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Petero 112

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Sample-efficient reinforcement learning in Minecraft

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Multi Agent Reinforcement Learning on Trains.

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A new benchmark for Artificial Intelligence (AI) research in Reinforcement Learning

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Trustable
May 16, 2020
Newtonian
May 16, 2020

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    May 16, 2020

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  • Kudos! You've won a bronze badge in this challenge. Keep up the great work!
    Challenge: Unity Obstacle Tower Challenge
    May 16, 2020
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Unity Obstacle Tower Challenge

How to show the Media?

About 1 year ago

Hi, I’m curious about how to show the Media in my submission?:stuck_out_tongue_winking_eye:

And another thing. After I answered Teri Pierce’s email. I didn’t receive any reply. Does that mean I have been eliminated?

Git push over 50mb

Over 1 year ago

I use this method and solve my problem. You can try this.

Git push over 50mb

Over 1 year ago

https://gitlab.aicrowd.com/Petero/obstacle-tower-challenge/issues/54

Evaluation Logs (Debug Mode)
This is a debug mode to test out your submission in AICrowd environment, the actual scores for this submission will not be reflected back to leaderboard.
State : Evaluation Pending :hourglass:
Total Execution Time :hourglass: : 9919s

Pod Health :heart:

Pod State : Pending

Pod Scheduling Time :clock1: : 9530 secs

Containers Waiting :large_orange_diamond: : redis-server,aicrowd-subcontractor

Git push over 50mb

Over 1 year ago

(post withdrawn by author, will be automatically deleted in 24 hours unless flagged)

Git push over 50mb

Over 1 year ago

Hi,Mohanty. I think the problem is still there.

Git push over 50mb

Over 1 year ago

Hi, Mohanty. There is the “pending” problem again.

Evaluation Logs (Debug Mode)
This is a debug mode to test out your submission in AICrowd environment, the actual scores for this submission will not be reflected back to leaderboard.
State : Evaluation Pending :hourglass:
Total Execution Time :hourglass: : 12634s

Pod Health :heart:

Pod State : Pending

Pod Scheduling Time :clock1: : 12135 secs

Containers Waiting :large_orange_diamond: : redis-server,aicrowd-subcontractor

Git push over 50mb

Over 1 year ago

How can I push a file over 50mb?

During the submission.
I got an error when I restore my model.

Message type "tensorflow.MetaGraphDef" has no field named "version"..

This problem is rare.I google it and has little result.But the model runs fine in the GCP. I try many way to figure out. Finally I try not use the “git lfs” but normal git push the .meta file and problem solved.
Then I got another error:

not an sstable (bad magic number)

and I tried to normal git push the other model files. Lots of them was pushed. Except a file about 81mb.

When I push it. Shows the error

 fatal: pack exceeds maximum allowed size.

I use git lfs, and submission failed. It shows

Checksum does not match:

I google it , Lots of people tell the error occurred by using the wrong file.
I can run my model on GCP. So I think it is just occurred by the git lfs.

I google it, use the

git config http.postBuffer 52428800
git config -l

not useful.And I can’t find any place to change the limit.
There is someone can help me solve this problem?

Evalutation error : Unity environment took too long to respond

Over 1 year ago

Finally, When I uninstalled the CUDA 10.0 and installed the 9.0. Problem solved.

Evalutation error : Unity environment took too long to respond

Over 1 year ago

GCP tensorflow-gpu==1.13.0 gpu nvidia p100 still have same problem.

Evalutation error : Unity environment took too long to respond

Over 1 year ago

hi,I have same problem.

and I use the AWS.ec2.

UnityTimeOutException Traceback (most recent call last)
in ()
----> 1 env = ObstacleTowerEnv(’/home/ubuntu/ObstacleTower/obstacletower’, retro=True)

~/anaconda3/lib/python3.6/site-packages/obstacle_tower_env.py in init(self, environment_filename, docker_training, worker_id, retro, timeout_wait, realtime_mode)

~/anaconda3/lib/python3.6/site-packages/mlagents_envs/environment.py in init(self, file_name, worker_id, base_port, seed, docker_training, no_graphics, timeout_wait)
67 )
68 try:
—> 69 aca_params = self.send_academy_parameters(rl_init_parameters_in)
70 except UnityTimeOutException:
71 self._close()

~/anaconda3/lib/python3.6/site-packages/mlagents_envs/environment.py in send_academy_parameters(self, init_parameters)
489 inputs = UnityInput()
490 inputs.rl_initialization_input.CopyFrom(init_parameters)
–> 491 return self.communicator.initialize(inputs).rl_initialization_output
492
493 def wrap_unity_input(self, rl_input: UnityRLInput) -> UnityOutput:

~/anaconda3/lib/python3.6/site-packages/mlagents_envs/rpc_communicator.py in initialize(self, inputs)
78 if not self.unity_to_external.parent_conn.poll(self.timeout_wait):
79 raise UnityTimeOutException(
—> 80 “The Unity environment took too long to respond. Make sure that :\n”
81 “\t The environment does not need user interaction to launch\n”
82 “\t The Academy and the External Brain(s) are attached to objects in the Scene\n”

UnityTimeOutException: The Unity environment took too long to respond. Make sure that :
The environment does not need user interaction to launch
The Academy and the External Brain(s) are attached to objects in the Scene
The environment and the Python interface have compatible versions.

Petero has not provided any information yet.