bamos

#!/usr/bin/env python3

import numpy as np
import gym
from baselines.common.vec_env.subproc_vec_env import SubprocVecEnv

env_name = 'Pendulum-v0'
nproc = 8
T = 10

pjessesco

# Reference : https://stackoverflow.com/a/59539843

from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtWidgets import *
from PyQt5.QtCore import QObject, pyqtSignal
import sys
import time
import threading

daleroberts

anastasiia-kornilova

import static java.lang.Math.*;

public class GaussSmooth {

    private static double gauss(double sigma, double x) {
        double expVal = -0.5 * (pow(x, 2) / pow(sigma, 2));
        return exp(expVal);
    }

    private static double[] gaussKernel1d(double sigma, int lw) {

rusty1s

import torch
import torch.nn.functional as F
from torchvision.datasets import MNIST
from torchvision.transforms import ToTensor
from torch.utils.data import DataLoader

from torch_geometric.utils import grid
from torch_geometric.nn import SplineConv

train_dataset = MNIST('/tmp/MNIST', train=True, transform=ToTensor())

arunavsk

import os.path as osp

import argparse
import torch
import torch.nn.functional as F
from torch_geometric.datasets import Planetoid
import torch_geometric.transforms as T
from torch_geometric.data import NeighborSampler
from torch_geometric.nn import GAE, SAGEConv
from torch_geometric.utils import train_test_split_edges

tehmas

import cv2
import cPickle
import socket
import struct

TCP_IP = '127.0.0.1'
TCP_PORT = 9501
server_address = (TCP_IP, TCP_PORT)
i = 0

andrewgiessel

import numpy as np

def makeGaussian(size, fwhm = 3, center=None):
    """ Make a square gaussian kernel.

    size is the length of a side of the square
    fwhm is full-width-half-maximum, which
    can be thought of as an effective radius.
    """

bsdnoobz

#!/usr/bin/env python

from PySide.QtCore import *
from PySide.QtGui import *
import cv2
import sys

class MainApp(QWidget):

    def __init__(self):

nirshlezinger1