- Support MLflow tracking (
border-mlflow-tracking
) (#2). - Add candle agent (
border-candle-agent
) (#1). - Add
Trainer::train_offline()
method for offline training (border-core
) (#18). - Add crate
border-policy-no-backend
.
- Take
self
in the signature ofpush()
method of replay buffer (border-core
). - Fix a bug in
MlpConfig
(border-tch-agent
). - Bump the version of tch to 0.16.0 (
border-tch-agent
). - Change the name of trait
StepProcessorBase
toStepProcessor
(border-core
). - Change the environment API to include terminate/truncate flags (
border-core
) (#10). - Split policy trait into two traits, one for sampling (
Policy
) and the other for configuration (Configurable
) (#12).
- Docker files (
border
). - Singularity files (
border
). - Script for GPUSOROBAN (#67).
Evaluator
trait inborder-core
(#70). It can be used to customize evaluation logic inTrainer
.- Example of asynchronous trainer for native Atari environment and DQN (
border/examples
). - Move tensorboard recorder into a separate crate (
border-tensorboard
).
- Bump the version of tch-rs to 0.8.0 (
border-tch-agent
). - Rename agents as following the convention in Rust (
border-tch-agent
). - Bump the version of gym to 0.26 (
border-py-gym-env
). - Remove the type parameter for array shape of gym environments (
border-py-gym-env
). - Interface of Python-Gym interface (
border-py-gym-env
).