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 |
|---|---|---|---|---|---|
import dataclasses
from collections import defaultdict
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Sequence, TypeVar, Union
import numpy as np
from torch.utils.tensorboard.writer import SummaryWriter
@dataclass
class Episode:
score: float = 0
length: int = 0
info: Dict... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/stats.py | 0.900283 | 0.452596 | stats.py | pypi |
import numpy as np
import torch
from typing import NamedTuple, Sequence
from rl_algo_impls.shared.policy.actor_critic import OnPolicy
from rl_algo_impls.shared.trajectory import Trajectory
from rl_algo_impls.wrappers.vectorable_wrapper import VecEnvObs
class RtgAdvantage(NamedTuple):
rewards_to_go: torch.Tensor... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/gae.py | 0.740456 | 0.55926 | gae.py | pypi |
import numpy as np
from dataclasses import dataclass, field
from typing import Generic, List, Optional, Type, TypeVar
from rl_algo_impls.wrappers.vectorable_wrapper import VecEnvObs
@dataclass
class Trajectory:
obs: List[np.ndarray] = field(default_factory=list)
act: List[np.ndarray] = field(default_factory... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/trajectory.py | 0.73307 | 0.479138 | trajectory.py | pypi |
import itertools
import os
import shutil
from time import perf_counter
from typing import Dict, List, Optional, Union
import numpy as np
from torch.utils.tensorboard.writer import SummaryWriter
from rl_algo_impls.shared.callbacks import Callback
from rl_algo_impls.shared.policy.policy import Policy
from rl_algo_impls... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/callbacks/eval_callback.py | 0.791015 | 0.26699 | eval_callback.py | pypi |
from typing import Any, Dict, List, Optional
import numpy as np
from rl_algo_impls.runner.config import Config
from rl_algo_impls.shared.algorithm import Algorithm
from rl_algo_impls.shared.callbacks.callback import Callback
from rl_algo_impls.shared.schedule import constant_schedule, lerp
from rl_algo_impls.wrappers... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/callbacks/lux_hyperparam_transitions.py | 0.873815 | 0.337395 | lux_hyperparam_transitions.py | pypi |
import numpy as np
import optuna
from time import perf_counter
from torch.utils.tensorboard.writer import SummaryWriter
from typing import NamedTuple, Union
from rl_algo_impls.shared.callbacks import Callback
from rl_algo_impls.shared.callbacks.eval_callback import evaluate
from rl_algo_impls.shared.policy.policy imp... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/callbacks/optimize_callback.py | 0.902138 | 0.295662 | optimize_callback.py | pypi |
from abc import abstractmethod
from typing import NamedTuple, Optional, Sequence, Tuple, TypeVar
import gym
import numpy as np
import torch
from gym.spaces import Box
from rl_algo_impls.shared.policy.actor_critic_network import (
ConnectedTrioActorCriticNetwork,
SeparateActorCriticNetwork,
UNetActorCritic... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/policy/actor_critic.py | 0.939178 | 0.328934 | actor_critic.py | pypi |
import os
from abc import ABC, abstractmethod
from copy import deepcopy
from typing import Dict, Optional, Type, TypeVar, Union
import numpy as np
import torch
import torch.nn as nn
from stable_baselines3.common.vec_env import unwrap_vec_normalize
from stable_baselines3.common.vec_env.vec_normalize import VecNormalize... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/policy/policy.py | 0.897339 | 0.273529 | policy.py | pypi |
from typing import Optional, Sequence, Tuple, Type
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from gym.spaces import MultiDiscrete, Space
from rl_algo_impls.shared.actor import pi_forward
from rl_algo_impls.shared.actor.gridnet import GridnetDistribution
from rl_algo_impls.s... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/policy/actor_critic_network/unet.py | 0.955089 | 0.368463 | unet.py | pypi |
from typing import Optional, Sequence, Tuple
import torch
import torch.nn as nn
from gym.spaces import Space
from rl_algo_impls.shared.actor import actor_head
from rl_algo_impls.shared.encoder import Encoder
from rl_algo_impls.shared.policy.actor_critic_network.network import (
ACNForward,
ActorCriticNetwork,... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/policy/actor_critic_network/separate_actor_critic.py | 0.956513 | 0.266006 | separate_actor_critic.py | pypi |
from typing import Optional, Sequence, Tuple
import torch
from gym.spaces import Space
from rl_algo_impls.shared.actor import actor_head
from rl_algo_impls.shared.encoder import Encoder
from rl_algo_impls.shared.policy.actor_critic_network.network import (
ACNForward,
ActorCriticNetwork,
default_hidden_si... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/policy/actor_critic_network/connected_trio.py | 0.955183 | 0.283465 | connected_trio.py | pypi |
from dataclasses import astuple
from typing import Any, Dict, Optional, Tuple
import numpy as np
from luxai_s2.actions import move_deltas
from rl_algo_impls.shared.lux.actions import FACTORY_ACTION_ENCODED_SIZE, pos_to_idx
from rl_algo_impls.shared.lux.shared import (
LuxEnvConfig,
LuxFactory,
LuxGameStat... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/lux/action_mask.py | 0.836521 | 0.339609 | action_mask.py | pypi |
import dataclasses
from dataclasses import dataclass
from typing import Dict, List, Tuple
import numpy as np
from luxai_s2.env import LuxAI_S2
from luxai_s2.unit import UnitType
class AgentRunningStats:
stats: np.ndarray
NAMES = (
# Change in value stats
"ice_generation",
"ore_generat... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/lux/stats.py | 0.794225 | 0.391406 | stats.py | pypi |
from typing import Dict, NamedTuple, Optional, Tuple, Type
import numpy as np
from luxai_s2.factory import FactoryStateDict
from luxai_s2.state import ObservationStateDict
from luxai_s2.unit import UnitStateDict
from rl_algo_impls.shared.lux.action_mask import (
agent_move_masks,
get_action_mask,
is_build... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/lux/observation.py | 0.787605 | 0.380701 | observation.py | pypi |
from typing import Any, Dict, List
import numpy as np
from luxai_s2.utils import my_turn_to_place_factory
from rl_algo_impls.shared.lux.shared import LuxGameState, pos_to_numpy
def bid_action(bid_std_dev: float, faction: str) -> Dict[str, Any]:
return {"bid": int(np.random.normal(scale=5)), "faction": faction}
... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/lux/early.py | 0.672977 | 0.399929 | early.py | pypi |
import logging
from dataclasses import astuple
from typing import Any, Dict, List, Optional, Union
import numpy as np
from luxai_s2.actions import move_deltas
from luxai_s2.map.position import Position
from rl_algo_impls.shared.lux.shared import (
LuxEnvConfig,
LuxGameState,
LuxUnit,
pos_to_numpy,
)
f... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/lux/actions.py | 0.630002 | 0.38168 | actions.py | pypi |
from dataclasses import astuple
from typing import Optional
import gym
import numpy as np
from torch.utils.tensorboard.writer import SummaryWriter
from rl_algo_impls.runner.config import Config, EnvHyperparams
from rl_algo_impls.wrappers.action_mask_wrapper import MicrortsMaskWrapper
from rl_algo_impls.wrappers.episo... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/vec_env/microrts.py | 0.792344 | 0.289833 | microrts.py | pypi |
from typing import Dict, List, Optional, TypeVar
import gym
import numpy as np
from gym.vector.vector_env import VectorEnv
from stable_baselines3.common.vec_env.base_vec_env import tile_images
from rl_algo_impls.wrappers.lux_env_gridnet import LuxEnvGridnet, LuxRewardWeights
from rl_algo_impls.wrappers.vectorable_wra... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/vec_env/vec_lux_env.py | 0.803482 | 0.495361 | vec_lux_env.py | pypi |
import os
from dataclasses import astuple
from typing import Callable, Optional
import gym
from gym.vector.async_vector_env import AsyncVectorEnv
from gym.vector.sync_vector_env import SyncVectorEnv
from gym.wrappers.frame_stack import FrameStack
from gym.wrappers.gray_scale_observation import GrayScaleObservation
fro... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/vec_env/vec_env.py | 0.739422 | 0.356783 | vec_env.py | pypi |
from dataclasses import astuple
from typing import Callable, Dict, Optional
import gym
from torch.utils.tensorboard.writer import SummaryWriter
from rl_algo_impls.runner.config import Config, EnvHyperparams
from rl_algo_impls.shared.vec_env.lux_async_vector_env import LuxAsyncVectorEnv
from rl_algo_impls.shared.vec_e... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/vec_env/lux.py | 0.859015 | 0.295538 | lux.py | pypi |
from dataclasses import astuple
from typing import Optional
import gym
import numpy as np
from torch.utils.tensorboard.writer import SummaryWriter
from rl_algo_impls.runner.config import Config, EnvHyperparams
from rl_algo_impls.wrappers.episode_stats_writer import EpisodeStatsWriter
from rl_algo_impls.wrappers.hwc_t... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/vec_env/procgen.py | 0.732305 | 0.359561 | procgen.py | pypi |
import multiprocessing as mp
import sys
import time
from copy import deepcopy
from ctypes import c_bool
from enum import Enum
from typing import Any, List, Optional, Union
import numpy as np
from gym import logger
from gym.error import (
AlreadyPendingCallError,
ClosedEnvironmentError,
CustomSpaceError,
... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/vec_env/lux_async_vector_env.py | 0.774541 | 0.404566 | lux_async_vector_env.py | pypi |
from dataclasses import asdict
from typing import Any, Dict, Optional
from torch.utils.tensorboard.writer import SummaryWriter
from rl_algo_impls.runner.config import Config, EnvHyperparams
from rl_algo_impls.shared.vec_env.lux import make_lux_env
from rl_algo_impls.shared.vec_env.microrts import make_microrts_env
fr... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/vec_env/make_env.py | 0.819893 | 0.171096 | make_env.py | pypi |
from typing import Optional, Sequence, Type
import gym
import torch
import torch.nn as nn
from rl_algo_impls.shared.encoder.cnn import FlattenedCnnEncoder
from rl_algo_impls.shared.module.utils import layer_init
class ResidualBlock(nn.Module):
def __init__(
self,
channels: int,
activatio... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/encoder/impala_cnn.py | 0.969252 | 0.355775 | impala_cnn.py | pypi |
from typing import Dict, Optional, Sequence, Type
import gym
import torch
import torch.nn as nn
import torch.nn.functional as F
from gym.spaces import Box, Discrete
from stable_baselines3.common.preprocessing import get_flattened_obs_dim
from rl_algo_impls.shared.encoder.cnn import CnnEncoder
from rl_algo_impls.share... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/encoder/encoder.py | 0.951063 | 0.258823 | encoder.py | pypi |
from typing import Optional, Tuple, Type, Union
import gym
import torch
import torch.nn as nn
from rl_algo_impls.shared.encoder.cnn import CnnEncoder, EncoderOutDim
from rl_algo_impls.shared.module.utils import layer_init
class GridnetEncoder(CnnEncoder):
"""
Encoder for encoder-decoder for Gym-MicroRTS
... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/encoder/gridnet_encoder.py | 0.958148 | 0.280051 | gridnet_encoder.py | pypi |
from typing import Optional, Tuple, Type
import gym
import torch.nn as nn
from gym.spaces import Box, Discrete, MultiDiscrete
from rl_algo_impls.shared.actor.actor import Actor
from rl_algo_impls.shared.actor.categorical import CategoricalActorHead
from rl_algo_impls.shared.actor.gaussian import GaussianActorHead
fro... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/actor/make_actor.py | 0.910764 | 0.33066 | make_actor.py | pypi |
from typing import Dict, Optional, Tuple, Type
import numpy as np
import torch
import torch.nn as nn
from numpy.typing import NDArray
from torch.distributions import Distribution, constraints
from rl_algo_impls.shared.actor import Actor, PiForward, pi_forward
from rl_algo_impls.shared.actor.categorical import MaskedC... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/actor/gridnet.py | 0.954563 | 0.561515 | gridnet.py | pypi |
from typing import Dict, Optional, Tuple, Type
import numpy as np
import torch
import torch.nn as nn
from numpy.typing import NDArray
from torch.distributions import Distribution, constraints
from rl_algo_impls.shared.actor.actor import Actor, PiForward, pi_forward
from rl_algo_impls.shared.actor.categorical import M... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/actor/multi_discrete.py | 0.942599 | 0.489381 | multi_discrete.py | pypi |
from typing import Optional, Tuple, Type
import numpy as np
import torch
import torch.nn as nn
from numpy.typing import NDArray
from rl_algo_impls.shared.actor import Actor, PiForward, pi_forward
from rl_algo_impls.shared.actor.gridnet import GridnetDistribution
from rl_algo_impls.shared.encoder import EncoderOutDim
... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/actor/gridnet_decoder.py | 0.954223 | 0.415195 | gridnet_decoder.py | pypi |
from typing import Optional, Tuple, Type, TypeVar, Union
import torch
import torch.nn as nn
from torch.distributions import Distribution, Normal
from rl_algo_impls.shared.actor.actor import Actor, PiForward
from rl_algo_impls.shared.module.utils import mlp
class TanhBijector:
def __init__(self, epsilon: float =... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/shared/actor/state_dependent_noise.py | 0.969252 | 0.694076 | state_dependent_noise.py | pypi |
import logging
from collections import defaultdict
from dataclasses import asdict, dataclass
from typing import List, Optional, Sequence, TypeVar
import numpy as np
import torch
import torch.nn as nn
from torch.optim import Adam
from torch.utils.tensorboard.writer import SummaryWriter
from rl_algo_impls.shared.algori... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/vpg/vpg.py | 0.89945 | 0.328907 | vpg.py | pypi |
from typing import Optional, Sequence, Tuple
import numpy as np
import torch
import torch.nn as nn
from rl_algo_impls.shared.actor import Actor, PiForward, actor_head
from rl_algo_impls.shared.encoder import Encoder
from rl_algo_impls.shared.policy.actor_critic import OnPolicy, Step, clamp_actions
from rl_algo_impls.... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/vpg/policy.py | 0.953837 | 0.277742 | policy.py | pypi |
import os
import pandas as pd
import wandb.apis.public
import yaml
from collections import defaultdict
from dataclasses import dataclass, asdict
from typing import Any, Dict, Iterable, List, NamedTuple, Optional, TypeVar
from urllib.parse import urlparse
from rl_algo_impls.runner.evaluate import Evaluation
Evaluatio... | /rl_algo_impls-0.0.13.tar.gz/rl_algo_impls-0.0.13/rl_algo_impls/publish/markdown_format.py | 0.4231 | 0.677741 | markdown_format.py | pypi |
from typing import List
from ..Agent import Agent
import numpy as np
class MonteCarlo(Agent):
def __init__(self, actions: List, gamma: float, eps: float):
super().__init__()
self.actions = actions
self.gamma = gamma
self.eps = eps
self.q_n = {} # q-value & number of pri... | /rl_algorithms-0.0.4.tar.gz/rl_algorithms-0.0.4/rl_algorithms/montecarlo/MonteCarlo.py | 0.937204 | 0.514156 | MonteCarlo.py | pypi |
from typing import List
from ..Agent import Agent
import numpy as np
class Sarsa(Agent):
def __init__(self, actions: List, alpha: float, gamma: float, eps: float):
super().__init__()
self.actions = actions
self.alpha = alpha
self.gamma = gamma
self.eps = eps
self... | /rl_algorithms-0.0.4.tar.gz/rl_algorithms-0.0.4/rl_algorithms/sarsa/Sarsa.py | 0.918068 | 0.474449 | Sarsa.py | pypi |
from typing import List
from ..Agent import Agent
import numpy as np
class NStepSarsa(Agent):
def __init__(self, actions: List, alpha: float, gamma: float, eps: float, n: int):
super().__init__()
self.actions = actions
self.alpha = alpha
self.gamma = gamma
self.eps = eps
... | /rl_algorithms-0.0.4.tar.gz/rl_algorithms-0.0.4/rl_algorithms/sarsa/NStepSarsa.py | 0.933628 | 0.47384 | NStepSarsa.py | pypi |
import collections
from copy import deepcopy
from typing import List
import torch
from ..Agent import Agent
import numpy as np
from torch import nn
class DSN(Agent):
def __init__(self, network: nn.Module, actions: List, alpha: float, gamma: float, eps: float, c: int = 128, t: int = 1024, capacity: int = 1024, ... | /rl_algorithms-0.0.4.tar.gz/rl_algorithms-0.0.4/rl_algorithms/sarsa/DSN.py | 0.926145 | 0.520557 | DSN.py | pypi |
from typing import List
from ..Agent import Agent
import numpy as np
class QLearning(Agent):
def __init__(self, actions: List, alpha: float, gamma: float, eps: float):
super().__init__()
self.actions = actions
self.alpha = alpha
self.gamma = gamma
self.eps = eps
... | /rl_algorithms-0.0.4.tar.gz/rl_algorithms-0.0.4/rl_algorithms/qlearning/QLearning.py | 0.924227 | 0.474266 | QLearning.py | pypi |
import collections
from copy import deepcopy
from typing import List
import torch
from ..Agent import Agent
import numpy as np
from torch import nn
class DQN(Agent):
def __init__(self, network: nn.Module, actions: List, alpha: float, gamma: float, eps: float, c: int = 128, t: int = 1024, capacity: int = 1024, ... | /rl_algorithms-0.0.4.tar.gz/rl_algorithms-0.0.4/rl_algorithms/qlearning/DQN.py | 0.919575 | 0.511473 | DQN.py | pypi |
from copy import deepcopy
from typing import List
from torch.nn.functional import cross_entropy
from ..Agent import Agent
import numpy as np
import torch
from torch import nn
from torch.distributions.categorical import Categorical
class OptionCritic(Agent):
def __init__(self, option_net:nn.Module, action_net:... | /rl_algorithms-0.0.4.tar.gz/rl_algorithms-0.0.4/rl_algorithms/policy/OptionCritic.py | 0.957308 | 0.401013 | OptionCritic.py | pypi |
from copy import deepcopy
from typing import List
from torch.nn.functional import cross_entropy
from ..Agent import Agent
import numpy as np
import torch
from torch import nn
from torch.distributions.categorical import Categorical
class ActorCritic(Agent):
def __init__(self, policy_net: nn.Module, v_net: nn.M... | /rl_algorithms-0.0.4.tar.gz/rl_algorithms-0.0.4/rl_algorithms/policy/ActorCritic.py | 0.955703 | 0.449453 | ActorCritic.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from rl_benchmark.util import n_step_average
def rewards_by_episode(rewards, cut_x=1e12, *args, **kwargs):
episodes = np.arange(len(rewards))
episodes, rewards... | /rl-benchmark-0.0.4.tar.gz/rl-benchmark-0.0.4/rl_benchmark/analyze/transform.py | 0.874265 | 0.262771 | transform.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from rl_benchmark.analyze.transform import rewards_by_episode, rewards_by_timestep, rewards_by_second, \
to_timeseries
class Re... | /rl-benchmark-0.0.4.tar.gz/rl-benchmark-0.0.4/rl_benchmark/analyze/plotter/result_plotter.py | 0.850282 | 0.199737 | result_plotter.py | pypi |
# Coach
[](https://circleci.com/gh/NervanaSystems/workflows/coach/tree/master)
[](https://github.com/NervanaSystems/coach/blob/master/LICENSE)
[:
"""
ABC for saver objects that implement saving/restoring to/from path, and merging two savers.
"""
@property
def path(self):
"""
Relative path for save/load. If two saver objects return the same path, they must be merge-able.... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/saver.py | 0.875268 | 0.393414 | saver.py | pypi |
import argparse
import os
import matplotlib
import matplotlib.pyplot as plt
from rl_coach.dashboard_components.signals_file import SignalsFile
class FigureMaker(object):
def __init__(self, path, cols, smoothness, signal_to_plot, x_axis, color):
self.experiments_path = path
self.environments = s... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/plot_atari.py | 0.639961 | 0.397588 | plot_atari.py | pypi |
import inspect
import json
import os
import sys
import types
from collections import OrderedDict
from enum import Enum
from typing import Dict, List, Union
from rl_coach.core_types import TrainingSteps, EnvironmentSteps, GradientClippingMethod, RunPhase, \
SelectedPhaseOnlyDumpFilter, MaxDumpFilter
from rl_coach.f... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/base_parameters.py | 0.590425 | 0.199932 | base_parameters.py | pypi |
import numpy as np
import contextlib
with contextlib.redirect_stdout(None):
import pygame
from pygame.locals import HWSURFACE, DOUBLEBUF
class Renderer(object):
def __init__(self):
self.size = (1, 1)
self.screen = None
self.clock = pygame.time.Clock()
self.display = pygame.dis... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/renderer.py | 0.689096 | 0.4575 | renderer.py | pypi |
import time
import os
from rl_coach.base_parameters import TaskParameters, DistributedCoachSynchronizationType
from rl_coach.checkpoint import CheckpointStateFile, CheckpointStateReader
from rl_coach.data_stores.data_store import SyncFiles
def wait_for(wait_func, data_store=None, timeout=10):
"""
block until... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/rollout_worker.py | 0.422624 | 0.166303 | rollout_worker.py | pypi |
from typing import List, Tuple
import numpy as np
from rl_coach.core_types import EnvironmentSteps
class Schedule(object):
def __init__(self, initial_value: float):
self.initial_value = initial_value
self.current_value = initial_value
def step(self):
raise NotImplementedError("")
... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/schedules.py | 0.938365 | 0.623893 | schedules.py | pypi |
import copy
import datetime
import os
import sys
import time
from itertools import cycle
from os import listdir
from os.path import isfile, join, isdir
from bokeh.layouts import row, column, Spacer, ToolbarBox
from bokeh.models import ColumnDataSource, Range1d, LinearAxis, Legend, \
WheelZoomTool, CrosshairTool,... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/dashboard_components/experiment_board.py | 0.40486 | 0.214527 | experiment_board.py | pypi |
from bokeh.layouts import row, column, widgetbox, Spacer
from bokeh.models import ColumnDataSource, Range1d, LinearAxis, Legend
from bokeh.models.widgets import RadioButtonGroup, MultiSelect, Button, Select, Slider, Div, CheckboxGroup, Toggle
from bokeh.plotting import figure
from rl_coach.dashboard_components.global... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/dashboard_components/episodic_board.py | 0.669205 | 0.369287 | episodic_board.py | pypi |
from collections import OrderedDict
import os
from genericpath import isdir, isfile
from os import listdir
from os.path import join
from enum import Enum
from bokeh.models import Div
from bokeh.plotting import curdoc
import tkinter as tk
from tkinter import filedialog
import colorsys
from rl_coach.core_types import T... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/dashboard_components/globals.py | 0.449151 | 0.179387 | globals.py | pypi |
import random
import numpy as np
from bokeh.models import ColumnDataSource
from bokeh.palettes import Dark2
from rl_coach.dashboard_components.globals import show_spinner, hide_spinner, current_color
from rl_coach.utils import squeeze_list
class Signal:
def __init__(self, name, parent, plot):
self.name... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/dashboard_components/signals.py | 0.507812 | 0.202778 | signals.py | pypi |
from typing import List
import numpy as np
from rl_coach.core_types import RunPhase, ActionType, EnvironmentSteps
from rl_coach.exploration_policies.additive_noise import AdditiveNoiseParameters
from rl_coach.exploration_policies.e_greedy import EGreedy, EGreedyParameters
from rl_coach.exploration_policies.explorati... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/exploration_policies/ucb.py | 0.940599 | 0.547162 | ucb.py | pypi |
from typing import List
import numpy as np
from rl_coach.core_types import RunPhase, ActionType
from rl_coach.exploration_policies.exploration_policy import DiscreteActionExplorationPolicy, ExplorationParameters
from rl_coach.schedules import Schedule
from rl_coach.spaces import ActionSpace
class BoltzmannParamete... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/exploration_policies/boltzmann.py | 0.918521 | 0.525978 | boltzmann.py | pypi |
from typing import List
import numpy as np
from rl_coach.core_types import RunPhase, ActionType
from rl_coach.exploration_policies.additive_noise import AdditiveNoiseParameters
from rl_coach.exploration_policies.e_greedy import EGreedy, EGreedyParameters
from rl_coach.exploration_policies.exploration_policy import E... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/exploration_policies/bootstrapped.py | 0.932584 | 0.577972 | bootstrapped.py | pypi |
from typing import List
from rl_coach.base_parameters import Parameters
from rl_coach.core_types import RunPhase, ActionType
from rl_coach.spaces import ActionSpace, DiscreteActionSpace, BoxActionSpace, GoalsSpace
class ExplorationParameters(Parameters):
def __init__(self):
self.action_space = None
... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/exploration_policies/exploration_policy.py | 0.91633 | 0.568655 | exploration_policy.py | pypi |
from typing import List
import numpy as np
from rl_coach.core_types import RunPhase, ActionType
from rl_coach.exploration_policies.exploration_policy import ContinuousActionExplorationPolicy, ExplorationParameters
from rl_coach.spaces import ActionSpace, BoxActionSpace, GoalsSpace
# Based on on the description in:... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/exploration_policies/ou_process.py | 0.905989 | 0.403332 | ou_process.py | pypi |
from typing import List
import numpy as np
from rl_coach.core_types import RunPhase, ActionType
from rl_coach.exploration_policies.exploration_policy import ContinuousActionExplorationPolicy, ExplorationParameters
from rl_coach.schedules import Schedule, LinearSchedule
from rl_coach.spaces import ActionSpace, BoxAct... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/exploration_policies/additive_noise.py | 0.6508 | 0.612049 | additive_noise.py | pypi |
from typing import List, Dict
import numpy as np
from rl_coach.architectures.layers import NoisyNetDense
from rl_coach.base_parameters import AgentParameters, NetworkParameters
from rl_coach.spaces import ActionSpace, BoxActionSpace, DiscreteActionSpace
from rl_coach.core_types import ActionType
from rl_coach.explo... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/exploration_policies/parameter_noise.py | 0.946886 | 0.576125 | parameter_noise.py | pypi |
from typing import List
import numpy as np
from scipy.stats import truncnorm
from rl_coach.core_types import RunPhase, ActionType
from rl_coach.exploration_policies.exploration_policy import ExplorationParameters, ContinuousActionExplorationPolicy
from rl_coach.schedules import Schedule, LinearSchedule
from rl_coach... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/exploration_policies/truncated_normal.py | 0.927593 | 0.637313 | truncated_normal.py | pypi |
from enum import Enum
from typing import Union, List
import numpy as np
from rl_coach.filters.observation.observation_move_axis_filter import ObservationMoveAxisFilter
try:
from pysc2 import maps
from pysc2.env import sc2_env
from pysc2.env import available_actions_printer
from pysc2.lib import act... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/environments/starcraft2_environment.py | 0.810629 | 0.387111 | starcraft2_environment.py | pypi |
import random
from enum import Enum
from typing import Union
import numpy as np
try:
from dm_control import suite
from dm_control.suite.wrappers import pixels
except ImportError:
from rl_coach.logger import failed_imports
failed_imports.append("DeepMind Control Suite")
from rl_coach.base_parameter... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/environments/control_suite_environment.py | 0.892217 | 0.541833 | control_suite_environment.py | pypi |
from typing import Union, Dict
from rl_coach.core_types import ActionType, EnvResponse, RunPhase
from rl_coach.spaces import ActionSpace
class EnvironmentInterface(object):
def __init__(self):
self._phase = RunPhase.UNDEFINED
@property
def phase(self) -> RunPhase:
"""
Get the ph... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/environments/environment_interface.py | 0.926968 | 0.414899 | environment_interface.py | pypi |
import os
import gym
import numpy as np
from gym import spaces
from gym.envs.registration import EnvSpec
from mujoco_py import load_model_from_path, MjSim, MjViewer, MjRenderContextOffscreen
class PendulumWithGoals(gym.Env):
metadata = {
'render.modes': ['human', 'rgb_array'], 'video.frames_per_second':... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/environments/mujoco/pendulum_with_goals.py | 0.641198 | 0.317413 | pendulum_with_goals.py | pypi |
import random
import gym
import numpy as np
from gym import spaces
class BitFlip(gym.Env):
metadata = {
'render.modes': ['human', 'rgb_array'], 'video.frames_per_second': 30
}
def __init__(self, bit_length=16, max_steps=None, mean_zero=False):
super(BitFlip, self).__init__()
if ... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/environments/toy_problems/bit_flip.py | 0.712232 | 0.38604 | bit_flip.py | pypi |
from enum import Enum
import gym
import numpy as np
from gym import spaces
class ExplorationChain(gym.Env):
metadata = {
'render.modes': ['human', 'rgb_array'], 'video.frames_per_second': 30
}
class ObservationType(Enum):
OneHot = 0
Therm = 1
def __init__(self, chain_length... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/environments/toy_problems/exploration_chain.py | 0.868172 | 0.521837 | exploration_chain.py | pypi |
from typing import Tuple, List
from rl_coach.base_parameters import AgentParameters, VisualizationParameters, TaskParameters, \
PresetValidationParameters
from rl_coach.environments.environment import EnvironmentParameters, Environment
from rl_coach.filters.filter import NoInputFilter, NoOutputFilter
from rl_coach... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/graph_managers/basic_rl_graph_manager.py | 0.698535 | 0.343424 | basic_rl_graph_manager.py | pypi |
from typing import List, Union, Tuple
from rl_coach.base_parameters import AgentParameters, VisualizationParameters, TaskParameters, \
PresetValidationParameters
from rl_coach.core_types import EnvironmentSteps
from rl_coach.environments.environment import EnvironmentParameters, Environment
from rl_coach.graph_man... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/graph_managers/hac_graph_manager.py | 0.893491 | 0.590366 | hac_graph_manager.py | pypi |
from typing import List, Type, Union
from rl_coach.base_parameters import MiddlewareScheme, NetworkComponentParameters
class MiddlewareParameters(NetworkComponentParameters):
def __init__(self, parameterized_class_name: str,
activation_function: str='relu', scheme: Union[List, MiddlewareScheme]... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/middleware_parameters.py | 0.917168 | 0.209066 | middleware_parameters.py | pypi |
from typing import Any, Dict, List, Tuple
import numpy as np
from rl_coach.base_parameters import AgentParameters
from rl_coach.saver import SaverCollection
from rl_coach.spaces import SpacesDefinition
class Architecture(object):
@staticmethod
def construct(variable_scope: str, devices: List[str], *args, *... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/architecture.py | 0.96606 | 0.664282 | architecture.py | pypi |
from typing import Type
from rl_coach.base_parameters import NetworkComponentParameters
class HeadParameters(NetworkComponentParameters):
def __init__(self, parameterized_class_name: str, activation_function: str = 'relu', name: str= 'head',
num_output_head_copies: int=1, rescale_gradient_from_... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/head_parameters.py | 0.947308 | 0.25303 | head_parameters.py | pypi |
from typing import List, Tuple
from rl_coach.base_parameters import Frameworks, AgentParameters
from rl_coach.logger import failed_imports
from rl_coach.saver import SaverCollection
from rl_coach.spaces import SpacesDefinition
from rl_coach.utils import force_list
class NetworkWrapper(object):
"""
The netwo... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/network_wrapper.py | 0.934492 | 0.364297 | network_wrapper.py | pypi |
from types import FunctionType
from mxnet.gluon import nn
from rl_coach.architectures import layers
from rl_coach.architectures.mxnet_components import utils
# define global dictionary for storing layer type to layer implementation mapping
mx_layer_dict = dict()
def reg_to_mx(layer_type) -> FunctionType:
""" ... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/layers.py | 0.946057 | 0.473657 | layers.py | pypi |
import copy
from typing import Any, Dict, Generator, List, Tuple, Union
import numpy as np
import mxnet as mx
from mxnet import autograd, gluon, nd
from mxnet.ndarray import NDArray
from rl_coach.architectures.architecture import Architecture
from rl_coach.architectures.mxnet_components.heads.head import LOSS_OUT_TY... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/architecture.py | 0.858748 | 0.272617 | architecture.py | pypi |
from typing import Any, List, Tuple
from mxnet import gluon, sym
from mxnet.contrib import onnx as onnx_mxnet
import numpy as np
from rl_coach.architectures.mxnet_components.utils import ScopedOnnxEnable
from rl_coach.saver import Saver
class ParameterDictSaver(Saver):
"""
Child class that implements save... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/savers.py | 0.908303 | 0.350199 | savers.py | pypi |
import copy
from itertools import chain
from typing import List, Tuple, Union
from types import ModuleType
import numpy as np
import mxnet as mx
from mxnet import nd, sym
from mxnet.gluon import HybridBlock
from mxnet.ndarray import NDArray
from mxnet.symbol import Symbol
from rl_coach.base_parameters import Network... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/general_network.py | 0.86421 | 0.246851 | general_network.py | pypi |
import inspect
from typing import Any, Dict, Generator, Iterable, List, Tuple, Union
from types import ModuleType
import mxnet as mx
from mxnet import gluon, nd
from mxnet.ndarray import NDArray
import numpy as np
from rl_coach.core_types import GradientClippingMethod
nd_sym_type = Union[mx.nd.NDArray, mx.sym.Symbol... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/utils.py | 0.924628 | 0.547827 | utils.py | pypi |
from typing import Union
from types import ModuleType
import mxnet as mx
from mxnet.gluon import rnn
from rl_coach.architectures.mxnet_components.layers import Dense
from rl_coach.architectures.mxnet_components.middlewares.middleware import Middleware
from rl_coach.architectures.middleware_parameters import LSTMMiddle... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/middlewares/lstm_middleware.py | 0.948131 | 0.350477 | lstm_middleware.py | pypi |
from typing import Union
from types import ModuleType
import mxnet as mx
from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
from rl_coach.architectures.mxnet_components.embedders.embedder import InputEmbedder
nd_sym_type = Union[mx.nd.NDArray, mx.sym.Symbol]
class TensorEmbedder(InputEmb... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/embedders/tensor_embedder.py | 0.9504 | 0.507019 | tensor_embedder.py | pypi |
from typing import Union
from types import ModuleType
import mxnet as mx
from mxnet import nd, sym
from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
from rl_coach.architectures.mxnet_components.embedders.embedder import InputEmbedder
from rl_coach.architectures.mxnet_components.layers impo... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/embedders/vector_embedder.py | 0.94388 | 0.418756 | vector_embedder.py | pypi |
from typing import Union
from types import ModuleType
import mxnet as mx
from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
from rl_coach.architectures.mxnet_components.embedders.embedder import InputEmbedder
from rl_coach.architectures.mxnet_components.layers import Conv2d
from rl_coach.ba... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/embedders/image_embedder.py | 0.96738 | 0.46308 | image_embedder.py | pypi |
from typing import Union, List, Tuple
from types import ModuleType
import mxnet as mx
from mxnet.gluon.loss import Loss, HuberLoss, L2Loss
from mxnet.gluon import nn
from rl_coach.architectures.mxnet_components.heads.head import Head, HeadLoss, LossInputSchema,\
NormalizedRSSInitializer
from rl_coach.architecture... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/heads/v_head.py | 0.976389 | 0.445288 | v_head.py | pypi |
from typing import Dict, List, Union, Tuple
import mxnet as mx
from mxnet.initializer import Initializer, register
from mxnet.gluon import nn, loss
from mxnet.ndarray import NDArray
from mxnet.symbol import Symbol
from rl_coach.base_parameters import AgentParameters
from rl_coach.spaces import SpacesDefinition
LOS... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/heads/head.py | 0.960915 | 0.573081 | head.py | pypi |
from typing import List, Tuple, Union
from types import ModuleType
import mxnet as mx
from mxnet.gluon import nn
from rl_coach.architectures.mxnet_components.heads.head import Head, HeadLoss, LossInputSchema,\
NormalizedRSSInitializer
from rl_coach.architectures.mxnet_components.heads.head import LOSS_OUT_TYPE_L... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/heads/ppo_v_head.py | 0.971252 | 0.489015 | ppo_v_head.py | pypi |
from typing import Union, List, Tuple
from types import ModuleType
import mxnet as mx
from mxnet.gluon.loss import Loss, HuberLoss, L2Loss
from mxnet.gluon import nn
from rl_coach.architectures.mxnet_components.heads.head import Head, HeadLoss, LossInputSchema
from rl_coach.architectures.mxnet_components.heads.head ... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/mxnet_components/heads/q_head.py | 0.974893 | 0.45308 | q_head.py | pypi |
from typing import Tuple
import tensorflow as tf
def create_cluster_spec(parameters_server: str, workers: str) -> tf.train.ClusterSpec:
"""
Creates a ClusterSpec object representing the cluster.
:param parameters_server: comma-separated list of hostname:port pairs to which the parameter servers are assi... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/distributed_tf_utils.py | 0.93739 | 0.62134 | distributed_tf_utils.py | pypi |
import math
from types import FunctionType
import tensorflow as tf
from rl_coach.architectures import layers
from rl_coach.architectures.tensorflow_components import utils
def batchnorm_activation_dropout(input_layer, batchnorm, activation_function, dropout_rate, is_training, name):
layers = [input_layer]
... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/layers.py | 0.843315 | 0.475605 | layers.py | pypi |
from typing import Union, List
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.architectures.tensorflow_components.middlewares.middleware import Middleware
from rl_coach.base_parameters import MiddlewareScheme
from rl_coach.core_types import Middleware_FC_Em... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/middlewares/fc_middleware.py | 0.879406 | 0.262254 | fc_middleware.py | pypi |
import numpy as np
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.architectures.tensorflow_components.middlewares.middleware import Middleware
from rl_coach.base_parameters import MiddlewareScheme
from rl_coach.core_types import Middleware_LSTM_Embedding
f... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/middlewares/lstm_middleware.py | 0.881793 | 0.242935 | lstm_middleware.py | pypi |
from typing import List
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Conv2d, Dense
from rl_coach.architectures.tensorflow_components.embedders.embedder import InputEmbedder
from rl_coach.base_parameters import EmbedderScheme
from rl_coach.core_types import InputTensorEmbedd... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/embedders/tensor_embedder.py | 0.953177 | 0.591989 | tensor_embedder.py | pypi |
from typing import List
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Conv2d, Dense
from rl_coach.architectures.tensorflow_components.embedders.embedder import InputEmbedder
from rl_coach.base_parameters import EmbedderScheme
from rl_coach.core_types import InputImageEmbeddi... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/embedders/image_embedder.py | 0.947805 | 0.500183 | image_embedder.py | pypi |
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.architectures.tensorflow_components.heads.q_head import QHead
from rl_coach.base_parameters import AgentParameters
from rl_coach.spaces import SpacesDefinition
class DuelingQHead(QHead):
def __init__(self... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/heads/dueling_q_head.py | 0.820254 | 0.296024 | dueling_q_head.py | pypi |
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.architectures.tensorflow_components.heads.head import Head
from rl_coach.base_parameters import AgentParameters
from rl_coach.core_types import ActionProbabilities
from rl_coach.spaces import SpacesDefinition
f... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/heads/sac_head.py | 0.847274 | 0.292829 | sac_head.py | pypi |
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.architectures.tensorflow_components.heads.head import Head
from rl_coach.base_parameters import AgentParameters
from rl_coach.core_types import QActionStateValue
from rl_coach.spaces import BoxActionSpace
from ... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/heads/naf_head.py | 0.894011 | 0.314011 | naf_head.py | pypi |
import numpy as np
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.architectures.tensorflow_components.heads.head import Head, normalized_columns_initializer
from rl_coach.base_parameters import AgentParameters
from rl_coach.core_types import ActionProbabili... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/heads/policy_head.py | 0.855987 | 0.361052 | policy_head.py | pypi |
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.architectures.tensorflow_components.heads.head import Head
from rl_coach.base_parameters import AgentParameters
from rl_coach.core_types import QActionStateValue
from rl_coach.spaces import SpacesDefinition, Bo... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/heads/sac_q_head.py | 0.877857 | 0.369599 | sac_q_head.py | pypi |
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.architectures.tensorflow_components.heads.head import Head, normalized_columns_initializer
from rl_coach.base_parameters import AgentParameters
from rl_coach.core_types import VStateValue
from rl_coach.spaces i... | /rl-coach-slim-1.0.1.tar.gz/rl-coach-slim-1.0.1/rl_coach/architectures/tensorflow_components/heads/v_head.py | 0.870515 | 0.251165 | v_head.py | pypi |
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