from runner.run_description import RunDescription, Experiment, ParamGrid
_params = ParamGrid([
('seed', [0000, 1111, 2222, 3333, 4444, 5555, 6666, 7777]),
])
_experiment = Experiment(
'quads_single_benchmark',
'python -m run_algorithm --env=quadrotor_single --train_for_env_steps=1000000000 --algo=APPO --gamma=0.99 --use_rnn=False --num_workers=36 --num_envs_per_worker=2 --num_policies=1 --rollout=128 --recurrence=1 --benchmark=False --with_pbt=False --actor_critic_share_weights=False --policy_initialization=xavier_uniform --adaptive_stddev=False --with_vtrace=False --max_policy_lag=100000000 --gae_lambda=1.00 --max_grad_norm=0.0 --ppo_clip_value=5.0 --batch_size=512 --ppo_epochs=1 --nonlinearity=tanh --learning_rate=0.0001 --exploration_loss_coeff=0.0 --initial_stddev=1.0 --hidden_size=64 --adam_eps=1e-8',
_params.generate_params(randomize=False),
)
RUN_DESCRIPTION = RunDescription('quads_single_benchmark',
experiments=[_experiment])
# Command to use this script on server:
# xvfb-run python -m runner.run --run=quad_single_benchmark --runner=processes --max_parallel=8 --pause_between=1 --experiments_per_gpu=2 --num_gpus=4
# Command to use this script on local machine:
# Please change num_workers to the physical cores of your local machine
# python -m runner.run --run=quad_single_benchmark --runner=processes --max_parallel=8 --pause_between=1 --experiments_per_gpu=2 --num_gpus=4
# On Brain server, when you use num_workers = 72, if the system reports: Resource temporarily unavailable,
# then, try to two commands below
# export OMP_NUM_THREADS=1
# export USE_SIMPLE_THREADED_LEVEL3=1
# By using sample-factory: v102, training for 220 M framesteps, average the avg_true_reward of 8 seeds,
# Mean: -229. Standard deviation: 10
# By using sample-factory: v102, training for 280 M framesteps, average the avg_true_reward of 8 seeds,
# Mean: -222. Standard deviation: 10
# By using sample-factory: v102, training for 400 M framesteps, average the avg_true_reward of 8 seeds,
from runner.run_description import RunDescription, Experiment, ParamGrid
_params = ParamGrid([
('env', [
'MiniGrid-MemoryS7-v0', 'MiniGrid-RedBlueDoors-8x8-v0',
'MiniGrid-MemoryS17Random-v0'
]),
('use_rnn', [True, False]),
('mem_size', [4, 0]),
])
_experiment = Experiment(
'mem_minigrid',
'python -m train_pytorch --algo=PPO --train_for_env_steps=300000000',
_params.generate_params(randomize=False),
)
RUN_DESCRIPTION = RunDescription('mem_minigrid_v39',
experiments=[_experiment],
pause_between_experiments=5,
use_gpus=2,
experiments_per_gpu=4,
max_parallel=8)
