def main(_):
with open(FLAGS.hq_replay_set) as f:
replay_list = sorted(json.load(f))
race_vs_race = os.path.basename(FLAGS.hq_replay_set).split('.')[0]
global_feature_vec_path = os.path.join(FLAGS.parsed_replay_path,
'GlobalFeatureVector', race_vs_race)
races = set(race_vs_race.split('_vs_'))
for race in races:
path = os.path.join(global_feature_vec_path, race)
if not os.path.isdir(path):
os.makedirs(path)
pbar = tqdm(total=len(replay_list), desc='#Replay')
for replay_path, replay_info_path in replay_list:
with open(replay_info_path) as f:
info = json.load(f)
info = Parse(info['info'], sc_pb.ResponseReplayInfo())
replay_name = os.path.basename(replay_path)
for player_info in info.player_info:
race = sc_pb.Race.Name(player_info.player_info.race_actual)
player_id = player_info.player_info.player_id
reward = player_info.player_result.result
replay_player_path = os.path.join(
race_vs_race, race, '{}@{}'.format(player_id, replay_name))
parse_replay(replay_player_path, reward, race,
race if len(races) == 1 else list(races - {race})[0])
pbar.update()
def sample_action(replay_path, action_path, sampled_path):
replay_info = os.path.join(FLAGS.infos_path, replay_path)
if not os.path.isfile(replay_info):
return
with open(replay_info) as f:
info = json.load(f)
result = []
proto = Parse(info['info'], sc_pb.ResponseReplayInfo())
for p in proto.player_info:
player_id = p.player_info.player_id
race = sc_common.Race.Name(p.player_info.race_actual)
action_file = os.path.join(action_path, race,
'{}@{}'.format(player_id, replay_path))
if not os.path.isfile(action_file):
return
result.append(sample_action_from_player(action_file))
assert len(result) == 2
sampled_actions = sorted(set(result[0]) | set(result[1]))
with open(os.path.join(sampled_path, replay_path), 'w') as f:
json.dump(sampled_actions, f)
def sample_frames(replay_path, action_path, sampled_frame_path):
replay_info = os.path.join(FLAGS.infos_path, replay_path)
if not os.path.isfile(replay_info):
return
with open(replay_info) as f:
info = json.load(f)
result = []
proto = Parse(info['info'], sc_pb.ResponseReplayInfo())
for p in proto.player_info: # Sample actions taken by each player
player_id = p.player_info.player_id
race = common_pb.Race.Name(p.player_info.race_actual)
action_file = os.path.join(action_path, race,
'{}@{}'.format(player_id, replay_path))
if not os.path.isfile(
action_file
): # Skip replays where actions haven't been extracted yet
print('Unable to locate', action_file)
return
result.append(sample_frames_from_player(action_file)
) # Get the frames where each player took a macro action
assert len(result) == 2
sampled_actions = sorted(
set(result[0]) | set(result[1])
) # Collect all frames where either player took a macro action
with open(os.path.join(sampled_frame_path, replay_path), 'w') as f:
json.dump(sampled_actions, f)
def main(_):
if not os.path.isdir(FLAGS.save_path):
os.makedirs(FLAGS.save_path)
replay_infos = glob.glob(os.path.join(FLAGS.infos_path, '*.SC2Replay'))
run_config = run_configs.get()
with run_config.start() as controller:
ping = controller.ping()
result = {}
pbar = tqdm(total=len(replay_infos), desc='#Replay')
for info_path in replay_infos:
with open(info_path) as f:
info = json.load(f)
proto = Parse(info['info'], sc_pb.ResponseReplayInfo())
if valid_replay(proto, ping):
players_info = proto.player_info
races = '_vs_'.join(sorted(sc_pb.Race.Name(player_info.player_info.race_actual)
for player_info in players_info))
if races not in result:
result[races] = []
result[races].append((info['path'], info_path))
pbar.update()
for k, v in result.items():
with open(os.path.join(FLAGS.save_path, k+'.json'), 'w') as f:
json.dump(v, f)
def main(argv):
with open(FLAGS.hq_replay_set) as f:
replay_list = sorted(json.load(f))
race_vs_race = os.path.basename(FLAGS.hq_replay_set).split('.')[0]
global_feature_path = os.path.join(FLAGS.parsed_replay_path, 'GlobalFeatures', race_vs_race)
for race in set(race_vs_race.split('_vs_')):
path = os.path.join(global_feature_path, race)
if not os.path.isdir(path):
os.makedirs(path)
pbar = tqdm(total=len(replay_list), desc='#Replay')
for replay_path, replay_info_path in replay_list: # Parse all replays
with open(replay_info_path) as f:
info = json.load(f)
info = Parse(info['info'], sc_pb.ResponseReplayInfo())
replay_name = os.path.basename(replay_path)
sampled_frame_path = os.path.join(FLAGS.parsed_replay_path, 'SampledFrames', race_vs_race, replay_name)
for player_info in info.player_info: # Parse replay from each players point of view
race = common_pb.Race.Name(player_info.player_info.race_actual)
player_id = player_info.player_info.player_id
reward = player_info.player_result.result
replay_player_path = os.path.join(race_vs_race, race, '{}@{}'.format(player_id, replay_name))
parse_replay(replay_player_path, sampled_frame_path, reward)
pbar.update()
def __call__(self, line):
replay_path, replay_info_path = line
with open(replay_info_path) as f:
info = json.load(f)
info = Parse(info['info'], sc_pb.ResponseReplayInfo())
replay_name = os.path.basename(replay_path)
sampled_action_path = os.path.join(FLAGS.parsed_replay_path, 'SampledActions', self.race_vs_race, replay_name)
for player_info in info.player_info:
race = sc_pb.Race.Name(player_info.player_info.race_actual)
player_id = player_info.player_info.player_id
reward = 2 - player_info.player_result.result
replay_player_path = os.path.join(self.race_vs_race, race, '{}@{}'.format(player_id, replay_name))
parse_replay(replay_player_path, sampled_action_path, reward, race,
race if len(self.races) == 1 else list(self.races - {race})[0], self.stats[race])
def main():
np.random.seed(FLAGS.seed)
ratio = np.asarray([float(i) for i in FLAGS.ratio.split(':')])
ratio /= np.sum(ratio)
if not os.path.isdir(FLAGS.save_path):
os.makedirs(FLAGS.save_path)
with open(FLAGS.hq_replay_set) as f:
replays_list = json.load(f)
result = []
race_vs_race = os.path.basename(FLAGS.hq_replay_set).split('.')[0]
for replay_path, info_path in replays_list:
replay_path_dict = {}
replay_name = os.path.basename(replay_path)
## Parsed Replay
for race in set(race_vs_race.split('_vs_')):
replay_path_dict[race] = []
with open(info_path) as f:
info = json.load(f)
proto = Parse(info['info'], sc_pb.ResponseReplayInfo())
for p in proto.player_info:
player_id = p.player_info.player_id
race = sc_pb.Race.Name(p.player_info.race_actual)
parsed_replays_info = {}
## Global Feature
global_path = os.path.join(FLAGS.parsed_replay_path, 'GlobalFeatureVector', race_vs_race, race,
'{}@{}.npz'.format(player_id, replay_name))
if os.path.isfile(os.path.join(FLAGS.root, global_path)):
parsed_replays_info['global_path'] = global_path
## Spatial Feature
spatial_path_S = os.path.join(FLAGS.parsed_replay_path, 'SpatialFeatureTensor', race_vs_race, race,
'{}@{}@S.npz'.format(player_id, replay_name))
if os.path.isfile(os.path.join(FLAGS.root, spatial_path_S)):
parsed_replays_info['spatial_path_S'] = spatial_path_S
spatial_path_G = os.path.join(FLAGS.parsed_replay_path, 'SpatialFeatureTensor', race_vs_race, race,
'{}@{}@G.npz'.format(player_id, replay_name))
if os.path.isfile(os.path.join(FLAGS.root, spatial_path_G)):
parsed_replays_info['spatial_path_G'] = spatial_path_G
replay_path_dict[race].append(parsed_replays_info)
result.append(replay_path_dict)
FLAGS.save_path = os.path.join(FLAGS.save_path, race_vs_race)
if not os.path.isdir(FLAGS.save_path):
os.makedirs(FLAGS.save_path)
train_end = int(len(result)*ratio[0])
val_end = int(len(result)*(ratio[0]+ratio[1]))
np.random.shuffle(result)
save(result[:train_end], 'train', FLAGS.save_path)
save(result[train_end:val_end], 'val', FLAGS.save_path)
save(result[val_end:], 'test', FLAGS.save_path)
