Fix environment setup

Flatland
#1

Hi,
I followed the first submission guide, but the command is missing.

(base)  user@notebook:~/test/neurips2020-flatland-starter-kit$ conda activate flatland-rl
(flatland-rl) user@notebook:~/test/neurips2020-flatland-starter-kit$ flatland-evaluator --tests ./scratch/test-envs/ --shuffle False
flatland-evaluator: command not found

(base) user@notebook:~/test/neurips2020-flatland-starter-kit$ conda activate flatland-rl
(flatland-rl) user@notebook:~/test/neurips2020-flatland-starter-kit$ redis-cli ping
PONG
(flatland-rl) user@notebook:~/test/neurips2020-flatland-starter-kit$ export AICROWD_TESTS_FOLDER=./scratch/test-envs/
(flatland-rl) user@notebook:~/test/neurips2020-flatland-starter-kit$ python run.py
Traceback (most recent call last):
  File "run.py", line 10, in <module>
    from flatland.core.env_observation_builder import DummyObservationBuilder
ModuleNotFoundError: No module named 'flatland'

What could be the problem?

#2

Hey @marko, it looks like Flatland is not correctly installed in your conda env.

What do you see if you run:

conda activate flatland-rl
pip list | grep flatland

Did you see any error messages after running the previous command, conda env create -f environment.yml?

#3 
(base) user@notebook:~/test/neurips2020-flatland-starter-kit$ conda env create -f environment.yml

CondaValueError: prefix already exists: /home/user/anaconda3/envs/flatland-rl

(base) user@notebook:~/test/neurips2020-flatland-starter-kit$ conda activate flatland-rl
(flatland-rl) user@notebook:~/test/neurips2020-flatland-starter-kit$ pip list | grep flatland
(flatland-rl) user@notebook:~/test/neurips2020-flatland-starter-kit$

flatland is not in pip list

Sorry, I installed it with pip install flatland-rl :wink:

#4

Did that fix it?

Otherwise, you need to reinstall the conda environment.

You first need to delete it:

conda info --envs # this will show you the paths of all your conda environments
rm -rf <path of flatland-rl env>

Then install it again:

conda env create -f environment.yml

Installing it afterward with pip can work too, but maybe some other requirements also failed to install the first time, so if you see more problems down the line it may be better to recreate it from scratch!

#5

Thanks, I think it works.

But the evaluator is messaging:

$ flatland-evaluator --tests ./scratch/test-envs/ --shuffle False
…
Evaluating Test_0/Level_0.pkl (0/28)
DEPRECATED - RailEnv arg: malfunction_and_process_data - use malfunction_generator
Percentage for test 0, level 0: 0.6
…

$ python run.py
/home/user/anaconda3/envs/flatland-rl/lib/python3.6/site-packages/torch/serialization.py:649: SourceChangeWarning: source code of class 'torch.nn.modules.linear.Linear' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.
  warnings.warn(msg, SourceChangeWarning)
DEPRECATED - RailEnv arg: malfunction_and_process_data - use malfunction_generator
Env Path :  ./scratch/test-envs/Test_0/Level_0.pkl
...

… and singe_agent training:

python reinforcement_learning/single_agent_training.py
…
home/user/anaconda3/envs/flatland-rl/lib/python3.6/site-packages/flatland/envs/rail_generators.py:781: UserWarning: Could not set all required cities!
“Could not set all required cities!”)
/home/user/anaconda3/envs/flatland-rl/lib/python3.6/site-packages/flatland/envs/rail_generators.py:703: UserWarning: [WARNING] Changing to Grid mode to place at least 2 cities.
warnings.warn("[WARNING] Changing to Grid mode to place at least 2 cities.")
…
Training 1 agents on 25x25 Episode 0 Average Score: -0.998 Dones: 0.00% Epsilon: 1.00 Action Probabilities: [0.19451372 0.19451372 0.19201995 0.18204489 0.23690773]
/home/user/anaconda3/envs/flatland-rl/lib/python3.6/site-packages/flatland/envs/rail_generators.py:781: UserWarning: Could not set all required cities!
“Could not set all required cities!”)
/home/user/anaconda3/envs/flatland-rl/lib/python3.6/site-packages/flatland/envs/rail_generators.py:703: UserWarning: [WARNING] Changing to Grid mode to place at least 2 cities.
warnings.warn("[WARNING] Changing to Grid mode to place at least 2 cities.")
Training 1 agents on 25x25 Episode 100 Average Score: -0.448 Dones: 78.00% Epsilon: 0.74 Action Probabilities: [0.20166263 0.2048007 0.20314909 0.20204801 0.18833957]
Training 1 agents on 25x25 Episode 200 Average Score: -0.322 Dones: 92.00% Epsilon: 0.55 Action Probabilities: [0.16372086 0.21758342 0.22398293 0.20844126 0.18627152]
Training 1 agents on 25x25 Episode 300 Average Score: -0.280 Dones: 94.00% Epsilon: 0.40 Action Probabilities: [0.14407814 0.21219257 0.22605965 0.19928484 0.21838479]
Training 1 agents on 25x25 Episode 400 Average Score: -0.260 Dones: 94.00% Epsilon: 0.30 Action Probabilities: [0.1091662 0.23197817 0.20431018 0.2002635 0.25428195]
Training 1 agents on 25x25 Episode 499 Average Score: -0.220 Dones: 96.00% Epsilon: 0.22 Action Probabilities: [0.10974794 0.2326567 0.17332144 0.21012715 0.27414678]

Maybe something is still misconfigured?
I had a learning curve output, but no behavior view.

#6

This looks good!

There’s no code to render the environment in single_agent_training.py to keep the code as simple as possible.

In the multiple agent training tutorial, we introduce the --render command-line flag which renders 1 episode in 100 in multi_agent_training.py, as well as utilities to save the trained policy.

After training a multi-agent policy, you can also render it in new environments using the evaluate_agent.py file with the --render flat.

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