os.makedirs(model_dir)
agent = Agent(name, brain, 1, reward_to_go=True, nn_baseline=True, normalize_advantages=True,
model_save_path='%s/model.ckpt' % model_dir)
machine_configs = [MachineConfig(2, 1, 1) for i in range(machines_number)]
csv_reader = CSVReader(jobs_csv)
jobs_configs = csv_reader.generate(0, jobs_len)
tic = time.time()
algorithm = RandomAlgorithm()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
print('RandomAlgorithm')
print(episode.env.now, time.time() - tic, average_completion(episode), average_slowdown(episode))
tic = time.time()
algorithm = RandomAlgorithm()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
print('RandomAlgorithm')
print(episode.env.now, time.time() - tic, average_completion(episode), average_slowdown(episode))
tic = time.time()
algorithm = RandomAlgorithm()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
print('RandomAlgorithm')
print(episode.env.now, time.time() - tic, average_completion(episode), average_slowdown(episode))
nn_baseline=True,
normalize_advantages=True,
model_save_path='%s/model.ckpt' % model_dir)
machine_configs = [MachineConfig(64, 1, 1) for i in range(machines_number)]
csv_reader = CSVReader(jobs_csv)
for job_chunk in range(n_job_chunk):
jobs_configs = csv_reader.generate(job_chunk * jobs_len, jobs_len)
tic = time.time()
algorithm = RandomAlgorithm()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
print(episode.env.now,
time.time() - tic, average_completion(episode),
average_slowdown(episode))
agent.log('makespan-random', episode.env.now, agent.global_step)
tic = time.time()
algorithm = FirstFitAlgorithm()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
print(episode.env.now,
time.time() - tic, average_completion(episode),
average_slowdown(episode))
agent.log('makespan-ff', episode.env.now, agent.global_step)
tic = time.time()
algorithm = Tetris()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
os.makedirs(model_dir)
agent = Agent(name, brain, 1, reward_to_go=True, nn_baseline=True, normalize_advantages=True,
model_save_path='%s/model.ckpt' % model_dir)
machine_configs = [MachineConfig(2, 1, 1) for i in range(machines_number)]
csv_reader = CSVReader(jobs_csv)
jobs_configs = csv_reader.generate(0, jobs_len)
tic = time.time()
algorithm = RandomAlgorithm()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
print('RandomAlgorithm')
print(episode.env.now, time.time() - tic, average_completion(episode), average_slowdown(episode))
tic = time.time()
algorithm = RandomAlgorithm()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
print('RandomAlgorithm')
print(episode.env.now, time.time() - tic, average_completion(episode), average_slowdown(episode))
tic = time.time()
algorithm = RandomAlgorithm()
episode = Episode(machine_configs, jobs_configs, algorithm, None)
episode.run()
print('RandomAlgorithm')
print(episode.env.now, time.time() - tic, average_completion(episode), average_slowdown(episode))