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Submission 13533

Submission13533
Competingyes
Challengeaido-LFV_multi-sim-validation
UserAndrás Kalapos 🇭🇺
Date submitted
Last status update
Completecomplete
DetailsEvaluation is complete.
Sisters
Result💚
Jobssim-0of4: 105154 sim-1of4: 105151 sim-2of4: 105148 sim-3of4: 105150
Next
User labelreal-v1.0-3092-363
Admin priority50
Blessingn/a
User priority50

105154

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loop2-000

105151

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zigzag-000

105150

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loop-000

105148

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autolab-000

Evaluation jobs for this submission

See previous jobs for previous versions of challenges
Job IDstepstatusup to datedate starteddate completeddurationmessage
105154sim-0of4successyes0:07:52
Artefacts hidden. If you are the author, please login using the top-right link or use the dashboard.
survival_time_median59.99999999999873
in-drivable-lane_median0.0
driven_lanedir_consec_median30.085963143999756
deviation-center-line_median2.6013706622390314


other stats
deviation-center-line_max2.6342675832665265
deviation-center-line_mean2.6013706622390314
deviation-center-line_min2.568473741211536
deviation-heading_max6.874552243963652
deviation-heading_mean6.840045238488424
deviation-heading_median6.840045238488424
deviation-heading_min6.805538233013195
distance-from-start_max1.553528354810836
distance-from-start_mean1.5386894489912364
distance-from-start_median1.5386894489912364
distance-from-start_min1.5238505431716365
driven_any_max30.417627606844007
driven_any_mean30.37921524610562
driven_any_median30.37921524610562
driven_any_min30.340802885367232
driven_lanedir_consec_max30.125631064170147
driven_lanedir_consec_mean30.085963143999756
driven_lanedir_consec_min30.046295223829365
driven_lanedir_max30.125631064170147
driven_lanedir_mean30.085963143999756
driven_lanedir_median30.085963143999756
driven_lanedir_min30.046295223829365
in-drivable-lane_max0.0
in-drivable-lane_mean0.0
in-drivable-lane_min0.0
per-episodes
details{"loop2-000-ego0": {"driven_any": 30.340802885367232, "survival_time": 59.99999999999873, "driven_lanedir": 30.046295223829365, "in-drivable-lane": 0.0, "deviation-heading": 6.874552243963652, "distance-from-start": 1.5238505431716365, "deviation-center-line": 2.568473741211536, "driven_lanedir_consec": 30.046295223829365}, "loop2-000-ego1": {"driven_any": 30.417627606844007, "survival_time": 59.99999999999873, "driven_lanedir": 30.125631064170147, "in-drivable-lane": 0.0, "deviation-heading": 6.805538233013195, "distance-from-start": 1.553528354810836, "deviation-center-line": 2.6342675832665265, "driven_lanedir_consec": 30.125631064170147}}
simulation-passed1
survival_time_max59.99999999999873
survival_time_mean59.99999999999873
survival_time_min59.99999999999873
No reset possible
105152sim-0of4successyes0:07:58
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105151sim-1of4successyes0:25:50
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survival_time_median59.99999999999873
in-drivable-lane_median0.0
driven_lanedir_consec_median28.695754836735077
deviation-center-line_median2.7783928147590142


other stats
deviation-center-line_max2.890252134890972
deviation-center-line_mean2.788727685021872
deviation-center-line_min2.7078729756784874
deviation-heading_max8.743311432888396
deviation-heading_mean8.176985228062325
deviation-heading_median8.177001514476252
deviation-heading_min7.610626450408398
distance-from-start_max4.514576585448333
distance-from-start_mean3.8412042583264214
distance-from-start_median3.767107191802359
distance-from-start_min3.3160260642526347
driven_any_max29.187239506629325
driven_any_mean29.030728957706984
driven_any_median29.043950984311152
driven_any_min28.84777435557631
driven_lanedir_consec_max28.865708149758984
driven_lanedir_consec_mean28.61929751182401
driven_lanedir_consec_min28.21997222406689
driven_lanedir_max28.865708149758984
driven_lanedir_mean28.61929751182401
driven_lanedir_median28.695754836735077
driven_lanedir_min28.21997222406689
in-drivable-lane_max0.5500000000000004
in-drivable-lane_mean0.1375000000000001
in-drivable-lane_min0.0
per-episodes
details{"zigzag-000-ego0": {"driven_any": 29.150656354517075, "survival_time": 59.99999999999873, "driven_lanedir": 28.832280556350995, "in-drivable-lane": 0.0, "deviation-heading": 7.716934409941715, "distance-from-start": 3.7647795953798617, "deviation-center-line": 2.7277787772706663, "driven_lanedir_consec": 28.832280556350995}, "zigzag-000-ego1": {"driven_any": 28.93724561410523, "survival_time": 59.99999999999873, "driven_lanedir": 28.55922911711916, "in-drivable-lane": 0.0, "deviation-heading": 8.637068619010789, "distance-from-start": 3.3160260642526347, "deviation-center-line": 2.890252134890972, "driven_lanedir_consec": 28.55922911711916}, "zigzag-000-ego2": {"driven_any": 29.187239506629325, "survival_time": 59.99999999999873, "driven_lanedir": 28.865708149758984, "in-drivable-lane": 0.0, "deviation-heading": 7.610626450408398, "distance-from-start": 3.769434788224858, "deviation-center-line": 2.7078729756784874, "driven_lanedir_consec": 28.865708149758984}, "zigzag-000-ego3": {"driven_any": 28.84777435557631, "survival_time": 59.99999999999873, "driven_lanedir": 28.21997222406689, "in-drivable-lane": 0.5500000000000004, "deviation-heading": 8.743311432888396, "distance-from-start": 4.514576585448333, "deviation-center-line": 2.8290068522473617, "driven_lanedir_consec": 28.21997222406689}}
simulation-passed1
survival_time_max59.99999999999873
survival_time_mean59.99999999999873
survival_time_min59.99999999999873
No reset possible
105150sim-3of4successyes0:19:10
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survival_time_median59.99999999999873
in-drivable-lane_median0.0
driven_lanedir_consec_median31.038133526200156
deviation-center-line_median2.533407987536443


other stats
deviation-center-line_max2.9009947823630085
deviation-center-line_mean2.6170510283530324
deviation-center-line_min2.5003933559762346
deviation-heading_max7.798959125130548
deviation-heading_mean7.233477277268131
deviation-heading_median7.126685215530896
deviation-heading_min6.881579552880183
distance-from-start_max3.249331035540738
distance-from-start_mean2.7809393989451587
distance-from-start_median2.9014592245674473
distance-from-start_min2.0715081111050027
driven_any_max31.453230794395083
driven_any_mean31.170200410378396
driven_any_median31.341462529222845
driven_any_min30.54464578867282
driven_lanedir_consec_max31.15378039512112
driven_lanedir_consec_mean30.86695192250479
driven_lanedir_consec_min30.237760242497732
driven_lanedir_max31.15378039512112
driven_lanedir_mean30.86695192250479
driven_lanedir_median31.038133526200156
driven_lanedir_min30.237760242497732
in-drivable-lane_max0.0
in-drivable-lane_mean0.0
in-drivable-lane_min0.0
per-episodes
details{"loop-000-ego0": {"driven_any": 30.54464578867282, "survival_time": 59.99999999999873, "driven_lanedir": 30.237760242497732, "in-drivable-lane": 0.0, "deviation-heading": 7.798959125130548, "distance-from-start": 2.0715081111050027, "deviation-center-line": 2.9009947823630085, "driven_lanedir_consec": 30.237760242497732}, "loop-000-ego1": {"driven_any": 31.240821950329128, "survival_time": 59.99999999999873, "driven_lanedir": 30.925667447149333, "in-drivable-lane": 0.0, "deviation-heading": 7.244801297197082, "distance-from-start": 3.249331035540738, "deviation-center-line": 2.525892756298839, "driven_lanedir_consec": 30.925667447149333}, "loop-000-ego2": {"driven_any": 31.453230794395083, "survival_time": 59.99999999999873, "driven_lanedir": 31.150599605250974, "in-drivable-lane": 0.0, "deviation-heading": 7.00856913386471, "distance-from-start": 3.244594309219576, "deviation-center-line": 2.5003933559762346, "driven_lanedir_consec": 31.150599605250974}, "loop-000-ego3": {"driven_any": 31.44210310811656, "survival_time": 59.99999999999873, "driven_lanedir": 31.15378039512112, "in-drivable-lane": 0.0, "deviation-heading": 6.881579552880183, "distance-from-start": 2.558324139915319, "deviation-center-line": 2.5409232187740467, "driven_lanedir_consec": 31.15378039512112}}
simulation-passed1
survival_time_max59.99999999999873
survival_time_mean59.99999999999873
survival_time_min59.99999999999873
No reset possible
105148sim-2of4successyes0:23:18
Artefacts hidden. If you are the author, please login using the top-right link or use the dashboard.
survival_time_median58.649999999998805
in-drivable-lane_median0.0
driven_lanedir_consec_median25.874726064531018
deviation-center-line_median2.962650517638707


other stats
deviation-center-line_max3.130218545814259
deviation-center-line_mean2.948759656438656
deviation-center-line_min2.7395190446629503
deviation-heading_max8.18693486157638
deviation-heading_mean7.412345511278785
deviation-heading_median7.28481419011348
deviation-heading_min6.8928188033117985
distance-from-start_max4.380918099389127
distance-from-start_mean3.7322322975407585
distance-from-start_median3.870333692572867
distance-from-start_min2.807343705628174
driven_any_max28.609042309922064
driven_any_mean26.58393943156665
driven_any_median26.146843299779988
driven_any_min25.43302881678456
driven_lanedir_consec_max28.37096490423912
driven_lanedir_consec_mean26.316219883575393
driven_lanedir_consec_min25.14446250100041
driven_lanedir_max28.37096490423912
driven_lanedir_mean26.316219883575393
driven_lanedir_median25.874726064531018
driven_lanedir_min25.14446250100041
in-drivable-lane_max0.0
in-drivable-lane_mean0.0
in-drivable-lane_min0.0
per-episodes
details{"autolab-000-ego0": {"driven_any": 25.43302881678456, "survival_time": 58.649999999998805, "driven_lanedir": 25.14446250100041, "in-drivable-lane": 0.0, "deviation-heading": 7.644809249226561, "distance-from-start": 4.027384618555687, "deviation-center-line": 3.130218545814259, "driven_lanedir_consec": 25.14446250100041}, "autolab-000-ego1": {"driven_any": 26.20285822830444, "survival_time": 58.649999999998805, "driven_lanedir": 25.93222975619936, "in-drivable-lane": 0.0, "deviation-heading": 6.8928188033117985, "distance-from-start": 4.380918099389127, "deviation-center-line": 3.1094085968040015, "driven_lanedir_consec": 25.93222975619936}, "autolab-000-ego2": {"driven_any": 28.609042309922064, "survival_time": 58.649999999998805, "driven_lanedir": 28.37096490423912, "in-drivable-lane": 0.0, "deviation-heading": 6.924819131000399, "distance-from-start": 2.807343705628174, "deviation-center-line": 2.7395190446629503, "driven_lanedir_consec": 28.37096490423912}, "autolab-000-ego3": {"driven_any": 26.090828371255537, "survival_time": 58.649999999998805, "driven_lanedir": 25.817222372862673, "in-drivable-lane": 0.0, "deviation-heading": 8.18693486157638, "distance-from-start": 3.7132827665900465, "deviation-center-line": 2.8158924384734125, "driven_lanedir_consec": 25.817222372862673}}
simulation-passed1
survival_time_max58.649999999998805
survival_time_mean58.649999999998805
survival_time_min58.649999999998805
No reset possible
88262403successyes0:49:10
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88261403successyes0:39:53
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88260402successyes1:01:50
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88259402successyes0:44:11
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71808402successyes1:03:16
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71639402timeoutyes----No reset possible
71357403successyes0:42:11
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62356356failedyes0:02:05
InvalidSubmission: T [...]
InvalidSubmission:
Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/duckietown_experiment_manager/code.py", line 242, in main
    robot_ci.write_topic_and_expect_zero("seed", config.seed)
  File "/usr/local/lib/python3.8/site-packages/zuper_nodes_wrapper/wrapper_outside.py", line 143, in write_topic_and_expect_zero
    msgs = read_reply(self.fpout, timeout=timeout, nickname=self.nickname)
  File "/usr/local/lib/python3.8/site-packages/zuper_nodes_wrapper/wrapper_outside.py", line 309, in read_reply
    raise RemoteNodeAborted(msg)
zuper_nodes.structures.RemoteNodeAborted: The remote node "ego2" aborted with the following error:

error in ego2 |Unexpected error:
              |
              || Traceback (most recent call last):
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1365, in _do_call
              ||     return fn(*args)
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1349, in _run_fn
              ||     return self._call_tf_sessionrun(options, feed_dict, fetch_list,
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1441, in _call_tf_sessionrun
              ||     return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
              || tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
              ||   (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
              || 	 [[{{node default_policy/functional_1_1/conv_value_1/Relu}}]]
              ||   (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
              || 	 [[{{node default_policy/functional_1_1/conv_value_1/Relu}}]]
              || 	 [[default_policy/strided_slice_1/_3]]
              || 0 successful operations.
              || 0 derived errors ignored.
              ||
              || During handling of the above exception, another exception occurred:
              ||
              || Traceback (most recent call last):
              ||   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/wrapper.py", line 322, in loop
              ||     call_if_fun_exists(node, "init", context=context_data)
              ||   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/utils.py", line 21, in call_if_fun_exists
              ||     f(**kwargs)
              ||   File "solution.py", line 29, in init
              ||     self.model = RLlibModel(SEED,experiment_idx=0,checkpoint_idx=0,logger=context)
              ||   File "/submission/model.py", line 55, in __init__
              ||     self.model = PPOTrainer(config=config["rllib_config"])
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer_template.py", line 90, in __init__
              ||     Trainer.__init__(self, config, env, logger_creator)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 455, in __init__
              ||     super().__init__(config, logger_creator)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/tune/trainable.py", line 174, in __init__
              ||     self._setup(copy.deepcopy(self.config))
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 596, in _setup
              ||     self._init(self.config, self.env_creator)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer_template.py", line 115, in _init
              ||     self.workers = self._make_workers(env_creator, self._policy,
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 662, in _make_workers
              ||     return WorkerSet(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/worker_set.py", line 61, in __init__
              ||     self._local_worker = self._make_worker(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/worker_set.py", line 237, in _make_worker
              ||     worker = cls(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/rollout_worker.py", line 360, in __init__
              ||     self._build_policy_map(policy_dict, policy_config)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/rollout_worker.py", line 842, in _build_policy_map
              ||     policy_map[name] = cls(obs_space, act_space, merged_conf)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/tf_policy_template.py", line 129, in __init__
              ||     DynamicTFPolicy.__init__(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/dynamic_tf_policy.py", line 237, in __init__
              ||     self._initialize_loss()
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/dynamic_tf_policy.py", line 324, in _initialize_loss
              ||     postprocessed_batch = self.postprocess_trajectory(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/tf_policy_template.py", line 155, in postprocess_trajectory
              ||     return postprocess_fn(self, sample_batch, other_agent_batches,
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/ppo/ppo_tf_policy.py", line 182, in postprocess_ppo_gae
              ||     last_r = policy._value(sample_batch[SampleBatch.NEXT_OBS][-1],
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/utils/tf_ops.py", line 86, in call
              ||     return session_or_none.run(symbolic_out[0], feed_dict)
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 957, in run
              ||     result = self._run(None, fetches, feed_dict, options_ptr,
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1180, in _run
              ||     results = self._do_run(handle, final_targets, final_fetches,
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1358, in _do_run
              ||     return self._do_call(_run_fn, feeds, fetches, targets, options,
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1384, in _do_call
              ||     raise type(e)(node_def, op, message)
              || tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
              ||   (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
              || 	 [[node default_policy/functional_1_1/conv_value_1/Relu (defined at /usr/local/lib/python3.8/dist-packages/ray/rllib/models/tf/visionnet_v2.py:103) ]]
              ||   (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
              || 	 [[node default_policy/functional_1_1/conv_value_1/Relu (defined at /usr/local/lib/python3.8/dist-packages/ray/rllib/models/tf/visionnet_v2.py:103) ]]
              || 	 [[default_policy/strided_slice_1/_3]]
              || 0 successful operations.
              || 0 derived errors ignored.
              ||
              || Original stack trace for 'default_policy/functional_1_1/conv_value_1/Relu':
              ||   File "solution.py", line 127, in <module>
              ||     main()
              ||   File "solution.py", line 123, in main
              ||     wrap_direct(node=node, protocol=protocol)
              ||   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/interface.py", line 24, in wrap_direct
              ||     run_loop(node, protocol, args)
              ||   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/wrapper.py", line 243, in run_loop
              ||     loop(node_name, fi, fo, node, protocol, tin, tout, config=config, fi_desc=fin, fo_desc=fout)
              ||   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/wrapper.py", line 322, in loop
              ||     call_if_fun_exists(node, "init", context=context_data)
              ||   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/utils.py", line 21, in call_if_fun_exists
              ||     f(**kwargs)
              ||   File "solution.py", line 29, in init
              ||     self.model = RLlibModel(SEED,experiment_idx=0,checkpoint_idx=0,logger=context)
              ||   File "/submission/model.py", line 55, in __init__
              ||     self.model = PPOTrainer(config=config["rllib_config"])
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer_template.py", line 90, in __init__
              ||     Trainer.__init__(self, config, env, logger_creator)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 455, in __init__
              ||     super().__init__(config, logger_creator)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/tune/trainable.py", line 174, in __init__
              ||     self._setup(copy.deepcopy(self.config))
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 596, in _setup
              ||     self._init(self.config, self.env_creator)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer_template.py", line 115, in _init
              ||     self.workers = self._make_workers(env_creator, self._policy,
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 662, in _make_workers
              ||     return WorkerSet(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/worker_set.py", line 61, in __init__
              ||     self._local_worker = self._make_worker(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/worker_set.py", line 237, in _make_worker
              ||     worker = cls(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/rollout_worker.py", line 360, in __init__
              ||     self._build_policy_map(policy_dict, policy_config)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/rollout_worker.py", line 842, in _build_policy_map
              ||     policy_map[name] = cls(obs_space, act_space, merged_conf)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/tf_policy_template.py", line 129, in __init__
              ||     DynamicTFPolicy.__init__(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/dynamic_tf_policy.py", line 237, in __init__
              ||     self._initialize_loss()
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/dynamic_tf_policy.py", line 324, in _initialize_loss
              ||     postprocessed_batch = self.postprocess_trajectory(
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/tf_policy_template.py", line 155, in postprocess_trajectory
              ||     return postprocess_fn(self, sample_batch, other_agent_batches,
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/ppo/ppo_tf_policy.py", line 182, in postprocess_ppo_gae
              ||     last_r = policy._value(sample_batch[SampleBatch.NEXT_OBS][-1],
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/utils/tf_ops.py", line 84, in call
              ||     symbolic_out[0] = fn(*placeholders)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/ppo/ppo_tf_policy.py", line 235, in value
              ||     model_out, _ = self.model({
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/models/modelv2.py", line 150, in __call__
              ||     res = self.forward(restored, state or [], seq_lens)
              ||   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/models/tf/visionnet_v2.py", line 103, in forward
              ||     model_out, self._value_out = self.base_model(
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 776, in __call__
              ||     outputs = call_fn(cast_inputs, *args, **kwargs)
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/functional.py", line 385, in call
              ||     return self._run_internal_graph(
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/functional.py", line 508, in _run_internal_graph
              ||     outputs = node.layer(*args, **kwargs)
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 776, in __call__
              ||     outputs = call_fn(cast_inputs, *args, **kwargs)
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/convolutional.py", line 269, in call
              ||     return self.activation(outputs)
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 10435, in relu
              ||     _, _, _op, _outputs = _op_def_library._apply_op_helper(
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/op_def_library.py", line 742, in _apply_op_helper
              ||     op = g._create_op_internal(op_type_name, inputs, dtypes=None,
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 3477, in _create_op_internal
              ||     ret = Operation(
              ||   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 1949, in __init__
              ||     self._traceback = tf_stack.extract_stack()
              ||
              ||
              || The above exception was the direct cause of the following exception:
              ||
              || Traceback (most recent call last):
              ||   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/wrapper.py", line 339, in loop
              ||     raise Exception(msg) from e
              || Exception: Exception while calling the node's init() function.
              ||
              || | Traceback (most recent call last):
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1365, in _do_call
              || |     return fn(*args)
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1349, in _run_fn
              || |     return self._call_tf_sessionrun(options, feed_dict, fetch_list,
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1441, in _call_tf_sessionrun
              || |     return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
              || | tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
              || |   (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
              || | 	 [[{{node default_policy/functional_1_1/conv_value_1/Relu}}]]
              || |   (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
              || | 	 [[{{node default_policy/functional_1_1/conv_value_1/Relu}}]]
              || | 	 [[default_policy/strided_slice_1/_3]]
              || | 0 successful operations.
              || | 0 derived errors ignored.
              || |
              || | During handling of the above exception, another exception occurred:
              || |
              || | Traceback (most recent call last):
              || |   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/wrapper.py", line 322, in loop
              || |     call_if_fun_exists(node, "init", context=context_data)
              || |   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/utils.py", line 21, in call_if_fun_exists
              || |     f(**kwargs)
              || |   File "solution.py", line 29, in init
              || |     self.model = RLlibModel(SEED,experiment_idx=0,checkpoint_idx=0,logger=context)
              || |   File "/submission/model.py", line 55, in __init__
              || |     self.model = PPOTrainer(config=config["rllib_config"])
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer_template.py", line 90, in __init__
              || |     Trainer.__init__(self, config, env, logger_creator)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 455, in __init__
              || |     super().__init__(config, logger_creator)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/tune/trainable.py", line 174, in __init__
              || |     self._setup(copy.deepcopy(self.config))
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 596, in _setup
              || |     self._init(self.config, self.env_creator)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer_template.py", line 115, in _init
              || |     self.workers = self._make_workers(env_creator, self._policy,
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 662, in _make_workers
              || |     return WorkerSet(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/worker_set.py", line 61, in __init__
              || |     self._local_worker = self._make_worker(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/worker_set.py", line 237, in _make_worker
              || |     worker = cls(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/rollout_worker.py", line 360, in __init__
              || |     self._build_policy_map(policy_dict, policy_config)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/rollout_worker.py", line 842, in _build_policy_map
              || |     policy_map[name] = cls(obs_space, act_space, merged_conf)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/tf_policy_template.py", line 129, in __init__
              || |     DynamicTFPolicy.__init__(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/dynamic_tf_policy.py", line 237, in __init__
              || |     self._initialize_loss()
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/dynamic_tf_policy.py", line 324, in _initialize_loss
              || |     postprocessed_batch = self.postprocess_trajectory(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/tf_policy_template.py", line 155, in postprocess_trajectory
              || |     return postprocess_fn(self, sample_batch, other_agent_batches,
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/ppo/ppo_tf_policy.py", line 182, in postprocess_ppo_gae
              || |     last_r = policy._value(sample_batch[SampleBatch.NEXT_OBS][-1],
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/utils/tf_ops.py", line 86, in call
              || |     return session_or_none.run(symbolic_out[0], feed_dict)
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 957, in run
              || |     result = self._run(None, fetches, feed_dict, options_ptr,
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1180, in _run
              || |     results = self._do_run(handle, final_targets, final_fetches,
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1358, in _do_run
              || |     return self._do_call(_run_fn, feeds, fetches, targets, options,
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py", line 1384, in _do_call
              || |     raise type(e)(node_def, op, message)
              || | tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
              || |   (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
              || | 	 [[node default_policy/functional_1_1/conv_value_1/Relu (defined at /usr/local/lib/python3.8/dist-packages/ray/rllib/models/tf/visionnet_v2.py:103) ]]
              || |   (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
              || | 	 [[node default_policy/functional_1_1/conv_value_1/Relu (defined at /usr/local/lib/python3.8/dist-packages/ray/rllib/models/tf/visionnet_v2.py:103) ]]
              || | 	 [[default_policy/strided_slice_1/_3]]
              || | 0 successful operations.
              || | 0 derived errors ignored.
              || |
              || | Original stack trace for 'default_policy/functional_1_1/conv_value_1/Relu':
              || |   File "solution.py", line 127, in <module>
              || |     main()
              || |   File "solution.py", line 123, in main
              || |     wrap_direct(node=node, protocol=protocol)
              || |   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/interface.py", line 24, in wrap_direct
              || |     run_loop(node, protocol, args)
              || |   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/wrapper.py", line 243, in run_loop
              || |     loop(node_name, fi, fo, node, protocol, tin, tout, config=config, fi_desc=fin, fo_desc=fout)
              || |   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/wrapper.py", line 322, in loop
              || |     call_if_fun_exists(node, "init", context=context_data)
              || |   File "/usr/local/lib/python3.8/dist-packages/zuper_nodes_wrapper/utils.py", line 21, in call_if_fun_exists
              || |     f(**kwargs)
              || |   File "solution.py", line 29, in init
              || |     self.model = RLlibModel(SEED,experiment_idx=0,checkpoint_idx=0,logger=context)
              || |   File "/submission/model.py", line 55, in __init__
              || |     self.model = PPOTrainer(config=config["rllib_config"])
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer_template.py", line 90, in __init__
              || |     Trainer.__init__(self, config, env, logger_creator)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 455, in __init__
              || |     super().__init__(config, logger_creator)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/tune/trainable.py", line 174, in __init__
              || |     self._setup(copy.deepcopy(self.config))
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 596, in _setup
              || |     self._init(self.config, self.env_creator)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer_template.py", line 115, in _init
              || |     self.workers = self._make_workers(env_creator, self._policy,
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/trainer.py", line 662, in _make_workers
              || |     return WorkerSet(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/worker_set.py", line 61, in __init__
              || |     self._local_worker = self._make_worker(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/worker_set.py", line 237, in _make_worker
              || |     worker = cls(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/rollout_worker.py", line 360, in __init__
              || |     self._build_policy_map(policy_dict, policy_config)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/evaluation/rollout_worker.py", line 842, in _build_policy_map
              || |     policy_map[name] = cls(obs_space, act_space, merged_conf)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/tf_policy_template.py", line 129, in __init__
              || |     DynamicTFPolicy.__init__(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/dynamic_tf_policy.py", line 237, in __init__
              || |     self._initialize_loss()
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/dynamic_tf_policy.py", line 324, in _initialize_loss
              || |     postprocessed_batch = self.postprocess_trajectory(
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/policy/tf_policy_template.py", line 155, in postprocess_trajectory
              || |     return postprocess_fn(self, sample_batch, other_agent_batches,
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/ppo/ppo_tf_policy.py", line 182, in postprocess_ppo_gae
              || |     last_r = policy._value(sample_batch[SampleBatch.NEXT_OBS][-1],
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/utils/tf_ops.py", line 84, in call
              || |     symbolic_out[0] = fn(*placeholders)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/agents/ppo/ppo_tf_policy.py", line 235, in value
              || |     model_out, _ = self.model({
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/models/modelv2.py", line 150, in __call__
              || |     res = self.forward(restored, state or [], seq_lens)
              || |   File "/usr/local/lib/python3.8/dist-packages/ray/rllib/models/tf/visionnet_v2.py", line 103, in forward
              || |     model_out, self._value_out = self.base_model(
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 776, in __call__
              || |     outputs = call_fn(cast_inputs, *args, **kwargs)
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/functional.py", line 385, in call
              || |     return self._run_internal_graph(
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/functional.py", line 508, in _run_internal_graph
              || |     outputs = node.layer(*args, **kwargs)
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 776, in __call__
              || |     outputs = call_fn(cast_inputs, *args, **kwargs)
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/convolutional.py", line 269, in call
              || |     return self.activation(outputs)
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 10435, in relu
              || |     _, _, _op, _outputs = _op_def_library._apply_op_helper(
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/op_def_library.py", line 742, in _apply_op_helper
              || |     op = g._create_op_internal(op_type_name, inputs, dtypes=None,
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 3477, in _create_op_internal
              || |     ret = Operation(
              || |   File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 1949, in __init__
              || |     self._traceback = tf_stack.extract_stack()
              || |
              || |
              ||

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/duckietown_challenges/cie_concrete.py", line 681, in scoring_context
    yield cie
  File "/usr/local/lib/python3.8/site-packages/duckietown_experiment_manager/experiment_manager.py", line 68, in go
    wrap(cie)
  File "/usr/local/lib/python3.8/site-packages/duckietown_experiment_manager/experiment_manager.py", line 34, in wrap
    asyncio.run(main(cie, logdir, attempts), debug=True)
  File "/usr/local/lib/python3.8/asyncio/runners.py", line 44, in run
    return loop.run_until_complete(main)
  File "/usr/local/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete
    return future.result()
  File "/usr/local/lib/python3.8/site-packages/duckietown_experiment_manager/code.py", line 249, in main
    raise InvalidSubmission(msg) from e
duckietown_challenges.exceptions.InvalidSubmission: Getting agent protocol
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