def worker_function(*args, config_path=None, config=None, **kwargs):
from baselines.common.cmd_util import common_arg_parser
from nvidia_gpu_scheduler.utils import log_tqdm
import os
from tqdm import tqdm
# Display addtional info (real-time child process progress not working)
arg_parser = common_arg_parser()
parsed_args, parsed_unknown_args = arg_parser.parse_known_args(*args)
pbar = tqdm(total=parsed_args.num_timesteps)
config_filename = os.path.basename(os.path.basename(config_path))
log_tqdm(pbar, config_filename, remove=True)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
# Execute OpenAI baselines.run module
run_baseline(args)
# Close tqdm and remove tqdm logs
log_tqdm(pbar, config_filename, remove=True)
pbar.close()
def run(steps=0, error_rate=0):
pbar = tqdm(total=steps)
config_filename = os.path.basename(os.path.basename(config_path))
log_tqdm(pbar, config_filename)
for i in range(steps):
time.sleep(1)
pbar.update(n=1)
log_tqdm(pbar, config_filename)
log_tqdm(pbar, config_filename, remove=True)
pbar.close()
# intentionally trigger error
trigger_error = random.random() < error_rate
if trigger_error:
raise ValueError('failed with %d%% probability' %
(error_rate * 100))
else:
print('succeeded with %d%% probability' %
(100 - error_rate * 100))
def worker_function(*args, config_path=None, config=None, **kwargs):
import os
import random
import time
from tqdm import tqdm
from nvidia_gpu_scheduler.utils import log_tqdm
n = config.steps
pbar = tqdm(total=n)
config_filename = os.path.basename(os.path.basename(config_path))
log_tqdm(pbar, config_filename)
for i in range(n):
time.sleep(1)
pbar.update(n=1)
log_tqdm(pbar, config_filename)
log_tqdm(pbar, config_filename, remove=True)
pbar.close()
# intentionally trigger with 50% probability
trigger_error = random.random() < config.error_rate
if trigger_error:
raise ValueError('failed with 50% probability')
else:
print('succeeded with 50% probability')