araffin

import gymnasium as gym
import numpy as np
from gymnasium.envs.mujoco.mujoco_env import MujocoEnv

# Env initialization
env = gym.make("HalfCheetah-v4", render_mode="human")
# Wrap to have reward statistics
env = gym.wrappers.RecordEpisodeStatistics(env)
mujoco_env = env.unwrapped
n_joints = 6

araffin

import gymnasium as gym
import numpy as np
from gymnasium.envs.mujoco.mujoco_env import MujocoEnv

# Env initialization
env = gym.make("Swimmer-v4", render_mode="human")
# Wrap to have reward statistics
env = gym.wrappers.RecordEpisodeStatistics(env)
mujoco_env = env.unwrapped
n_joints = 2

nmwsharp

Pretty print tables summarizing properties of tensor arrays in numpy, pytorch, jax, etc.

Now on pip! `pip install arrgh` https://github.com/nmwsharp/arrgh

qgallouedec

import urllib.request
from datetime import datetime

import wandb
import yaml
from yaml.loader import SafeLoader

atari_ids = [
    # "AdventureNoFrameskip-v4",
    # "AirRaidNoFrameskip-v4",

Starbuck5

import cv2
import pygame
import numpy
import functools

# WHAT IS THIS?
# This script is a simple ascii video player made in Python / pygame
# It allows you to drop in videos, or to use the webcam

pygame.init()

Miffyli

# A very useful script for giving credit where it is due: by replacing (most) variable names by the authors who wrote them.
# Requirements: pip install gitpython
# Usage: python3 assign-credits.py <input_file> <output_file>
# Example: python3 assign-credits.py ./src/main.py ./src/main-credited.py

# NOTE that this is an awful idea with an awful implementation. The "generated" code likely does not work
# (e.g. typing stuff is skipped, class attribute names are replaced). The "author" is decided by the current HEAD of git repo, and whoever
# defines the variable first will get the credits (hahaa dunno if even this is right).

# It is getting late and I am tired of typing so I will let Github Copilot write something for me.

mike10004

#!/usr/bin/python3

"""
WARNING: The code you are about to view is DISGUSTING

I wrote most of it months ago, so don't ask me what it's doing, or why.
"""

import struct
import sys

InnovArul

import torch, torch.nn as nn, torch.nn.functional as F
import numpy as np
import torch.optim as optim

# tied autoencoder using off the shelf nn modules
class TiedAutoEncoderOffTheShelf(nn.Module):
    def __init__(self, inp, out, weight):
        super().__init__()
        self.encoder = nn.Linear(inp, out, bias=False)
        self.decoder = nn.Linear(out, inp, bias=False)

fgolemo

How to install PyTorch v0.3.1 on RaspberryPi 3B

Prerequisites

Important I'd recommend you use at least a 16GB sd card. I tried it with an 8GB card and it baaaaarely fits. I had to uninstall a lot of packages and regularly clean up.

Go to https://www.raspberrypi.org/downloads/raspbian/ and download the Raspbian Stretch image (either one).

Use Etcher (from https://etcher.io/) to "burn" the image onto the SD card.

time-awareness.ipynb