barosl

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

int addi(int a, int b) {
    return a + b;
}

char *adds(char *a, char *b) {
    char *res = malloc(strlen(a) + strlen(b) + 1);

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

FrancesCoronel

Repository Title Goes Here

INSERT GRAPHIC HERE (include hyperlink in image)

Subtitle or Short Description Goes Here

ideally one sentence >

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

njbbaer

import time
import numpy as np
from numpy.fft import fft2, ifft2
from matplotlib import pyplot, animation


def fft_convolve2d(board, kernal):
    board_ft = fft2(board)
    kernal_ft = fft2(kernal)
    height, width = board_ft.shape

ericjang

def sample_gumbel(shape, eps=1e-20): 
  """Sample from Gumbel(0, 1)"""
  U = tf.random_uniform(shape,minval=0,maxval=1)
  return -tf.log(-tf.log(U + eps) + eps)

def gumbel_softmax_sample(logits, temperature): 
  """ Draw a sample from the Gumbel-Softmax distribution"""
  y = logits + sample_gumbel(tf.shape(logits))
  return tf.nn.softmax( y / temperature)

gluschenko

using UnityEngine;
using System.Collections;

public class IK : MonoBehaviour {
	
	public Vector3 Target = new Vector3(-8, 0, 0);
	public Vector3 BendTarget = new Vector3(-4, 0, 3);
	public float Transition = 1f;
	
	public GameObject[] Members = new GameObject[3];

victor-shepardson

from contextlib import contextmanager
import numpy as np
import torch
from torch import Tensor, ByteTensor
import torch.nn.functional as F
from torch.autograd import Variable
import pycuda.driver
from pycuda.gl import graphics_map_flags
from glumpy import app, gloo, gl

abridgland

atabakd

# https://mail.python.org/pipermail/scipy-user/2011-May/029521.html

import numpy as np

def KLdivergence(x, y):
  """Compute the Kullback-Leibler divergence between two multivariate samples.

  Parameters
  ----------
  x : 2D array (n,d)