def get_env_config(): """get rins env config.""" config = ConfigDict() # required fields. config.class_path = "liaison.env.rins" # should be rel to the parent directory. config.class_name = "Env" # makes observations suitable for the MLP model. config.make_obs_for_mlp = True # adds all the constraints to MLP state space. # adds #variables * #constraints dimensions to the state space. config.mlp_embed_constraints = False config.make_obs_for_self_attention = False """if graph_seed < 0, then use the environment seed""" config.graph_seed = 42 config.dataset = 'milp-facilities-10' config.dataset_type = 'train' config.graph_start_idx = args.graph_start_idx config.n_graphs = 1 config.k = args.k config.steps_per_episode = 2000 return config
def get_config(): config = ConfigDict() # required fields. config.class_path = "liaison.env.xor_env" # should be rel to the parent directory. config.class_name = "Env" # makes observations suitable for the MLP model. config.make_obs_for_mlp = False # makes observations for graphnet agent with node labels in node features and # shortest path embedded as edge features. config.make_obs_for_graphnet_semi_supervised = False """if graph_seed < 0, then use the environment seed""" config.graph_seed = 42 return config
def get_config(): config = ConfigDict() # required fields. config.class_path = "liaison.env.tsp" # should be rel to the parent directory. config.class_name = "Env" # makes observations suitable for the MLP model. config.make_obs_for_mlp = False """if graph_seed < 0, then use the environment seed""" config.graph_seed = 42 config.dataset = 'tsp-20' config.dataset_type = 'train' config.graph_idx = 0 return config