def classifier(nn_params, log, exp, train_path, val_path, test_path,
save_logs):
# create model and train it
model = Network.CNN(nn_params)
if nn_params["load_model"] is not None:
with open(nn_params["load_model"], 'rb') as pickle_file:
model2 = pickle.load(pickle_file)
model.init_weights(model2)
model, mean, std = train_model(model, nn_params, log, exp, train_path,
val_path, save_logs)
# test model
X_test, Y_test = read_data(test_path, nn_params, "test")
# apply z score scaling
if nn_params["z_scale"]:
X_test, _, __ = z_scaling(X_test.copy(), mean, std)
test_model(model, nn_params, exp, X_test, Y_test, save_logs, "test")
