def __init__(self, path, device):
self.params = parameters.Params()
self.params.load(os.path.join(path, 'params.json'))
print('Loading metric...')
self.selector = ae.ConvAE(device=device,
encoding_shape=self.params.feature_size,
learning_rate=0.0001,
beta=1)
self.selector.load(os.path.join(path, 'models/ckpt/ckpt_ae.pth'))
self.selector.training = False
u_limit = 600
l_limit = 0
else:
u_limit = 1.35
l_limit = -u_limit
utils.show(bs_points,
filepath=params.save_path,
name='final_{}_{}'.format(evolver.elapsed_gen, params.env_tag),
info={'seed': seed},
upper_limit=u_limit,
lower_limit=l_limit)
if __name__ == "__main__":
p = parameters.Params()
parallel_threads = p.threads
seeds = [
11, 59, 3, 6, 4, 18, 13, 1, 22, 34, 99, 43, 100, 15, 66, 10, 7, 9, 42,
2
]
# Selects seeds to run in parallel
multiseeds = []
for i in range(0, len(seeds), parallel_threads):
multiseeds.append(seeds[i:min(i + parallel_threads, len(seeds))])
total_train_time = 0
for seeds in multiseeds:
params = [parameters.Params()
def load_params(self, path):
print('Loading parameters...')
self.params = parameters.Params()
self.params.load(os.path.join(path, 'params.json'))
assert self.env_tag == self.params.env_tag, 'Env tag from folder different from parameters env tag: {} - {}'.format(self.env_tag, self.params.env_tag)
# print("")
# for key in errors:
# avg = np.mean(errors[key])
# std = np.std(errors[key])
# print("Seed {}: Mean {} - Std {}.".format(key, avg, std))
# Parameters
# -----------------------------------------------
seed = 42
load_path = '/home/giuseppe/src/taxons/experiments/Maze_AE_Mixed/{}'.format(seed)
params = parameters.Params()
params.load(os.path.join(load_path, 'params.json'))
env = gym.make(params.env_tag)
# -----------------------------------------------
# Possible targets
# -----------------------------------------------
# x = []
# target_poses = []
# if "Billiard" in params.env_tag:
# env.env.params.RANDOM_BALL_INIT_POSE = True
# elif "Ant" in params.env_tag:
# env.render()
#
# for k in range(50): # Generate 50 target datapoints