andrewliao11

# modified from https://gist.github.com/sorenbouma/6502fbf55ecdf988aa247ef7f60a9546
import gym
import numpy as np
import matplotlib.pyplot as plt

env = gym.make('CartPole-v0')
env.render(close=True)
#vector of means(mu) and standard dev(sigma) for each paramater
mu=np.random.uniform(size=env.observation_space.shape)
sigma=np.random.uniform(low=0.001,size=env.observation_space.shape)

kkweon

import numpy as np
import gym
import random

from collections import deque
from keras.layers import Input, Activation, Dense, Flatten, RepeatVector, Reshape
from keras.layers.convolutional import Conv2D
from keras.models import Model
from keras import backend as K

ZWMiller

try:
    import pyaudio
    import numpy as np
    import pylab
    import matplotlib.pyplot as plt
    from scipy.io import wavfile
    import time
    import sys
    import seaborn as sns
except:

namoshizun

"""
Implement a very simple gaussian process for regression task.
Credit : http://katbailey.github.io/post/gaussian-processes-for-dummies/
"""

import numpy as np
import matplotlib.pyplot as pl


def prepare_data(n, fn):

zakkak

# [<tag>] (If applied, this commit will...) <subject> (Max 72 char)
# |<----   Preferably using up to 50 chars   --->|<------------------->|
# Example:
# [feat] Implement automated commit messages

# (Optional) Explain why this change is being made
# |<----   Try To Limit Each Line to a Maximum Of 72 Characters   ---->|

# (Optional) Provide links or keys to any relevant tickets, articles or other resources
# Example: Github issue #23

gustavohenrique

import sys
import base64
from Crypto.Cipher import AES


class AESCipher(object):
    def __init__(self, key):
        self.bs = 16
        self.cipher = AES.new(key, AES.MODE_ECB)

kyamagu

shreydesai

import torch
import torch.nn as nn
import numpy as np

class DotProductAttention(nn.Module):
    
    def __init__(self, query_dim, key_dim, value_dim):
        super().__init__()
        
        self.scale = 1.0/np.sqrt(query_dim)

zigmoo

Screen Quick Reference

Wait a minute, why would anyone use 'screen', and what is it anyway?

Well, because it's both AWESOME and FUN!!

It lets you keep your own session running on all the servers you already use, and chances are, it's probably already installed and waiting for you! (since 1987!)

Basic

| Description | Command |

Rowing0914

import numpy as np
from autograd import grad
import matplotlib.pyplot as plt


def f(x):
    return x ** 3

def f_first(x):
    return 3 * x ** 2