if __name__ == '__main__':
results_dir = str(sys.argv[1])
# results_dir = "Results_maze_baselines"
if not os.path.exists(results_dir):
os.makedirs(results_dir)
just_testing = False
epochs_cnn = 1 # 000
epochs_nav = 10
batch_size = 150
lib = FnLibrary()
lib.addItems(
get_items_from_repo(
['flatten_2d_list', 'map_g', 'compose', 'repeat', 'conv_g']))
interpreter = Interpreter(lib, epochs=1, batch_size=batch_size)
# interpreter.epochs = epochs_cnn
# res1 = _train_s2t1(results_dir)
# print("res1: {}".format(res1["accuracy"]))
interpreter.epochs = epochs_nav
res2 = _train_s2t2(results_dir, "s2t1_cnn", "s2t1_mlp")
print("res2: {}".format(res2["accuracy"]))
interpreter.epochs = epochs_nav
res3 = _train_s2t3(results_dir, "s2t2_cnn", "s2t2_mlp", "s2t2_conv_g")
print("res3: {}".format(res3["accuracy"]))
result["new_fns_dict"][name_mlp].save(results_directory)
result["new_fns_dict"][name_conv_g].save(results_directory)
return result
if __name__ == '__main__':
results_dir = str(sys.argv[1])
# results_dir = "Results_maze_baselines"
if not os.path.exists(results_dir):
os.makedirs(results_dir)
just_testing = False
epochs_cnn = 1000
epochs_nav = 10
batch_size = 150
lib = FnLibrary()
lib.addItems(
get_items_from_repo(
['flatten_2d_list', 'map_g', 'compose', 'repeat', 'conv_g']))
interpreter = Interpreter(lib, epochs=1, batch_size=batch_size)
interpreter.epochs = epochs_cnn
#res1 = _train_s1t1(results_dir)
#print("res1: {}".format(res1["accuracy"]))
interpreter.epochs = epochs_nav
res2 = _train_s1t2(results_dir, "s1t1_cnn", "s1t1_mlp")
print("res2: {}".format(res2["accuracy"]))