def get_join_tokens():
if marlo.is_grading():
"""
In the crowdAI Evaluation environment obtain the join_tokens
from the evaluator
the `params` parameter passed to the `evaluator_join_token` only allows
the following keys :
"seed",
"tick_length",
"max_retries",
"retry_sleep",
"step_sleep",
"skip_steps",
"videoResolution",
"continuous_to_discrete",
"allowContinuousMovement",
"allowDiscreteMovement",
"allowAbsoluteMovement",
"add_noop_command",
"comp_all_commands"
# TODO: Add this to the official documentation ?
# Help Wanted :D Pull Requests welcome :D
"""
join_tokens = marlo.evaluator_join_token(params={})
else:
"""
When debugging locally,
Please ensure that you have a Minecraft client running on port 10000 and 10001
by doing :
$MALMO_MINECRAFT_ROOT/launchClient.sh -port 10000
$MALMO_MINECRAFT_ROOT/launchClient.sh -port 10001
"""
print("Generating join tokens locally...")
client_pool = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
join_tokens = marlo.make('MarLo-BuildbattleTrain1-v0',
params={
"client_pool": client_pool,
"agent_names" : [
"MarLo-Agent-0",
"MarLo-Agent-1"
]
})
return join_tokens
def get_join_tokens():
if marlo.is_grading():
"""
In the crowdAI Evaluation environment obtain the join_tokens
from the evaluator
the `params` parameter passed to the `evaluator_join_token` only allows
the following keys :
"seed",
"tick_length",
"max_retries",
"retry_sleep",
"step_sleep",
"skip_steps",
"videoResolution",
"continuous_to_discrete",
"allowContinuousMovement",
"allowDiscreteMovement",
"allowAbsoluteMovement",
"add_noop_command",
"comp_all_commands"
# TODO: Add this to the official documentation ?
# Help Wanted :D Pull Requests welcome :D
"""
join_tokens = marlo.evaluator_join_token(params={})
else:
"""
When debugging locally,
Please ensure that you have a Minecraft client running on port 10000 and 10001
by doing :
$MALMO_MINECRAFT_ROOT/launchClient.sh -port 10000
$MALMO_MINECRAFT_ROOT/launchClient.sh -port 10001
"""
print("Generating join tokens locally...")
client_pool = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
join_tokens = marlo.make('MarLo-BuildbattleTrain1-v0',
params={
"client_pool":
client_pool,
"agent_names":
["MarLo-Agent-0", "MarLo-Agent-1"]
})
return join_tokens
def get_join_tokens():
if marlo.is_grading():
"""
In the crowdAI Evaluation environment obtain the join_tokens
from the evaluator
"""
join_tokens = marlo.evaluator_join_token()
else:
"""
When debugging locally,
Please ensure that you have a Minecraft client running on port 10000
by doing :
$MALMO_MINECRAFT_ROOT/launchClient.sh -port 10000
"""
client_pool = [('127.0.0.1', 10000)]
join_tokens = marlo.make('MarLo-FindTheGoal-v0',
params={"client_pool": client_pool})
return join_tokens
function calls, then the evaluation of your code will fail in case
of a tournament, where multiple submissions can control different agents
in the same game.
"""
for _idx, join_token in enumerate(join_tokens):
# Run agent-N on a separate thread
thread_handler = run_agent(join_token, _idx)
# Accumulate thread handlers
thread_handlers.append(thread_handler)
# Wait for threads to complete or raise an exception
marlo.utils.join_all(thread_handlers)
print("Episode Run Complete")
if __name__ == "__main__":
"""
In case of debugging locally, run the episode just once
and in case of when the agent is being evaluated, continue
running episodes for as long as the evaluator keeps supplying
join_tokens.
"""
if not marlo.is_grading():
print("Running single episode...")
run_episode()
else:
while True:
run_episode()
function calls, then the evaluation of your code will fail in case
of a tournament, where multiple submissions can control different agents
in the same game.
"""
for _idx, join_token in enumerate(join_tokens):
# Run agent-N on a separate thread
thread_handler = run_agent(join_token, _idx)
# Accumulate thread handlers
thread_handlers.append(thread_handler)
# Wait for threads to complete or raise an exception
marlo.utils.join_all(thread_handlers)
print("Episode Run Complete")
if __name__ == "__main__":
"""
In case of debugging locally, run the episode just once
and in case of when the agent is being evaluated, continue
running episodes for as long as the evaluator keeps supplying
join_tokens.
"""
if not marlo.is_grading():
print("Running single episode...")
run_episode()
else:
while True:
run_episode()