FLAGS <- tensorflow::flags(
# Training
flag_integer("epochs", 20),
flag_integer("steps_per_epoch", 250),
flag_integer("batch_size", 32),
flag_integer("val_size", 100),
flag_integer("patience", 40),
flag_integer("valid_freq", 3),
# Optimizer
flag_string("optimizer", "adam"), # TODO: use optimizer$get(FLAGS$optimizer) to set params
flag_numeric("init_lr", 0.001),
flag_numeric("max_lr", 3),
flag_numeric("momentum", 0),
flag_numeric("decay", 0),
flag_boolean("nesterov", FALSE),
# Model
flag_boolean("global_pool", TRUE),
flag_boolean("batchnorm", FALSE),
flag_integer("clipvalue", 0),
flag_integer("clipnorm", 0),
# Misc
flag_boolean("profile", FALSE)
)
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