def main():
# init maze environment including observation and action interfaces
env = maze_env_factory(max_pieces_in_inventory=200,
raw_piece_size=[100, 100],
static_demand=(30, 15))
# wrap environment with logging wrapper
env = LogStatsWrapper(env, logging_prefix="main")
# register a console writer and connect the writer to the statistics logging system
with SimpleStatsLoggingSetup(env):
# reset environment
obs = env.reset()
# run interaction loop
for i in range(15):
# sample random action
action = env.action_space.sample()
# take actual environment step
obs, reward, done, info = env.step(action)
from docs.tutorial_maze_env.part04_events.env.maze_env import maze_env_factory
from maze.utils.log_stats_utils import SimpleStatsLoggingSetup
from maze.core.wrappers.log_stats_wrapper import LogStatsWrapper
# init maze environment
env = maze_env_factory(max_pieces_in_inventory=200,
raw_piece_size=[100, 100],
static_demand=(30, 15))
# wrap environment with logging wrapper
env = LogStatsWrapper(env, logging_prefix="main")
# register a console writer and connect the writer to the statistics logging system
with SimpleStatsLoggingSetup(env):
# reset environment and run interaction loop
obs = env.reset()
for i in range(15):
action = env.action_space.sample()
obs, reward, done, info = env.step(action)