def main():
from att_model_proxy import cmd_args
seed = cmd_args.seed
np.random.seed(seed)
from att_model_proxy import AttMolProxy as ProxyModel
from att_model_proxy import cmd_args
model = ProxyModel()
cal_valid_prior(model, cmd_args.latent_dim)
def main():
seed = 10960817
np.random.seed(seed)
from att_model_proxy import AttMolProxy as ProxyModel
from att_model_proxy import cmd_args
model = ProxyModel()
priors_file = cmd_args.save_dir + '/decoded_priors.txt'
valid_prior = cal_valid_prior(model, cmd_args.latent_dim)
save_decoded_priors(valid_prior, priors_file)
def main():
seed = 10960817
np.random.seed(seed)
from att_model_proxy import AttMolProxy as ProxyModel
from att_model_proxy import cmd_args
model = ProxyModel()
generation_file = cmd_args.save_dir + '/decoded_generation.txt'
result = cal_valid_prior(model, cmd_args.latent_dim)
save_decoded_priors(result, generation_file)
def main():
seed = 10960817
np.random.seed(seed)
from att_model_proxy import AttMolProxy as ProxyModel
from att_model_proxy import cmd_args
model = ProxyModel()
valid_prior = cal_valid_prior(model, cmd_args.latent_dim)
valid_prior_save_file = cmd_args.saved_model + '-valid_prior.txt'
print('valid prior:', valid_prior)
with open(valid_prior_save_file, 'w') as fout:
print('valid prior:', valid_prior, file=fout)
def main():
from att_model_proxy import AttMolProxy as ProxyModel
from att_model_proxy import cmd_args
# takes the model and calculate the decode results
model = ProxyModel()
# update where to save
decoded_file = cmd_args.save_dir + '/decoded_results.txt'
# reading smiles test set
if cmd_args.smiles_file == 'qm9':
smiles_list = readStr_qm9()
elif cmd_args.smiles_file == 'zinc':
smiles_list = read_zinc()
XTE = smiles_list[0:nb_smiles]
decoded_result = reconstruct(model, XTE)
decoded_result = np.array(decoded_result)
save_decoded_results(XTE, decoded_result, decoded_file)
def main():
from att_model_proxy import AttMolProxy as ProxyModel
from att_model_proxy import cmd_args
decode_result_save_file = cmd_args.saved_model + '-reconstruct_zinc_decode_result.csv'
accuracy_save_file = cmd_args.saved_model + '-reconstruct_zinc_accuracy.txt'
model = ProxyModel()
decode_result = reconstruct(model, smiles)
accuracy, junk = cal_accuracy(decode_result)
print('accuracy:', accuracy, 'junk:', junk)
save_result = True
if save_result:
with open(accuracy_save_file, 'w') as fout:
print('accuracy:', accuracy, 'junk:', junk, file=fout)
save_decode_result(decode_result, decode_result_save_file)