import os

from config import get_config, show_config, save_config, load_config

from data import Generator

from base import BasicScenario

from solver import REGISTRY

def run(config):

print(f"\n{'-' * 20} Complete {'-' * 20}\n")

if __name__ == '__main__':

# Please refer to `base.loader` to obtain all available solvers

# 1. Get Config

# The key settings are controlled with config.py

# while other advanced settings are listed in settings/*.yaml

config = get_config()

# You can modify some settings directly here.

# An example:

# config.solver_name = 'a3c_gcn_seq2seq' # modify the algorithm of the solver

# config.shortest_method = 'mcf' # modify the shortest path algorithm to Multi-commodity Flow

# config.num_train_epochs = 100 # modify the number of trainning epochs

# 2. Generate Dataset

# Although we do not generate a static dataset,

# the environment will automatically produce a random dataset.

p_net, v_net_simulator = Generator.generate_dataset(

config,

p_net=False,

v_nets=False,

save=False) # Here, no dataset will be generated and saved.

# 3. Start to Run

# A scenario with an environment and a solver will be create following provided config.

# The interaction between the environment and the solver will happen in this scenario.

run(config)