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