ferreirafabio

RL Packages and Implementations

This gist is an accumulation of high-quality implementations and packages useful for research in reinforcement learning.

TensorFlow

• Dopamine
• Atari Model Zoo
• Baselines
• SpinningUp
• TRFL

ferreirafabio

% Contributors: Jonas Rothfuss and Fabio Ferreira

import math
import os
import moviepy
import subprocess
import random
import glob
import multiprocessing
from moviepy.video.io.ffmpeg_tools import ffmpeg_extract_subclip

ferreirafabio

% contributors: Jonas Rothfuss and Fabio Ferreira

import itertools
import os
import subprocess
import glob

AVI_SOURCE_DIR = '/data/rothfuss/data/ArmarExperiences/videos/memory'
TARGET_DIR = '/data/rothfuss/data/ArmarExperiences/videos/memory_augmented'

ferreirafabio

from videofeatures import Pipeline, ActivityNetDataset, TwentyBNDataset, ResNetFeatures, SIFTFeatures, VGGFeatures, SURFFeatures
import configparser

_base_dir = "./output"
config = configparser.ConfigParser()
config.read('config.ini')

train_dir = config['GULP']['train_data_gulp']
valid_dir = config['GULP']['valid_data_gulp']