<jupyter_start><jupyter_text>**Try to solve OpenAI Gym BipedalWalker-v2 by reinforcement-learning A3C**

in google colaboratory (CPU) **Install module of BipedalWalker version 2**<jupyter_code>!pip install torch==1.5.0 torchvision==0.6.0 torchaudio==0.5.0 setproctitle==1.1.10
!pip install box2d-py==2.3.5
!pip install 'gym[Box2D]'==0.10.11
!pip install pyglet==1.3.2<jupyter_output><empty_output><jupyter_text>**Clone source files**<jupyter_code>!git clone https://github.com/shun60s/BipedalWalker-a3c
cd BipedalWalker-a3c_continuous-clone/<jupyter_output><empty_output><jupyter_text>**Check file tree**<jupyter_code>!ls -l<jupyter_output><empty_output><jupyter_text>**train BipedalWalker-v2**

Stop manually to push stop button.<jupyter_code>!python main.py --workers 6 --env BipedalWalker-v2 --save-max True --model MLP --stack-frames 1 --gpu-ids -1<jupyter_output><empty_output><jupyter_text>Eval trained model.  Output mp4 file will be saved.<jupyter_code>!apt-get -qq -y install xvfb freeglut3-dev ffmpeg
!pip -q install pyglet
!pip -q install pyopengl
!pip -q install pyvirtualdisplay
!pip install pyyaml==3.12
# Start virtual display
from pyvirtualdisplay import Display
display = Display(visible=0, size=(1024, 768))
display.start()
import os
!python gym_eval.py --env BipedalWalker-v2 --num-episodes 100 --stack-frames 1 --model MLP --new-gym-eval True<jupyter_output><empty_output><jupyter_text>**Show output mp4 list**<jupyter_code>!ls BipedalWalker-v2_monitor/*.mp4<jupyter_output><empty_output><jupyter_text>**Load previous model file and train again !**<jupyter_code>!python main.py --workers 6 --env BipedalWalker-v2 --load True --save-max True --model MLP --stack-frames 1 --gpu-ids -1<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13482501434308664, 'fraction_numerical': 0.03614457831325301, 'mean_word_length': 5.8125, 'pattern_counts': {'":': 0, '<': 29, '<?xml version=': 0, '>': 29, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '7', 'dir': 'jupyter-structured-clean-dedup', 'id': '359995', 'license': 'Apache-2.0', 'n_tokens_mistral': 706, 'n_tokens_neox': 667, 'n_words': 143, 'path': 'BipedalWalker_v2_Colab.ipynb', 'repo_name': 'shun60s/BipedalWalker-a3c_continuous-clone', 'size': '1743'}