bananemure

"""
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)

bananemure

# Example for my blog post at:
# http://danijar.com/introduction-to-recurrent-networks-in-tensorflow/
import functools
import sets
import tensorflow as tf


def lazy_property(function):
    attribute = '_' + function.__name__

bananemure

spss2opal <- function (fi,fo) 
{
  A <- haven::read_sav(fi,user_na = TRUE)
  #--------------------------------all vars + labels
  vars <- names(A)
  vars_label <- sapply(A,function(x) {lbl <- attributes(x)[['label']]; ifelse(is.null(lbl),NA,lbl ) })
  opal_type <- sapply(A, function(x) 
                            { 
                              format <-  attributes(x)$format;  
                              if(grepl('F\\d\\.([1-9])',format)) return ('decimal')

bananemure

#!/bin/bash

openssl genrsa -out privatekey.pem 1024
openssl req -new -x509 -key privatekey.pem -out publickey.pem -days 1825
#openssl pkcs12 -export -out public_privatekey.pfx -inkey privatekey.pem -in publickey.pem