Functions — github.com/Ericonaldo/ILSwiss

↓ 1 callersMethodreset

(self)

rlkit/envs/worker/subproc.py:161

↓ 1 callersFunctionreset_execution_environment

Call this between calls to separate experiments. :return:

rlkit/launchers/launcher_util.py:347

↓ 1 callersFunctionrollout

( env, policy, max_path_length, no_terminal=False, render=False, render_kwargs={},

rlkit/samplers/normal_sampler.py:5

↓ 1 callersFunctionsafe_json

(data)

rlkit/launchers/launcher_util.py:318

↓ 1 callersMethodsample_all_trajs

( self, keys=None, samples_per_traj=None, )

rlkit/data_management/simple_replay_buffer.py:374

↓ 1 callersMethodsample_n

(self, n)

rlkit/torch/common/distributions.py:30

↓ 1 callersFunctionsave_experiment_data

(dictionary, log_dir)

rlkit/launchers/launcher_util.py:99

↓ 1 callersFunctionsave_plot

(x, y, title, save_path, color="cyan", x_axis_lims=None, y_axis_lims=None)

rlkit/core/vistools.py:145

↓ 1 callersFunctionsave_video

(video_frames, filename, fps=60, video_format="mp4")

run_scripts/video.py:12

↓ 1 callersMethodseed

(self, seed: Optional[int] = None)

rlkit/envs/worker/subproc.py:197

↓ 1 callersFunctionset_gpu_mode

(mode, gpu_id=0)

rlkit/torch/utils/pytorch_util.py:55

↓ 1 callersMethodset_num_steps_total

(self, t)

rlkit/policies/base.py:23

↓ 1 callersMethodset_param_values

(self, param_values)

rlkit/torch/core.py:16

↓ 1 callersMethodset_steps

( self, n_env_steps_total, n_rollouts_total, n_train_steps_total, n_pr

rlkit/core/base_algorithm.py:548

↓ 1 callersFunctionset_tboard

(dir_name, name="tboard")

rlkit/core/logger.py:128

↓ 1 callersFunctionset_wandb

(dir_name, variant)

rlkit/core/logger.py:134

↓ 1 callersMethodstart_training

(self, start_epoch=0)

rlkit/core/base_algorithm.py:162

↓ 1 callersMethodterminate

(self)

rlkit/envs/wrappers.py:38

↓ 1 callersMethodterminate_episode

(self)

rlkit/data_management/simple_replay_buffer.py:125

↓ 1 callersFunctiontie_weights

(src, trg)

rlkit/torch/common/encoders.py:6

↓ 1 callersMethodto

(self, device)

rlkit/torch/algorithms/sac/sac_ae.py:422

↓ 1 callersMethodto

(self, device)

rlkit/torch/algorithms/mbpo/mbpo.py:277

↓ 1 callersMethodto

(self, device)

rlkit/torch/algorithms/mbpo/bnn_trainer.py:277

↓ 1 callersMethodtrain_ac

(self, batch)

rlkit/torch/algorithms/sac/sac_ae.py:210

↓ 1 callersMethodtrain_cpc

(self, batch)

rlkit/torch/algorithms/sac/sac_ae.py:143

↓ 1 callersMethodtrain_encdec

(self, batch)

rlkit/torch/algorithms/sac/sac_ae.py:174

↓ 1 callersMethodtransform

(self, inputs)

rlkit/torch/utils/transform_layer.py:196

↓ 1 callersMethodvariants

(self, randomized=False)

rlkit/launchers/launcher_util.py:554

↓ 1 callersMethodwait

Given a list of workers, return those ready ones.

rlkit/envs/worker/base.py:44

MethodDOWN

(self, n=1)

rlkit/data_management/mil_color_print.py:55

MethodPOS

(self, x=1, y=1)

rlkit/data_management/mil_color_print.py:64

Method__enter__

(self)

rlkit/data_management/mil_utils.py:88

Method__exit__

(self, exc_type, exc_val, exc_tb)

rlkit/data_management/mil_utils.py:91

Method__getattr__

(self, attrname)

rlkit/envs/envpool.py:29

Method__getattr__

(self, attrname)

rlkit/envs/wrappers.py:45

Method__getattr__

(self, attrname)

rlkit/envs/wrappers.py:359

Method__getattr__

(self, key: str)

rlkit/envs/worker/base.py:17

Method__getattr__

(self, key: str)

rlkit/envs/worker/subproc.py:142

Method__getattr__

(self, key: str)

rlkit/envs/worker/dummy.py:15

Method__getattribute__

Switch the attribute getter depending on the key. Any class who inherits ``Env`` will inherit some attributes, like ``action_space``.

rlkit/envs/vecenvs.py:118

Method__getstate__

(self)

rlkit/torch/core.py:53

Method__getstate__

(self)

rlkit/envs/wrappers.py:324

Method__getstate__

(self)

rlkit/envs/worker/utils.py:10

Method__init__

( self, brightness=0, contrast=0, saturation=0, hue=0, p=0,

rlkit/torch/utils/transform_layer.py:90

Method__init__

(self, obs_shape, feature_dim, num_layers, num_filters, *args)

rlkit/torch/common/encoders.py:116

Method__init__

(self, obs_shape, feature_dim, num_layers=2, num_filters=32)

rlkit/torch/common/encoders.py:133

Method__init__

(self, stochastic_policy)

rlkit/torch/common/policies.py:20

Method__init__

(self, hidden_sizes, obs_dim, action_dim, init_w=1e-3, **kwargs)

rlkit/torch/common/policies.py:49

Method__init__

( self, hidden_sizes, obs_dim, action_dim, init_w=1e-3, policy

rlkit/torch/common/policies.py:131

Method__init__

( self, hidden_sizes, obs_dim, action_dim, init_w=1e-3, max_ac

rlkit/torch/common/policies.py:210

Method__init__

( self, hidden_sizes, obs_dim, action_dim, conditioned_std=True,

rlkit/torch/common/policies.py:349

Method__init__

( self, hidden_sizes, obs_dim, action_dim, action_space, init_

rlkit/torch/common/policies.py:482

Method__init__

( self, obs_dim, condition_dim, action_dim, observation_key="observati

rlkit/torch/common/policies.py:570

Method__init__

( self, hidden_sizes, obs_dim, condition_dim, action_dim, acti

rlkit/torch/common/policies.py:653

Method__init__

( self, hidden_sizes, obs_dim, condition_dim, action_dim, obse

rlkit/torch/common/policies.py:708

Method__init__

(self, encoder, **kwargs)

rlkit/torch/common/policies.py:744

Method__init__

( self, hidden_sizes, obs_dim, action_dim, init_w=1e-3, **kwar

rlkit/torch/common/policies.py:760

Method__init__

( self, hidden_sizes, obs_dim, condition_dim, action_dim, obse

rlkit/torch/common/policies.py:832

Method__init__

(self, features, center=True, scale=False, eps=1e-6)

rlkit/torch/common/modules.py:24

Method__init__

( self, **kwargs, )

rlkit/torch/common/networks.py:119

Method__init__

(self, input_size: int, output_size: int, ensemble_size: int = 1)

rlkit/torch/common/networks.py:150

Method__init__

( self, hidden_sizes: List, output_size: int, input_size: int, init_w:

rlkit/torch/common/networks.py:175

Method__init__

(self, mean, log_sig_diag)

rlkit/torch/common/distributions.py:16

Method__init__

:param epsilon: Numerical stability epsilon when computing log-prob.

rlkit/torch/common/distributions.py:60

Method__init__

( self, trainer, batch_size, num_train_steps_per_train_call, *args, **kwargs )

rlkit/torch/algorithms/torch_rl_algorithm.py:8

Method__init__

( self, encoder: nn.Module, decoder: nn.Module, policy: nn.Module, qf1

rlkit/torch/algorithms/sac/sac_ae.py:24

Method__init__

( self, policy: nn.Module, qf1: nn.Module, qf2: nn.Module, vf: nn.Modu

rlkit/torch/algorithms/sac/sac.py:23

Method__init__

( self, policy: nn.Module, qf1: nn.Module, qf2: nn.Module, reward_scal

rlkit/torch/algorithms/sac/sac_alpha.py:21

Method__init__

:param env: :param qf: :param policy: :param exploration_policy: :param policy_learning_rate: :param

rlkit/torch/algorithms/ddpg/ddpg.py:21

Method__init__

( self, policy: nn.Module, qf1: nn.Module, qf2: nn.Module, reward_scal

rlkit/torch/algorithms/td3/td3.py:20

Method__init__

( self, replay_buffer=None, her_ratio=0.8, relabel_type="future", **kwargs )

rlkit/torch/algorithms/her/her.py:13

Method__init__

( self, policy, qf1, qf2, reward_scale=1.0, discount=0.99,

rlkit/torch/algorithms/her/td3.py:24

Method__init__

( self, policy, qf1, qf2, reward_scale=1.0, discount=0.99,

rlkit/torch/algorithms/her/sac.py:20

Method__init__

( self, env, model: BNNTrainer, algo: SoftActorCritic, # model-free algorithm

rlkit/torch/algorithms/mbpo/mbpo.py:24

Method__init__

(self, model: BNN, is_terminal: Callable, gen_model_idx: Callable)

rlkit/torch/algorithms/mbpo/fake_env.py:10

Method__init__

( self, bnn: BNN, lr: float = 1e-3, optimizer_class: Type[optim.Optimizer] = o

rlkit/torch/algorithms/mbpo/bnn_trainer.py:17

Method__init__

( self, replay_buffer=None, her_ratio=0.8, relabel_type="future", use_

rlkit/torch/algorithms/gcsl/rl.py:17

Method__init__

( self, policy, mode="MSE", reward_scale=1.0, discount=0.99, p

rlkit/torch/algorithms/gcsl/gcsl.py:21

Method__init__

( self, policy, vf, mini_batch_size=64, clip_eps=0.2, reward_s

rlkit/torch/algorithms/ppo/ppo.py:12

Method__init__

( self, mode, # 'MLE' or 'MSE' expert_replay_buffer, num_updates_per_train_ca

rlkit/torch/algorithms/bc/bc.py:15

Method__init__

:param env: Env. :param qf: QFunction. Maps from state to action Q-values. :param learning_rate: Learning rate for qf. Adam

rlkit/torch/algorithms/dqn/dqn.py:134

Method__init__

(self, encoder, **kwargs)

rlkit/torch/algorithms/adv_irl/adv_irl_visual.py:33

Method__init__

( self, mode, # airl, gail, or fairl discriminator, policy_trainer, e

rlkit/torch/algorithms/adv_irl/adv_irl.py:34

Method__init__

( self, input_dim, hid_dim=100, hid_act="relu", rnn_act="gru", # gru,

rlkit/torch/algorithms/adv_irl/disc_models/rnn_disc_models.py:6

Method__init__

( self, input_dim, num_layer_blocks=2, hid_dim=100, hid_act="relu",

rlkit/torch/algorithms/adv_irl/disc_models/simple_disc_models.py:52

Method__init__

( self, input_dim, num_layer_blocks=2, hid_dim=100, hid_act="relu",

rlkit/torch/algorithms/adv_irl/disc_models/cnn_disc_models.py:78

Method__init__

( self, policy, qf1, qf2, reward_scale=1.0, discount=0.99,

rlkit/torch/algorithms/discrete_sac/discrete_sac.py:23

Method__init__

( self, expert_policy, *args, unscale_for_expert=True, num_initial_tra

rlkit/torch/algorithms/dagger/dagger.py:14

Method__init__

:param max_replay_buffer_size: :param env:

rlkit/data_management/aug_replay_buffer.py:26

Method__init__

( self, max_replay_buffer_size, observation_dim, action_dim, random_seed=1995 )

rlkit/data_management/simple_replay_buffer.py:17

Method__init__

:param max_replay_buffer_size: :param env:

rlkit/data_management/env_replay_buffer.py:8

Method__init__

:param max_replay_buffer_size: :param env:

rlkit/data_management/relabel_replay_buffer.py:13

Method__init__

(self)

rlkit/data_management/mil_utils.py:44

Method__init__

(self, message)

rlkit/data_management/mil_utils.py:85

Method__init__

( self, max_sub_buf_size, observation_dim, action_dim, random_seed=199

rlkit/data_management/episodic_replay_buffer.py:13

Method__init__

(self)

rlkit/data_management/path_builder.py:34

Method__init__

:param max_replay_buffer_size: :param env:

rlkit/data_management/relabel_horizon_replay_buffer.py:10

Method__init__

( self, size, eps=1e-8, default_clip_range=np.inf, mean=0, std

rlkit/data_management/normalizer.py:9

Method__init__

(self, *args, **kwargs)

rlkit/data_management/normalizer.py:68

Method__init__

( self, size, default_clip_range=np.inf, mean=0, std=1, eps=1e

rlkit/data_management/normalizer.py:82

Functions830 in github.com/Ericonaldo/ILSwiss