class TorchLearner(BaseAgent):
def __init__(self, name, team, index):
sys.path.append(path)
from output_formatter import OutputFormatter
from input_formatter import InputFormatter
import torch
BaseAgent.__init__(self, name, team, index)
self.actor_model = None
self.single_model = None
self.torch = torch
self.output_formatter = OutputFormatter()
self.input_formatter = InputFormatter(self.index, self.index,
self.team)
def initialize_agent(self):
from torch_model import SingleAction, SymmetricModel
self.actor_model = SymmetricModel()
self.actor_model.load_state_dict(
self.torch.load('levi/cool_atba.actor'))
self.single_model = SingleAction(self.actor_model)
def get_output(self, game_tick_packet):
spatial, car_stats = self.input_formatter.get_input(game_tick_packet)
with self.torch.no_grad():
action = self.single_model.get_action(spatial, car_stats)
in_the_air = game_tick_packet.game_cars[self.index].jumped
player_input = self.output_formatter.get_output(action, in_the_air)
return player_input
class TorchLearner(BaseAgent):
def __init__(self, name, team, index):
sys.path.append(path)
from output_formatter import OutputFormatter
from input_formatter import InputFormatter
from cool_atba import Atba
import torch
BaseAgent.__init__(self, name, team, index)
self.atba = Atba()
self.torch = torch
self.output_formatter = OutputFormatter()
self.input_formatter = InputFormatter(self.index, self.index,
self.team)
def get_output(self, game_tick_packet):
spatial, car_stats = self.input_formatter.get_input(game_tick_packet)
atba_action = self.atba.get_action(spatial, car_stats)
in_the_air = game_tick_packet.game_cars[self.index].jumped
player_input = self.output_formatter.get_output(
atba_action, in_the_air)
return player_input