Tianshou/docs/spelling_wordlist.txt

tianshou
arXiv
tanh
lr
logits
env
envs
optim
eps
timelimit
TimeLimit
envpool
EnvPool
maxsize
timestep
timesteps
numpy
ndarray
stackoverflow
tensorboard
state_dict
len
tac
fqf
iqn
qrdqn
rl
offpolicy
onpolicy
quantile
quantiles
dqn
param
async
subprocess
deque
nn
equ
cql
fn
boolean
pre
np
cuda
rnn
rew
pre
perceptron
bsz
dataset
mujoco
jit
nstep
preprocess
repo
ReLU
namespace
recv
th
utils
NaN
linesearch
hyperparameters
pseudocode
entropies
nn
config
cpu
rms
debias
indice
regularizer
miniblock
modularize
serializable
softmax
vectorized
optimizers
undiscounted
submodule
subclasses
submodules
tfevent
dirichlet
docstring
webpage
formatter
num
py
pythonic
中文文档位于
conda
miniconda
Amir
Andreas
Antonoglou
Beattie
Bellemare
Charles
Daan
Demis
Dharshan
Fidjeland
Georg
Hassabis
Helen
Ioannis
Kavukcuoglu
King
Koray
Kumaran
Legg
Mnih
Ostrovski
Petersen
Riedmiller
Rusu
Sadik
Shane
Stig
Veness
Volodymyr
Wierstra
Lillicrap
Pritzel
Heess
Erez
Yuval
Tassa
Schulman
Filip
Wolski
Prafulla
Dhariwal
Radford
Oleg
Klimov
Kaichao
Jiayi
Weng
Duburcq
Huayu
Strens
Ornstein
Uhlenbeck
mse
gail
airl
ppo
Jupyter
Colab
Colaboratory
IPendulum
Reacher
Runtime
Nvidia
bump to v0.4.3 (#432) * add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check 2021-09-03 05:05:04 +08:00			`tianshou`
			`arXiv`
			`tanh`
			`lr`
			`logits`
			`env`
			`envs`
			`optim`
			`eps`
			`timelimit`
			`TimeLimit`
update dqn tutorial and add envpool to docs (#526) Co-authored-by: Jiayi Weng <trinkle23897@gmail.com> 2022-02-15 06:39:47 +08:00			`envpool`
			`EnvPool`
bump to v0.4.3 (#432) * add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check 2021-09-03 05:05:04 +08:00			`maxsize`
			`timestep`
update dqn tutorial and add envpool to docs (#526) Co-authored-by: Jiayi Weng <trinkle23897@gmail.com> 2022-02-15 06:39:47 +08:00			`timesteps`
bump to v0.4.3 (#432) * add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check 2021-09-03 05:05:04 +08:00			`numpy`
			`ndarray`
			`stackoverflow`
W&B: Add usage in the docs (#463) 2021-10-13 20:58:25 +05:30			`tensorboard`
Add learning rate scheduler to BasePolicy (#598) 2022-04-17 08:52:30 -07:00			`state_dict`
bump to v0.4.3 (#432) * add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check 2021-09-03 05:05:04 +08:00			`len`
			`tac`
			`fqf`
			`iqn`
			`qrdqn`
			`rl`
Add Trainers as generators (#559) The new proposed feature is to have trainers as generators. The usage pattern is: ```python trainer = OnPolicyTrainer(...) for epoch, epoch_stat, info in trainer: print(f"Epoch: {epoch}") print(epoch_stat) print(info) do_something_with_policy() query_something_about_policy() make_a_plot_with(epoch_stat) display(info) ``` - epoch int: the epoch number - epoch_stat dict: a large collection of metrics of the current epoch, including stat - info dict: the usual dict out of the non-generator version of the trainer You can even iterate on several different trainers at the same time: ```python trainer1 = OnPolicyTrainer(...) trainer2 = OnPolicyTrainer(...) for result1, result2, ... in zip(trainer1, trainer2, ...): compare_results(result1, result2, ...) ``` Co-authored-by: Jiayi Weng <trinkle23897@gmail.com> 2022-03-17 17:26:14 +01:00			`offpolicy`
			`onpolicy`
bump to v0.4.3 (#432) * add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check 2021-09-03 05:05:04 +08:00			`quantile`
			`quantiles`
			`dqn`
			`param`
			`async`
			`subprocess`
Add Trainers as generators (#559) The new proposed feature is to have trainers as generators. The usage pattern is: ```python trainer = OnPolicyTrainer(...) for epoch, epoch_stat, info in trainer: print(f"Epoch: {epoch}") print(epoch_stat) print(info) do_something_with_policy() query_something_about_policy() make_a_plot_with(epoch_stat) display(info) ``` - epoch int: the epoch number - epoch_stat dict: a large collection of metrics of the current epoch, including stat - info dict: the usual dict out of the non-generator version of the trainer You can even iterate on several different trainers at the same time: ```python trainer1 = OnPolicyTrainer(...) trainer2 = OnPolicyTrainer(...) for result1, result2, ... in zip(trainer1, trainer2, ...): compare_results(result1, result2, ...) ``` Co-authored-by: Jiayi Weng <trinkle23897@gmail.com> 2022-03-17 17:26:14 +01:00			`deque`
bump to v0.4.3 (#432) * add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check 2021-09-03 05:05:04 +08:00			`nn`
			`equ`
			`cql`
			`fn`
			`boolean`
			`pre`
			`np`
add multi-GPU support (#461) add a new class DataParallelNet 2021-10-05 13:39:14 -04:00			`cuda`
bump to v0.4.3 (#432) * add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check 2021-09-03 05:05:04 +08:00			`rnn`
			`rew`
			`pre`
			`perceptron`
			`bsz`
			`dataset`
			`mujoco`
			`jit`
			`nstep`
			`preprocess`
			`repo`
			`ReLU`
			`namespace`
Enable venvs.reset() concurrent execution (#517) - change the internal API name of worker: send_action -> send, get_result -> recv (align with envpool) - add a timing test for venvs.reset() to make sure the concurrent execution - change venvs.reset() logic Co-authored-by: Jiayi Weng <trinkle23897@gmail.com> 2022-02-08 00:40:01 +08:00			`recv`
bump to v0.4.3 (#432) * add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check 2021-09-03 05:05:04 +08:00			`th`
			`utils`
			`NaN`
			`linesearch`
			`hyperparameters`
			`pseudocode`
			`entropies`
			`nn`
			`config`
			`cpu`
			`rms`
			`debias`
			`indice`
			`regularizer`
			`miniblock`
			`modularize`
			`serializable`
			`softmax`
			`vectorized`
			`optimizers`
			`undiscounted`
			`submodule`
			`subclasses`
			`submodules`
			`tfevent`
			`dirichlet`
			`docstring`
			`webpage`
			`formatter`
			`num`
			`py`
			`pythonic`
			`中文文档位于`
			`conda`
			`miniconda`
			`Amir`
			`Andreas`
			`Antonoglou`
			`Beattie`
			`Bellemare`
			`Charles`
			`Daan`
			`Demis`
			`Dharshan`
			`Fidjeland`
			`Georg`
			`Hassabis`
			`Helen`
			`Ioannis`
			`Kavukcuoglu`
			`King`
			`Koray`
			`Kumaran`
			`Legg`
			`Mnih`
			`Ostrovski`
			`Petersen`
			`Riedmiller`
			`Rusu`
			`Sadik`
			`Shane`
			`Stig`
			`Veness`
			`Volodymyr`
			`Wierstra`
			`Lillicrap`
			`Pritzel`
			`Heess`
			`Erez`
			`Yuval`
			`Tassa`
			`Schulman`
			`Filip`
			`Wolski`
			`Prafulla`
			`Dhariwal`
			`Radford`
			`Oleg`
			`Klimov`
			`Kaichao`
			`Jiayi`
			`Weng`
			`Duburcq`
			`Huayu`
			`Strens`
			`Ornstein`
			`Uhlenbeck`
Add Intrinsic Curiosity Module (#503) 2022-01-14 10:43:48 -08:00			`mse`
Implement Generative Adversarial Imitation Learning (GAIL) (#550) Implement GAIL based on PPO and provide example script and sample (i.e., most likely not the best) results with Mujoco tasks. (#531, #173) 2022-03-06 07:57:15 -08:00			`gail`
			`airl`
			`ppo`
Add jupyter notebook tutorials using Google Colaboratory (#599) 2022-04-19 20:58:52 +08:00			`Jupyter`
			`Colab`
			`Colaboratory`
Update Mujoco Bemchmark's webpage (#606) 2022-04-24 01:11:33 +08:00			`IPendulum`
			`Reacher`
			`Runtime`
			`Nvidia`