def main():
#todo this funciton and taining should become part of the library!!
# sodass man nur mehr savepath und dataset angeben muss!
msg.info("Traing a network for butadien", 2)
msg.info("Fetching dataset ... ", 2)
dataset = prep_dataset()
save_path = "butadien/data/networks/networkS400.npy"
user_input = msg.input(
"This will overwrite the model at " + save_path + \
"Are you sure you want that? (y for yes)"
)
if user_input.upper() != "Y":
msg.info("Aborting", 2)
return
msg.info("Try to fetch current model")
try:
model = np.load(save_path, encoding="latin1")
structure, weights, biases = model[0], model[1], model[2]
network = EluFixedValue(structure, weights, biases)
test_error = model[3]
user_input = msg.input(
"Model found with test error : " + str(test_error) + \
". Do you want to continue to train it? (y for yes)"
)
if user_input.upper() != "Y":
msg.info("Creating new network", 2)
model = None
except:
model = None
if model is None:
dim_triu = int(DIM * (DIM + 1) / 2)
structure = [
dim_triu,
int(dim_triu * 0.75),
int(dim_triu * 0.5), dim_triu, dim_triu
]
test_error = 1e10
msg.info("Train ... ", 2)
network = EluTrNNN(structure)
train_network(dataset, network, save_path, test_error)
msg.info("All done. Bye bye..", 2)
def main():
msg.info("Traing a network for butadien", 2)
msg.info("Fetching dataset ... ", 2)
dataset = prep_dataset()
msg.info("Train ... ", 2)
trainer, network, sess = train_network(dataset)
user_input = msg.input("Keep this network for butadien " + " (y for yes)?")
if user_input.upper() == "Y":
save_path = join("butadien/data", "network.npy")
network.export(sess, save_path)
msg.info("Exported network to: " + save_path, 2)
else:
msg.info("Network discarded ...", 2)
msg.info("All done. Bye bye..", 2)
def main(molecule_type):
msg.info("Traing a network for " + molecule_type, 2)
msg.info("Fetching dataset ... ", 2)
dataset = prep_dataset(molecule_type)
msg.info("Train ... ", 2)
trainer, network, sess = train_network(molecule_type, dataset)
user_input = msg.input("Keep this network for " + molecule_type +
" (y for yes)?")
if user_input.upper() == "Y":
save_path = \
join("cc2ai", molecule_type, "network_" + molecule_type + ".npy")
network.export(sess, save_path)
msg.info("Exported network to: " + save_path, 2)
else:
msg.info("Network discarded ...", 2)
msg.info("All done. Bye bye..", 2)