Nov05

Udacity Deep Reinforcement Learning - p2 & deeprl env setup

👉 check the drlnd_py310 env setup notes
👉 check the p1 env setup notes
👉 course curriculum
👉 Colab notebooks

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Nov05

👉 Udacity Deep Reinforcement Learning Python Environment Setup

⚠️ Python 3.11 has to be downgraded to Python 3.10, or Multiprocessing will cause TypeError: code() argument 13 must be str, not int in both Windows and Linux. Google Colab is currently using Python 3.10 as well.

• Windows 11 (64-bit), VSCode, Powershell, Miniconda3, Python 3.10
• repo: https://github.com/Nov05/udacity-deep-reinforcement-learning
• working dir: D:\github\ udacity-deep-reinforcement-learning\python
• package deeprl is copied and modified from https://github.com/ShangtongZhang/DeepRL/tree/master/ deep_rl into .\python.

Nov05

"deeprl/agent/DDPG_agent.py"

• trg = trg*(1-τ) + src*τ
• τ is stored in self.config.target_network_mix

    def soft_update(self, target, source):
        ## trg = trg*(1-τ) + src*τ
        ## τ is stored in self.config.target_network_mix
        for target_param, source_param in zip(target.parameters(), source.parameters()):
 target_param.detach_()

Nov05

Udacity Deep Reinforcement Learning - p1 env setup

👉 for the course projcts, Unity MLAgents - Banana Collector, etc.
👉 go to the Banana and VisualBanana notebooks
👉 go to the course repo
👉 check course curriculum

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Window 11, VSCode, Minicoda, Powershell

Nov05

(drlnd_p2) PS D:\github\udacity-deep-reinforcement-learning\python\mujoco-py> python examples\body_interaction.py

You appear to be missing MuJoCo.  We expected to find the file here: C:\Users\*\.mujoco\mujoco210

This package only provides python bindings, the library must be installed separately.

Please follow the instructions on the README to install MuJoCo

Nov05

⚠️ issue: from gym.wrappers import Monitor caused ImportError: cannot import name 'Monitor' from 'gym.wrappers'.

• solution (2022'):

  from gym.wrappers.record_video import RecordVideo
  env = gym.make('CartPole-v1', render_mode="rgb_array")
  env = RecordVideo(env, './video',  episode_trigger = lambda episode_number: True)
  env.reset()
  

Nov05

20240218_pong-PPO.ipynb
👉 training log for reference
1000 episodes, T4 GPU, Wall time: 1h 38min 14s

Episode: 20, score: -15.750000
[-16. -16. -16. -16. -16. -16. -16. -14.]
Episode: 40, score: -12.625000

Nov05

20240217_pong_REINFORCE.ipynb
👉 training log for reference
1200 episodes on T4 GPU, Wall time: 2h 12min 12s

Episode: 20, score: -14.500000
[-14. -15. -16. -13. -14. -16. -16. -12.]
Episode: 40, score: -14.500000

Nov05

20240217_pong_REINFORCE.ipynb
👉 training log for reference
800 episodes on T4 GPU, Wall time: 1h 17min 44s

Episode: 20, score: -14.000000
[-15. -17. -15. -14. -13. -13. -16.  -9.]

Nov05

Ankit404butfound/PyWhatKit#313

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
/usr/local/lib/python3.10/dist-packages/Xlib/support/unix_connect.py in get_socket(dname, host, dno)
     75             s = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
---> 76             s.connect('/tmp/.X11-unix/X%d' % dno)
     77     except OSError as val: