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#include <stdio.h>
#include <stdlib.h>
#include <locale.h>
#include "strings.h"

typedef struct
{
	char rua[100];
  char complemento[100];
	char cidade[100];

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#include <stdio.h>
#include <stdlib.h>
#include <locale.h>
#include "strings.h"

typedef struct
{
	char rua[100];
  char complemento[100];
	char cidade[100];

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace ECP_13_03_17
{
    class Program
    {

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace BSI_POO_03_03_17
{
    class Program
    {

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<connectionStrings> <add name="DefaultConnection" connectionString="Data Source=(LocalDB)\MSSQLocalDB; AttachDbFilename=|DataDirectory|\Database.mdf;Integrated Security=True" providerName="System.Data.SqlClient" /> </connectionStrings>

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<connectionStrings>
	<add name="DefaultConnection" connectionString="Data Source=(LocalDB)\v11.0;AttachDbFilename=|DataDirectory|\Database.mdf;Integrated Security=True" providerName="System.Data.SqlClient" />
</connectionStrings>

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from twisted.internet.protocol import Factory, Protocol
from twisted.internet import reactor

class IphoneChat(Protocol):
    def connectionMade(self):
        self.factory.clients.append(self)
        print "clients are ", self.factory.clients

    def connectionLost(self, reason):
        self.factory.clients.remove(self)

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"""
A deep neural network with or w/o dropout in one file.
"""

import numpy, theano, sys, math
from theano import tensor as T
from theano import shared
from theano.tensor.shared_randomstreams import RandomStreams
from collections import OrderedDict

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//at CustomKlass.h add this:

+ (instancetype)myCustomInit:(NSString *)myCustomParam;

//at CustomKlass.m

+ (instancetype)myCustomInit:(NSString *)myCustomParam
{
	CustomKlass* returnValue = NULL;
	if (reachability != NULL)

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lua build_release_macosx.lua
default target: build
-- reading package ann/ann
-- reading package ann/autoencoders
-- reading package ann/fnnlm
-- reading package ann/loss
-- reading package ann/optimizer
-- reading package autodiff/ann
-- reading package autodiff/autodiff
-- reading package basics/AffineTransform2D