def run_cnn(
arch_params,
optimization_params,
dataset,
filename_params,
visual_params,
n_epochs=200,
validate_after_epochs=1,
verbose=False,
):
net = network(filename_params=filename_params,
random_seed=arch_params["random_seed"],
verbose=verbose)
net.init_data(dataset, outs=arch_params["outs"], verbose=verbose)
net.build_network(arch_params=arch_params,
optimization_params=optimization_params,
verbose=verbose)
net.create_dirs(visual_params=visual_params)
net.train(n_epochs=n_epochs,
validate_after_epochs=validate_after_epochs,
verbose=verbose)
net.test(verbose=verbose)
net.save_network()
"""
def run_cnn(
arch_params,
optimization_params ,
dataset,
filename_params,
visual_params,
n_epochs = 200,
validate_after_epochs = 1,
verbose = False,
):
net = network( filename_params = filename_params,
random_seed = arch_params ["random_seed"],
verbose = verbose )
net.init_data ( dataset, outs = arch_params["outs"], verbose = verbose )
net.build_network( arch_params = arch_params,
optimization_params = optimization_params,
verbose = verbose)
net.create_dirs ( visual_params = visual_params )
net.train( n_epochs = n_epochs,
validate_after_epochs = validate_after_epochs,
verbose = verbose )
net.test( verbose = verbose )
net.save_network ()
"""
def generality_experiment(
arch_params,
optimization_params ,
dataset,
original_filename_params,
filename_params_retrain,
retrain_params,
visual_params,
validate_after_epochs = 1,
n_epochs = 50,
ft_epochs = 200,
verbose = False
):
params_loaded, arch_params_loaded = load_network (filename_params ["network_save_name"] ,
data_params = False,
optimization_params = False)
# retrain is used to do the dataset some wierd experiments.
retrain_net = network(
filename_params = filename_params_retrain,
random_seed = arch_params ["random_seed"],
verbose = verbose )
retrain_net.init_data ( dataset = dataset , outs = arch_params ["outs"], verbose = verbose )
retrain_net.build_network (
arch_params = arch_params_loaded,
optimization_params = optimization_params,
init_params = params_loaded,
retrain_params = retrain_params,
verbose = verbose )
retrain_net.create_dirs ( visual_params = visual_params )
retrain_net.train ( n_epochs = n_epochs,
ft_epochs = ft_epochs,
validate_after_epochs = validate_after_epochs,
verbose = verbose)
retrain_net.test ( verbose = verbose )
retrain_net.save_network ()
