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@smsong @spMohanty @kidzik
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import opensim as osim
from osim.http.client import Client
import numpy as np
# Settings
remote_base = "http://osim-rl-grader.aicrowd.com/"
aicrowd_token = "a66245c8324e2d37b92f098a57ef3f99" # use your aicrowd token
# your aicrowd token (API KEY) can be found at your prorfile page at https://www.aicrowd.com
client = Client(remote_base)
# Create environment
observation = client.env_create(aicrowd_token, env_id='L2M2019Env')
# IMPLEMENTATION OF YOUR CONTROLLER
# my_controller = ... (for example the one trained in keras_rl)
while True:
#action = my_controller.update(observation)
action = [.5]*22
[observation, reward, done, info] = client.env_step(action)
print(observation)
if done:
observation = client.env_reset()
if not observation:
break
client.submit()
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