import numpy as np
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from HYPERS import *
from PokerRL.game.games import StandardLeduc # or any other game
if __name__ == '__main__':
ctrl = Driver(t_prof=TrainingProfile(
name="Leduc_DREAM_BaselineT100_v001_SEED" +
str(np.random.randint(1000000)),
nn_type="feedforward",
n_batches_adv_training=SDCFR_LEDUC_BATCHES,
periodic_restart=SDCFR_LEDUC_PERIOD,
n_traversals_per_iter=SDCFR_LEDUC_TRAVERSALS_OS,
sampler="learned_baseline",
n_batches_per_iter_baseline=100,
os_eps=OS_EPS,
game_cls=StandardLeduc,
DISTRIBUTED=False,
),
eval_methods={
"br": 3,
})
ctrl.run()
import numpy as np
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from HYPERS import *
from PokerRL.game.games import Flop3Holdem # or any other game
if __name__ == '__main__':
ctrl = Driver(
t_prof=TrainingProfile(
name="FHP_OSSDCFR_v001_SEED" + str(np.random.randint(1000000)),
n_traversals_per_iter=(SDCFR_FHP_TRAVERSALS_OS / N_LA_FHP_CFR),
sampler="eq_baseline",
DREAM_and_DeepCFR=
True, # turns baseline off. Hacky but allows code sharing
os_eps=OS_EPS,
game_cls=Flop3Holdem,
n_batches_adv_training=SDCFR_FHP_BATCHES,
n_learner_actor_workers=N_LA_FHP_CFR,
mini_batch_size_adv=int(SDCFR_FHP_BATCH_SIZE / N_LA_FHP_CFR),
max_buffer_size_adv=int(4e7 / N_LA_FHP_NFSP),
DISTRIBUTED=True,
rlbr_args=DIST_RLBR_ARGS_games,
),
eval_methods={"rlbr": RL_BR_FREQ_CFR})
ctrl.run()
import numpy as np
from DREAM_and_DeepCFR.EvalAgentDeepCFR import EvalAgentDeepCFR
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from HYPERS import *
from PokerRL.game.games import StandardLeduc # or any other game
if __name__ == '__main__':
ctrl = Driver(t_prof=TrainingProfile(
name="Leduc_DREAM_v001_SEED" + str(np.random.randint(1000000)),
nn_type="feedforward",
n_batches_adv_training=SDCFR_LEDUC_BATCHES,
n_traversals_per_iter=SDCFR_LEDUC_TRAVERSALS_OS,
sampler="learned_baseline",
n_batches_per_iter_baseline=SDCFR_LEDUC_BASELINE_BATCHES,
os_eps=OS_EPS,
game_cls=StandardLeduc,
eval_modes_of_algo=(EvalAgentDeepCFR.EVAL_MODE_SINGLE,
EvalAgentDeepCFR.EVAL_MODE_AVRG_NET),
n_batches_avrg_training=4000,
DISTRIBUTED=False,
),
eval_methods={
"br": 20,
})
ctrl.run()
import numpy as np
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from PokerRL.game.games import StandardLeduc # or any other game
if __name__ == '__main__':
ctrl = Driver(t_prof=TrainingProfile(
name="SD-CFR_LEDUC_LB_2700trav_095_SEED" +
str(np.random.randint(1000000)),
n_traversals_per_iter=2700,
n_batches_adv_training=3000,
sampler="learned_baseline",
os_eps=0.5,
game_cls=StandardLeduc,
),
eval_methods={
"br": 3,
})
ctrl.run()
import numpy as np
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from HYPERS import *
from PokerRL.game.games import Flop3Holdem # or any other game
if __name__ == '__main__':
ctrl = Driver(t_prof=TrainingProfile(
name="FHP_ESSDCFR_v001_SEED" + str(np.random.randint(1000000)),
n_traversals_per_iter=(SDCFR_FHP_TRAVERSALS_ES / N_LA_FHP_CFR),
sampler="es",
game_cls=Flop3Holdem,
n_batches_adv_training=SDCFR_FHP_BATCHES,
n_learner_actor_workers=N_LA_FHP_CFR,
mini_batch_size_adv=int(SDCFR_FHP_BATCH_SIZE / N_LA_FHP_CFR),
max_buffer_size_adv=int(4e7 / N_LA_FHP_CFR),
DISTRIBUTED=True,
rlbr_args=DIST_RLBR_ARGS_games,
),
eval_methods={"rlbr": RL_BR_FREQ_CFR})
ctrl.run()
import numpy as np
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from HYPERS import *
from PokerRL.game.games import StandardLeduc # or any other game
if __name__ == '__main__':
ctrl = Driver(t_prof=TrainingProfile(
name="Leduc_ESSDCFR1500_v001_SEED" + str(np.random.randint(1000000)),
n_batches_adv_training=SDCFR_LEDUC_BATCHES,
n_traversals_per_iter=1500,
sampler="es",
game_cls=StandardLeduc,
DISTRIBUTED=False,
),
eval_methods={
"br": 20,
})
ctrl.run()
import numpy as np
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from HYPERS import *
from PokerRL.game.games import StandardLeduc # or any other game
if __name__ == '__main__':
ctrl = Driver(t_prof=TrainingProfile(
name="Leduc_OSSDCFR_v001_SEED" + str(np.random.randint(1000000)),
n_batches_adv_training=SDCFR_LEDUC_BATCHES,
n_traversals_per_iter=SDCFR_LEDUC_TRAVERSALS_OS,
sampler="mo",
n_actions_traverser_samples=1,
os_eps=OS_EPS,
game_cls=StandardLeduc,
DISTRIBUTED=False,
),
eval_methods={
"br": 20,
})
ctrl.run()
import numpy as np
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from PokerRL.game.games import StandardLeduc # or any other game
if __name__ == '__main__':
ctrl = Driver(t_prof=TrainingProfile(
name="SD-Leduc_DREAM_ResetNever_v001_SEED" + str(np.random.randint(1000000)),
n_traversals_per_iter=900,
n_batches_adv_training=3000,
periodic_restart=100000000,
sampler="learned_baseline",
os_eps=0.5,
game_cls=StandardLeduc,
),
eval_methods={
"br": 3,
})
ctrl.run()
import numpy as np
from DREAM_and_DeepCFR.EvalAgentDeepCFR import EvalAgentDeepCFR
from DREAM_and_DeepCFR.TrainingProfile import TrainingProfile
from DREAM_and_DeepCFR.workers.driver.Driver import Driver
from HYPERS import *
from PokerRL.game.games import StandardLeduc # or any other game
if __name__ == '__main__':
ctrl = Driver(t_prof=TrainingProfile(
name="Leduc_ESSDCFR_v001_SEED" + str(np.random.randint(1000000)),
n_batches_adv_training=SDCFR_LEDUC_BATCHES,
n_traversals_per_iter=SDCFR_LEDUC_TRAVERSALS_ES,
sampler="es",
eval_modes_of_algo=(EvalAgentDeepCFR.EVAL_MODE_SINGLE, ),
n_batches_avrg_training=4000,
game_cls=StandardLeduc,
DISTRIBUTED=False,
),
eval_methods={
"br": 20,
})
ctrl.run()