.949412 | 0.537102 | torch_ops.py | pypi |
from functools import partial
from ray.rllib.utils.annotations import override, PublicAPI, DeveloperAPI
from ray.rllib.utils.framework import try_import_tf, try_import_tfp, \
try_import_torch
from ray.rllib.utils.deprecation import deprecation_warning, renamed_agent, \
renamed_class, renamed_function
from ray.... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/__init__.py | 0.868297 | 0.241668 | __init__.py | pypi |
from gym.spaces import Space
import numpy as np
from typing import Union, Optional
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.utils.annotations import override
from ray.rllib.utils.exploration.exploration import Exploration
from ray.rllib.uti... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/gaussian_noise.py | 0.965152 | 0.54468 | gaussian_noise.py | pypi |
import numpy as np
from typing import Optional, Union
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.utils.annotations import override
from ray.rllib.utils.exploration.gaussian_noise import GaussianNoise
from ray.rllib.utils.framework import try_import_tf, try_import_torch, \
get_variab... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/ornstein_uhlenbeck_noise.py | 0.954785 | 0.478468 | ornstein_uhlenbeck_noise.py | pypi |
import gym
import numpy as np
import tree
from typing import Union
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.utils.annotations import override
from ray.rllib.utils.exploration.exploration import Exploration
from ray.rllib.utils.exploration.r... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/stochastic_sampling.py | 0.917912 | 0.542197 | stochastic_sampling.py | pypi |
from gym.spaces import Discrete, Box, MultiDiscrete, Space
import numpy as np
import tree
from typing import Union, Optional
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.utils.annotations import override
from ray.rllib.utils.exploration.explora... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/random.py | 0.908445 | 0.482368 | random.py | pypi |
from gym.spaces import Space
from typing import Optional
from ray.rllib.utils.exploration.epsilon_greedy import EpsilonGreedy
from ray.rllib.utils.schedules import ConstantSchedule
class PerWorkerEpsilonGreedy(EpsilonGreedy):
"""A per-worker epsilon-greedy class for distributed algorithms.
Sets the epsilon ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/per_worker_epsilon_greedy.py | 0.952209 | 0.465084 | per_worker_epsilon_greedy.py | pypi |
import numpy as np
import tree
import random
from typing import Union, Optional
from ray.rllib.models.torch.torch_action_dist \
import TorchMultiActionDistribution
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.utils.annotations import override
from ray.rllib.utils.exploration.explorati... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/epsilon_greedy.py | 0.895972 | 0.411584 | epsilon_greedy.py | pypi |
from gym.spaces import Discrete, MultiDiscrete, Space
import numpy as np
from typing import Optional, Tuple, Union
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.models.catalog import ModelCatalog
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.tf_action_dist import Ca... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/curiosity.py | 0.925894 | 0.505615 | curiosity.py | pypi |
from gym.spaces import Space
from typing import List, Optional, Union, TYPE_CHECKING
from ray.rllib.env.base_env import BaseEnv
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.utils.annotations... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/exploration.py | 0.977154 | 0.457076 | exploration.py | pypi |
from gym.spaces import Box, Discrete
import numpy as np
from typing import Optional, TYPE_CHECKING, Union
from ray.rllib.env.base_env import BaseEnv
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.tf_action_dist import Categorical, Deter... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/parameter_noise.py | 0.931439 | 0.438304 | parameter_noise.py | pypi |
from gym.spaces import Discrete, Space
from typing import Union, Optional
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.models.tf.tf_action_dist import Categorical
from ray.rllib.models.torch.torch_action_dist import TorchCategorical
from ray.rllib.utils.annotations import override
from ra... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/exploration/soft_q.py | 0.966498 | 0.463869 | soft_q.py | pypi |
from ray.rllib.utils.annotations import override
from ray.rllib.utils.framework import try_import_tf
from ray.rllib.utils.schedules.schedule import Schedule
tf1, tf, tfv = try_import_tf()
def _linear_interpolation(left, right, alpha):
return left + alpha * (right - left)
class PiecewiseSchedule(Schedule):
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/schedules/piecewise_schedule.py | 0.93835 | 0.591546 | piecewise_schedule.py | pypi |
from abc import ABCMeta, abstractmethod
from ray.rllib.utils.annotations import DeveloperAPI
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
@DeveloperAPI
class Schedule(metaclass=ABCMeta):
"""Schedule classes implement various time-dependent scheduling schemas.
- Constan... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/schedules/schedule.py | 0.936706 | 0.394901 | schedule.py | pypi |
from gym.spaces import Tuple, Dict
import numpy as np
import tree
def flatten_space(space):
"""Flattens a gym.Space into its primitive components.
Primitive components are any non Tuple/Dict spaces.
Args:
space(gym.Space): The gym.Space to flatten. This may be any
supported type (inc... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/utils/spaces/space_utils.py | 0.940756 | 0.656741 | space_utils.py | pypi |
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... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/mock.py | 0.689619 | 0.189071 | mock.py | pypi |
from typing import Dict, Optional, TYPE_CHECKING
from ray.rllib.env import BaseEnv
from ray.rllib.policy import Policy
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.evaluation import MultiAgentEpisode
from ray.rllib.utils.annotations import PublicAPI
from ray.rllib.utils.deprecation import depre... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/callbacks.py | 0.940024 | 0.21819 | callbacks.py | pypi |
import numpy as np
from ray.rllib.utils.framework import try_import_torch
torch, nn = try_import_torch()
class VDNMixer(nn.Module):
def __init__(self):
super(VDNMixer, self).__init__()
def forward(self, agent_qs, batch):
return torch.sum(agent_qs, dim=2, keepdim=True)
class QMixer(nn.Modu... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/qmix/mixers.py | 0.944758 | 0.518485 | mixers.py | pypi |
from gym.spaces import Tuple, Discrete, Dict
import logging
import numpy as np
import tree
import ray
from ray.rllib.agents.qmix.mixers import VDNMixer, QMixer
from ray.rllib.agents.qmix.model import RNNModel, _get_size
from ray.rllib.env.multi_agent_env import ENV_STATE
from ray.rllib.env.wrappers.group_agents_wrappe... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/qmix/qmix_policy.py | 0.924073 | 0.423398 | qmix_policy.py | pypi |
import gym
from gym.spaces import Discrete
import logging
from typing import Dict, List, Optional, Tuple, Type, Union
import ray
import ray.experimental.tf_utils
from ray.rllib.agents.sac.sac_tf_policy import build_sac_model, \
postprocess_trajectory, validate_spaces
from ray.rllib.agents.dqn.dqn_tf_policy import ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/sac/sac_torch_policy.py | 0.966584 | 0.355132 | sac_torch_policy.py | pypi |
import gym
from gym.spaces import Box, Discrete
import numpy as np
from typing import Dict, List, Optional
from ray.rllib.models.catalog import ModelCatalog
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.utils import force_list
from ray.rllib.utils.annotations import override
from ray.rllib.utils.... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/sac/sac_tf_model.py | 0.932499 | 0.445952 | sac_tf_model.py | pypi |
import gym
from gym.spaces import Box, Discrete
import numpy as np
from typing import Dict, List, Optional
from ray.rllib.models.catalog import ModelCatalog
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils import force_list
from ray.rllib.utils.annotations import override
from ray.rll... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/sac/sac_torch_model.py | 0.947271 | 0.463019 | sac_torch_model.py | pypi |
import gym
from gym.spaces import Box, Discrete
from functools import partial
import logging
import numpy as np
from typing import Dict, List, Optional, Tuple, Type, Union
import ray
import ray.experimental.tf_utils
from ray.rllib.agents.ddpg.ddpg_tf_policy import ComputeTDErrorMixin, \
TargetNetworkMixin
from ray... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/sac/sac_tf_policy.py | 0.945626 | 0.282669 | sac_tf_policy.py | pypi |
import logging
import ray
from ray.rllib.agents.dreamer.utils import FreezeParameters
from ray.rllib.models.catalog import ModelCatalog
from ray.rllib.policy.policy_template import build_policy_class
from ray.rllib.utils.framework import try_import_torch
from ray.rllib.utils.torch_ops import apply_grad_clipping
torch... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dreamer/dreamer_torch_policy.py | 0.89921 | 0.457682 | dreamer_torch_policy.py | pypi |
import numpy as np
from ray.rllib.utils.framework import try_import_torch
torch, nn = try_import_torch()
# Custom initialization for different types of layers
if torch:
class Linear(nn.Linear):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def reset_paramete... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dreamer/utils.py | 0.865423 | 0.255622 | utils.py | pypi |
import numpy as np
from typing import Any, List, Tuple
from ray.rllib.models.torch.misc import Reshape
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils.framework import try_import_torch
from ray.rllib.utils.framework import TensorType
torch, nn = try_import_torch()
if torch:
from ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dreamer/dreamer_model.py | 0.957833 | 0.471467 | dreamer_model.py | pypi |
import logging
import random
import numpy as np
from ray.rllib.agents import with_common_config
from ray.rllib.agents.dreamer.dreamer_torch_policy import DreamerTorchPolicy
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.execution.common import STEPS_SAMPLED_COUNTER, \
LEARNER_INFO, _ge... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dreamer/dreamer.py | 0.799286 | 0.290779 | dreamer.py | pypi |
import gym
import numpy as np
import tree
import ray
import ray.experimental.tf_utils
from ray.rllib.agents.es.es_tf_policy import make_session
from ray.rllib.models import ModelCatalog
from ray.rllib.policy.policy import Policy
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.utils.filter import ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ars/ars_tf_policy.py | 0.831622 | 0.217213 | ars_tf_policy.py | pypi |
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.ars.ars_tf_policy import ARSTFPolicy
from ray.rllib.agents.es import optimizers, utils
from ray.rllib.agents.es.es import validate_config
from ray.... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ars/ars.py | 0.93064 | 0.33135 | ars.py | pypi |
import numpy as np
import gym
import logging
from typing import Dict, List, Tuple, Type, Union
import ray
import ray.experimental.tf_utils
from ray.rllib.agents.sac.sac_tf_policy import postprocess_trajectory, \
validate_spaces
from ray.rllib.agents.sac.sac_torch_policy import _get_dist_class, stats, \
build_s... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/cql/cql_torch_policy.py | 0.877674 | 0.393968 | cql_torch_policy.py | pypi |
from typing import Optional, Type, List
from ray.rllib.agents.sac.sac import SACTrainer, \
DEFAULT_CONFIG as SAC_CONFIG
from ray.rllib.agents.cql.cql_torch_policy import CQLTorchPolicy
from ray.rllib.utils.typing import TrainerConfigDict
from ray.rllib.policy.policy import Policy
from ray.rllib.utils import merge_... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/cql/cql.py | 0.917916 | 0.206694 | cql.py | pypi |
from typing import List
import gym
from ray.rllib.models.tf.layers import NoisyLayer
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.utils.framework import try_import_tf
from ray.rllib.utils.typing import ModelConfigDict, TensorType
tf1, tf, tfv = try_import_tf()
class DistributionalQTFModel(TF... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dqn/distributional_q_tf_model.py | 0.837819 | 0.431644 | distributional_q_tf_model.py | pypi |
import logging
from typing import List, Tuple, Type
import gym
import ray
from ray.rllib.models import ModelCatalog
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.tf_action_dist import (Categorical,
TFActionDistribution)
from ray.rllib.models.torc... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dqn/simple_q_tf_policy.py | 0.941088 | 0.360799 | simple_q_tf_policy.py | pypi |
from typing import Sequence
import gym
from ray.rllib.models.torch.misc import SlimFC
from ray.rllib.models.torch.modules.noisy_layer import NoisyLayer
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils.framework import try_import_torch
from ray.rllib.utils.typing import ModelConfigDict... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dqn/dqn_torch_model.py | 0.906055 | 0.386271 | dqn_torch_model.py | pypi |
import logging
from typing import Dict, Tuple
import gym
import ray
from ray.rllib.agents.dqn.simple_q_tf_policy import (
build_q_models, compute_q_values, get_distribution_inputs_and_class)
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.torch.torch_action_dist import TorchCategorical, \
T... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dqn/simple_q_torch_policy.py | 0.964069 | 0.388763 | simple_q_torch_policy.py | pypi |
from typing import Dict, List, Optional, Tuple
import gym
import ray
from ray.rllib.agents.dqn.dqn_tf_policy import clip_gradients, \
compute_q_values, PRIO_WEIGHTS, postprocess_nstep_and_prio
from ray.rllib.agents.dqn.dqn_tf_policy import build_q_model
from ray.rllib.agents.dqn.simple_q_tf_policy import TargetNe... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dqn/r2d2_tf_policy.py | 0.948894 | 0.395514 | r2d2_tf_policy.py | pypi |
from typing import Dict, Tuple
import gym
import ray
from ray.rllib.agents.dqn.dqn_tf_policy import (PRIO_WEIGHTS,
postprocess_nstep_and_prio)
from ray.rllib.agents.dqn.dqn_torch_policy import \
build_q_model_and_distribution, compute_q_values
from ray.rllib.agents.... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/dqn/r2d2_torch_policy.py | 0.940926 | 0.437403 | r2d2_torch_policy.py | pypi |
from ray.rllib.agents.trainer import with_common_config
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.agents.marwil.marwil_tf_policy import MARWILTFPolicy
from ray.rllib.execution.replay_ops import SimpleReplayBuffer, Replay, \
StoreToReplayBuffer
from ray.rllib.execution.rollout_ops im... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/marwil/marwil.py | 0.87401 | 0.318088 | marwil.py | pypi |
import ray
from ray.rllib.agents.marwil.marwil_tf_policy import postprocess_advantages
from ray.rllib.evaluation.postprocessing import Postprocessing
from ray.rllib.policy.policy_template import build_policy_class
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.utils.framework import try_import_tor... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/marwil/marwil_torch_policy.py | 0.903159 | 0.386706 | marwil_torch_policy.py | pypi |
import logging
import ray
from ray.rllib.agents.ppo.ppo_tf_policy import compute_and_clip_gradients
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.evaluation.postprocessing import compute_advantages, \
Postprocessing
from ray.rllib.policy.tf_policy_template import build_tf_policy
from ray.rll... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/marwil/marwil_tf_policy.py | 0.940599 | 0.382776 | marwil_tf_policy.py | pypi |
from ray.rllib.agents.impala.vtrace_tf import VTraceFromLogitsReturns, \
VTraceReturns
from ray.rllib.models.torch.torch_action_dist import TorchCategorical
from ray.rllib.utils import force_list
from ray.rllib.utils.framework import try_import_torch
from ray.rllib.utils.torch_ops import convert_to_torch_tensor
to... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/impala/vtrace_torch.py | 0.966937 | 0.484502 | vtrace_torch.py | pypi |
import collections
from ray.rllib.models.tf.tf_action_dist import Categorical
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
VTraceFromLogitsReturns = collections.namedtuple("VTraceFromLogitsReturns", [
"vs", "pg_advantages", "log_rhos", "behaviour_action_log_probs",
"targ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/impala/vtrace_tf.py | 0.939151 | 0.441733 | vtrace_tf.py | pypi |
import gym
import logging
import numpy as np
import ray
import ray.rllib.agents.impala.vtrace_torch as vtrace
from ray.rllib.models.torch.torch_action_dist import TorchCategorical
from ray.rllib.policy.policy_template import build_policy_class
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.policy... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/impala/vtrace_torch_policy.py | 0.921556 | 0.392337 | vtrace_torch_policy.py | pypi |
import math
from ray.rllib.agents.a3c.a3c import DEFAULT_CONFIG as A3C_CONFIG, \
validate_config, get_policy_class
from ray.rllib.agents.a3c.a3c_tf_policy import A3CTFPolicy
from ray.rllib.agents.trainer_template import build_trainer
from ray.rllib.execution.metric_ops import StandardMetricsReporting
from ray.rlli... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/a3c/a2c.py | 0.697712 | 0.244555 | a2c.py | pypi |
import gym
import ray
from ray.rllib.agents.ppo.ppo_torch_policy import ValueNetworkMixin
from ray.rllib.evaluation.postprocessing import compute_gae_for_sample_batch, \
Postprocessing
from ray.rllib.policy.policy import Policy
from ray.rllib.policy.policy_template import build_policy_class
from ray.rllib.policy.s... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/a3c/a3c_torch_policy.py | 0.887686 | 0.244893 | a3c_torch_policy.py | pypi |
import ray
from ray.rllib.agents.ppo.ppo_tf_policy import ValueNetworkMixin
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.evaluation.postprocessing import compute_gae_for_sample_batch, \
Postprocessing
from ray.rllib.policy.tf_policy_template import build_tf_policy
from ray.rllib.policy.tf_p... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/a3c/a3c_tf_policy.py | 0.923988 | 0.240808 | a3c_tf_policy.py | pypi |
import logging
import ray
from ray.rllib.agents.ddpg.ddpg_tf_policy import build_ddpg_models, \
get_distribution_inputs_and_class, validate_spaces
from ray.rllib.agents.dqn.dqn_tf_policy import postprocess_nstep_and_prio, \
PRIO_WEIGHTS
from ray.rllib.models.torch.torch_action_dist import TorchDeterministic, \... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ddpg/ddpg_torch_policy.py | 0.670716 | 0.26884 | ddpg_torch_policy.py | pypi |
import numpy as np
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.utils.framework import try_import_tf
tf1, tf, tfv = try_import_tf()
class DDPGTFModel(TFModelV2):
"""Extension of standard TFModel to provide DDPG action- and q-outputs.
Data flow:
obs -> forward() -> model_out
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ddpg/ddpg_tf_model.py | 0.907362 | 0.456107 | ddpg_tf_model.py | pypi |
from ray.rllib.agents.ddpg.ddpg import DDPGTrainer, \
DEFAULT_CONFIG as DDPG_CONFIG
TD3_DEFAULT_CONFIG = DDPGTrainer.merge_trainer_configs(
DDPG_CONFIG,
{
# largest changes: twin Q functions, delayed policy updates, and target
# smoothing
"twin_q": True,
"policy_delay": 2,
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ddpg/td3.py | 0.70202 | 0.436922 | td3.py | pypi |
import numpy as np
from ray.rllib.models.torch.misc import SlimFC
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.models.utils import get_activation_fn
from ray.rllib.utils.framework import try_import_torch
torch, nn = try_import_torch()
class DDPGTorchModel(TorchModelV2, nn.Module):
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ddpg/ddpg_torch_model.py | 0.954073 | 0.38027 | ddpg_torch_model.py | pypi |
import gym
import logging
from typing import Dict, List, Optional, Type, Union
import ray
from ray.rllib.evaluation.episode import MultiAgentEpisode
from ray.rllib.evaluation.postprocessing import compute_gae_for_sample_batch, \
Postprocessing
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.t... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ppo/ppo_tf_policy.py | 0.962822 | 0.308619 | ppo_tf_policy.py | pypi |
import gym
import logging
from typing import Dict, List, Type, Union
import ray
from ray.rllib.agents.ppo.ppo_tf_policy import setup_config
from ray.rllib.evaluation.postprocessing import compute_gae_for_sample_batch, \
Postprocessing
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.torch.torch_a... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ppo/ppo_torch_policy.py | 0.955121 | 0.361291 | ppo_torch_policy.py | pypi |
import logging
import time
import ray
from ray.rllib.agents.ppo import ppo
from ray.rllib.evaluation.worker_set import WorkerSet
from ray.rllib.execution.rollout_ops import ParallelRollouts
from ray.rllib.execution.metric_ops import StandardMetricsReporting
from ray.rllib.execution.common import STEPS_SAMPLED_COUNTER,... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ppo/ddppo.py | 0.841858 | 0.205456 | ddppo.py | pypi |
import gym
import numpy as np
import logging
from typing import Type
import ray.rllib.agents.impala.vtrace_torch as vtrace
from ray.rllib.agents.impala.vtrace_torch_policy import make_time_major, \
choose_optimizer
from ray.rllib.agents.ppo.appo_tf_policy import make_appo_model, \
postprocess_trajectory
from r... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/ppo/appo_torch_policy.py | 0.927741 | 0.282505 | appo_torch_policy.py | pypi |
import logging
import ray
from ray.rllib.agents.ppo.ppo_tf_policy import vf_preds_fetches, \
compute_and_clip_gradients, setup_config, ValueNetworkMixin
from ray.rllib.evaluation.postprocessing import compute_gae_for_sample_batch, \
Postprocessing
from ray.rllib.models.utils import get_activation_fn
from ray.r... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/maml/maml_tf_policy.py | 0.852014 | 0.160398 | maml_tf_policy.py | pypi |
from typing import Dict, List, Type, Union
import ray
from ray.rllib.agents.pg.utils import post_process_advantages
from ray.rllib.evaluation.postprocessing import Postprocessing
from ray.rllib.models.torch.torch_action_dist import TorchDistributionWrapper
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.po... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/pg/pg_torch_policy.py | 0.970826 | 0.397851 | pg_torch_policy.py | pypi |
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, utils
from ray.rllib.agents.es.es_tf_policy import ESTFPolicy, rollout
from ray.rllib.env.env_context import EnvContext
from ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/es/es.py | 0.912756 | 0.237388 | es.py | pypi |
import gym
import numpy as np
import tree
import ray
from ray.rllib.models import ModelCatalog
from ray.rllib.policy.policy_template import build_policy_class
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.utils.filter import get_filter
from ray.rllib.utils.framework import try_import_torch
from... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/es/es_torch_policy.py | 0.833968 | 0.336522 | es_torch_policy.py | pypi |
import gym
import numpy as np
import tree
import ray
import ray.experimental.tf_utils
from ray.rllib.models import ModelCatalog
from ray.rllib.policy.policy import Policy
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.utils.annotations import override
from ray.rllib.utils.filter import get_filte... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/es/es_tf_policy.py | 0.879432 | 0.286363 | es_tf_policy.py | pypi |
import numpy as np
from ray.rllib.evaluation.postprocessing import discount_cumsum
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.utils.exploration.stochastic_sampling import StochasticSampling
from ray.rllib.utils.framework import try_import_tf, try_import_torch
tf1, tf, tfv = try_import_tf()
torch, _ =... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/mbmpo/utils.py | 0.884314 | 0.374419 | utils.py | pypi |
import gym
from gym.spaces import Discrete, Box
import numpy as np
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils.framework import try_import_torch
from ray.rllib.evaluation.rollout_worker import get_global_worker
from ray.rllib.policy.sample_batch import SampleBatch
from ray.rllib.e... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/mbmpo/model_ensemble.py | 0.92916 | 0.472683 | model_ensemble.py | pypi |
from typing import Dict, List, Sequence, Tuple
import gym
import numpy as np
import ray
from ray.rllib.models.modelv2 import ModelV2, restore_original_dimensions
from ray.rllib.models.torch.torch_action_dist import (TorchCategorical,
TorchDistributionWrapper)
fro... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/rllib/agents/slateq/slateq_torch_policy.py | 0.953859 | 0.523177 | slateq_torch_policy.py | pypi |
from abc import ABCMeta, abstractmethod
import random
from hashlib import sha256
from functools import lru_cache
from typing import List
import numpy as np
import ray
from ray.serve.utils import logger
@lru_cache(maxsize=128)
def deterministic_hash(key: bytes) -> float:
"""Given an arbitrary bytes, return a det... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/serve/endpoint_policy.py | 0.925844 | 0.403214 | endpoint_policy.py | pypi |
from abc import ABCMeta, abstractmethod
from ray.serve.utils import logger
class AutoscalingPolicy:
"""Defines the interface for an autoscaling policy.
To add a new autoscaling policy, a class should be defined that provides
this interface. The class may be stateful, in which case it may also want
t... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/serve/autoscaling_policy.py | 0.857843 | 0.411702 | autoscaling_policy.py | pypi |
import inspect
from enum import Enum
from typing import Any, Dict, List, Optional
import pydantic
from pydantic import BaseModel, PositiveInt, validator, NonNegativeFloat
from pydantic.dataclasses import dataclass
from ray.serve.constants import DEFAULT_HTTP_HOST, DEFAULT_HTTP_PORT
from ray.serve.utils import logger
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/serve/config.py | 0.854809 | 0.153105 | config.py | pypi |
import asyncio
from functools import singledispatch
import importlib
from itertools import groupby
import json
import logging
import random
import string
import time
from typing import Iterable, List, Tuple, Dict, Optional
import os
from ray.serve.exceptions import RayServeException
from collections import UserDict
im... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/serve/utils.py | 0.777849 | 0.181535 | utils.py | pypi |
import json
import starlette.requests
def build_starlette_request(scope, serialized_body: bytes):
"""Build and return a Starlette Request from ASGI payload.
This function is intended to be used immediately before task invocation
happens.
"""
# Simulates receiving HTTP body from TCP socket. In ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/serve/http_util.py | 0.724286 | 0.264539 | http_util.py | pypi |
import ray
import ray._private.services as services
import ray.worker
from ray import profiling
from ray import ray_constants
from ray.state import GlobalState
__all__ = ["free", "global_gc"]
MAX_MESSAGE_LENGTH = ray._config.max_grpc_message_size()
def global_gc():
"""Trigger gc.collect() on all workers in the c... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/internal/internal_api.py | 0.869049 | 0.204084 | internal_api.py | pypi |
import hashlib
import logging
import inspect
from filelock import FileLock
from pathlib import Path
from zipfile import ZipFile
from ray.job_config import JobConfig
from enum import Enum
from ray.experimental.internal_kv import (_internal_kv_put, _internal_kv_get,
_internal_k... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/_private/runtime_env.py | 0.613931 | 0.213767 | runtime_env.py | pypi |
import json
import logging
import os
import threading
import time
import traceback
from collections import namedtuple
from typing import List
from opencensus.stats import aggregation
from opencensus.stats import measure as measure_module
from opencensus.stats import stats as stats_module
from opencensus.stats.view imp... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/_private/metrics_agent.py | 0.830078 | 0.307033 | metrics_agent.py | pypi |
import inspect
import logging
import sys
from ray.util.client.ray_client_helpers import ray_start_client_server
from ray._private.ray_microbenchmark_helpers import timeit
def benchmark_get_calls(ray):
value = ray.put(0)
def get_small():
ray.get(value)
timeit("client: get calls", get_small)
d... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/_private/ray_client_microbenchmark.py | 0.494629 | 0.154344 | ray_client_microbenchmark.py | pypi |
import re
from prometheus_client import start_http_server
from prometheus_client.core import (
REGISTRY,
CollectorRegistry,
CounterMetricFamily,
GaugeMetricFamily,
HistogramMetricFamily,
UnknownMetricFamily,
)
from opencensus.common.transports import sync
from opencensus.stats import aggregat... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/_private/prometheus_exporter.py | 0.745398 | 0.256762 | prometheus_exporter.py | pypi |
import logging
import os
import numpy as np
import ray.ray_constants as ray_constants
logger = logging.getLogger(__name__)
class RayParams:
"""A class used to store the parameters used by Ray.
Attributes:
redis_address (str): The address of the Redis server to connect to. If
this addre... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/_private/parameter.py | 0.773815 | 0.375706 | parameter.py | pypi |
import inspect
from inspect import Parameter
import logging
from ray.util.inspect import is_cython
# Logger for this module. It should be configured at the entry point
# into the program using Ray. Ray provides a default configuration at
# entry/init points.
logger = logging.getLogger(__name__)
# This dummy type is ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/_private/signature.py | 0.843959 | 0.490846 | signature.py | pypi |
from typing import Callable, Type, Union
import inspect
import logging
import os
from ray.tune.function_runner import wrap_function
from ray.tune.registry import get_trainable_cls
from ray.tune.trainable import Trainable, TrainableUtil
from ray.tune.syncer import get_cloud_sync_client
logger = logging.getLogger(__na... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/durable_trainable.py | 0.920968 | 0.359083 | durable_trainable.py | pypi |
import logging
from types import FunctionType
import ray
import ray.cloudpickle as pickle
from ray.experimental.internal_kv import _internal_kv_initialized, \
_internal_kv_get, _internal_kv_put
from ray.tune.error import TuneError
TRAINABLE_CLASS = "trainable_class"
ENV_CREATOR = "env_creator"
RLLIB_MODEL = "rlli... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/registry.py | 0.748995 | 0.193166 | registry.py | pypi |
import click
import logging
import os
import subprocess
import operator
from datetime import datetime
import pandas as pd
from pandas.api.types import is_string_dtype, is_numeric_dtype
from ray.tune.result import (DEFAULT_EXPERIMENT_INFO_KEYS, DEFAULT_RESULT_KEYS,
CONFIG_PREFIX)
from ray.t... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/commands.py | 0.550245 | 0.156975 | commands.py | pypi |
from __future__ import print_function
from typing import Dict, List, Optional, Union
import collections
import os
import sys
import numpy as np
import time
from ray.tune.callback import Callback
from ray.tune.logger import pretty_print
from ray.tune.result import (DEFAULT_METRIC, EPISODE_REWARD_MEAN,
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/progress_reporter.py | 0.892223 | 0.209672 | progress_reporter.py | pypi |
import logging
from ray.tune.trial import Trial, Checkpoint
from ray.tune.error import TuneError
from ray.tune.cluster_info import is_ray_cluster
logger = logging.getLogger(__name__)
class TrialExecutor:
"""Module for interacting with remote trainables.
Manages platform-specific details such as resource ha... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/trial_executor.py | 0.918626 | 0.26792 | trial_executor.py | pypi |
import heapq
import gc
import logging
from ray.tune.result import TRAINING_ITERATION
from ray.tune.utils.util import flatten_dict
logger = logging.getLogger(__name__)
class Checkpoint:
"""Describes a checkpoint of trial state.
Checkpoint may be saved in different storage.
Attributes:
storage (... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/checkpoint_manager.py | 0.886224 | 0.298568 | checkpoint_manager.py | pypi |
import logging
from copy import copy
from inspect import signature
from math import isclose
from typing import Any, Callable, Dict, List, Optional, Sequence, Union
import numpy as np
logger = logging.getLogger(__name__)
class Domain:
"""Base class to specify a type and valid range to sample parameters from.
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/sample.py | 0.947974 | 0.469581 | sample.py | pypi |
import warnings
from typing import Dict, Optional
import time
from collections import defaultdict, deque
import numpy as np
from ray import logger
class Stopper:
"""Base class for implementing a Tune experiment stopper.
Allows users to implement experiment-level stopping via ``stop_all``. By
default, t... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/stopper.py | 0.958528 | 0.266666 | stopper.py | pypi |
from typing import TYPE_CHECKING, Dict, List
from ray.tune.checkpoint_manager import Checkpoint
if TYPE_CHECKING:
from ray.tune.trial import Trial
class Callback:
"""Tune base callback that can be extended and passed to a ``TrialRunner``
Tune callbacks are called from within the ``TrialRunner`` class. ... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/callback.py | 0.902953 | 0.487978 | callback.py | pypi |
from ray.tune.error import TuneError
from ray.tune.tune import run_experiments, run
from ray.tune.syncer import SyncConfig
from ray.tune.experiment import Experiment
from ray.tune.analysis import ExperimentAnalysis, Analysis
from ray.tune.stopper import Stopper, EarlyStopping
from ray.tune.registry import register_env,... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/__init__.py | 0.66769 | 0.184547 | __init__.py | pypi |
import os
# yapf: disable
# __sphinx_doc_begin__
# (Optional/Auto-filled) training is terminated. Filled only if not provided.
DONE = "done"
# (Optional) Enum for user controlled checkpoint
SHOULD_CHECKPOINT = "should_checkpoint"
# (Auto-filled) The hostname of the machine hosting the training process.
HOSTNAME = "h... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/result.py | 0.498535 | 0.247067 | result.py | pypi |
from collections import namedtuple
import logging
import json
from numbers import Number
# For compatibility under py2 to consider unicode as str
from typing import Optional
from six import string_types
import ray
from ray.tune import TuneError
logger = logging.getLogger(__name__)
class Resources(
namedtup... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/resources.py | 0.875913 | 0.265821 | resources.py | pypi |
import copy
import logging
from typing import Dict, List, Optional, Union
from ray.tune.error import TuneError
from ray.tune.experiment import Experiment, 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.... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/suggest/search_generator.py | 0.939996 | 0.239316 | search_generator.py | pypi |
import copy
import logging
import math
from typing import Dict, List, Optional, Union
import ConfigSpace
from ray.tune.result import DEFAULT_METRIC
from ray.tune.sample import Categorical, Domain, Float, Integer, LogUniform, \
Normal, \
Quantized, \
Uniform
from ray.tune.suggest import Searcher
from ray.t... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/suggest/bohb.py | 0.941095 | 0.395076 | bohb.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import inspect
import logging
from typing import Dict, List, Optional, Union
from ray.tune.result import DEFAULT_METRIC
from ray.tune.sample import Domain, Float, Quantized
from ray.tune.suggest.suggestion imp... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/suggest/dragonfly.py | 0.930237 | 0.340746 | dragonfly.py | pypi |
import logging
import pickle
from typing import Dict, List, Optional, Union
import numpy as np
import pandas as pd
from ray.tune.result import DEFAULT_METRIC
from ray.tune.sample import Categorical, Domain, Float, Integer, LogUniform, \
Quantized, Uniform
from ray.tune.suggest.suggestion import UNRESOLVED_SEARCH_... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/suggest/hebo.py | 0.936452 | 0.446133 | hebo.py | pypi |
import copy
import logging
from typing import Dict, List, Optional, Tuple
import ray
import ray.cloudpickle as pickle
from ray.tune.result import DEFAULT_METRIC
from ray.tune.sample import Categorical, Domain, Float, Integer, Quantized, \
Uniform
from ray.tune.suggest.suggestion import UNRESOLVED_SEARCH_SPACE, \
... | /ray_delvewheel-1.3.0.0-cp38-cp38-win_amd64.whl/ray-1.3.0.data/purelib/ray/tune/suggest/zoopt.py | 0.915554 | 0.290327 | zoopt.py | pypi |
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