def config():
conf = confs.TrainNNConfig("reversi")
conf.generation_prefix = "x4"
conf.overwrite_existing = True
conf.next_step = 20
conf.validation_split = 1.0
conf.starting_step = 10
return conf
def breakthrough(self, gen_prefix):
conf = confs.TrainNNConfig("breakthrough")
conf.generation_prefix = gen_prefix
conf.use_previous = False
conf.next_step = 92
conf.validation_split = 0.9
conf.batch_size = 512
conf.epochs = 6
conf.starting_step = 20
return conf
def train_config_template(game, gen_prefix):
conf = confs.TrainNNConfig("speedChess")
conf.generation_prefix = gen_prefix
conf.use_previous = True
conf.next_step = 0
conf.validation_split = 0.9
conf.batch_size = 128
conf.epochs = 20
conf.starting_step = 0
conf.overwrite_existing = False
return conf
def get_conf():
conf = confs.TrainNNConfig(game="cittaceot",
generation_prefix="v8",
use_previous=False,
next_step=3,
overwrite_existing=False,
validation_split=0.9,
batch_size=32,
max_sample_count=1000000,
max_epoch_samples_count=100000,
starting_step=0,
compile_strategy="adam",
learning_rate=None)
return conf
def c4(self, gen_prefix):
conf = confs.TrainNNConfig("connectFour")
conf.generation_prefix = gen_prefix
conf.use_previous = False
conf.next_step = 33
conf.validation_split = 0.9
conf.batch_size = 4096
conf.epochs = 1
conf.starting_step = 25
conf.overwrite_existing = True
return conf
def get_conf_reversi():
conf = confs.TrainNNConfig(game="reversi",
generation_prefix="v7",
use_previous=False,
next_step=15,
overwrite_existing=True,
validation_split=0.9,
batch_size=256,
epochs=3,
max_sample_count=200000,
max_epoch_samples_count=100000,
starting_step=10,
compile_strategy="adam",
learning_rate=None)
return conf
def speedChess(self, gen_prefix):
conf = confs.TrainNNConfig("speedChess")
conf.generation_prefix = gen_prefix
conf.use_previous = False
conf.next_step = 12
conf.validation_split = 0.9
conf.batch_size = 128
conf.epochs = 20
conf.max_sample_count = 300000
conf.starting_step = 3
conf.overwrite_existing = True
return conf
def reversi(self, gen_prefix):
conf = confs.TrainNNConfig("reversi")
conf.generation_prefix = gen_prefix
conf.batch_size = 512
conf.compile_strategy = "adam"
conf.epochs = 6
conf.learning_rate = None
conf.next_step = 20
conf.overwrite_existing = False
conf.starting_step = 5
conf.use_previous = False
conf.validation_split = 0.90000
conf.resample_buckets = [[10, 1.0], [0, 0.5]]
return conf
def get_train_config(game, gen_prefix, next_step, starting_step):
config = confs.TrainNNConfig(game)
config.next_step = next_step
config.starting_step = starting_step
config.generation_prefix = gen_prefix
config.batch_size = 512
config.compile_strategy = "adam"
config.epochs = 8
config.learning_rate = 0.0005
config.overwrite_existing = False
config.use_previous = True
config.validation_split = 0.90000
config.resample_buckets = [[100, 1.0], [-1, 0.8]]
config.max_epoch_size = 1048576
return config
def train_config_template(game, gen_prefix):
conf = confs.TrainNNConfig(game)
conf.generation_prefix = gen_prefix
conf.next_step = 0
conf.starting_step = 0
conf.use_previous = True
conf.validation_split = 0.95
conf.overwrite_existing = False
conf.epochs = 1
conf.batch_size = 256
conf.compile_strategy = "SGD"
conf.l2_regularisation = 0.00002
conf.learning_rate = 0.01
conf.initial_value_weight = 1.0
conf.max_epoch_size = 1024 * 1024
conf.resample_buckets = [[100, 1.00000]]
return conf
