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normal.py
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normal.py
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class EvaluateConfig:
def __init__(self):
self.game_num = 200 # 400
self.replace_rate = 0.55
self.play_config = PlayConfig()
self.play_config.simulation_num_per_move = 100
self.play_config.thinking_loop = 5
self.play_config.c_puct = 1
self.play_config.change_tau_turn = 0
self.play_config.noise_eps = 0
self.evaluate_latest_first = True
class PlayDataConfig:
def __init__(self):
self.nb_game_in_file = 100
self.max_file_num = 200 # 5000
class PlayConfig:
def __init__(self):
self.simulation_num_per_move = 100
self.thinking_loop = 5
self.logging_thinking = False
self.c_puct = 2
self.noise_eps = 0.25
self.dirichlet_alpha = 0.03
self.change_tau_turn = 10
self.virtual_loss = 3
self.prediction_queue_size = 16
self.parallel_search_num = 16
self.prediction_worker_sleep_sec = 0.0001
self.wait_for_expanding_sleep_sec = 0.00001
class TrainerConfig:
def __init__(self):
self.batch_size = 512 # 2048
self.epoch_to_checkpoint = 1
self.start_total_steps = 0
self.save_model_steps = 2000
class ModelConfig:
cnn_filter_num = 256
cnn_filter_size = 3
res_layer_num = 10
l2_reg = 1e-4
value_fc_size = 256