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#include <iostream>
#include <memory>

using Scalar = float;

class Node;

using NodePtr = std::shared_ptr<Node>;

class Node

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➜  pytorch_unique git:(master) sudo pip3 install torch-unique 
The directory '/home/daiver/.cache/pip/http' or its parent directory is not owned by the current user and the cache has been disabled. Please check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag.
The directory '/home/daiver/.cache/pip' or its parent directory is not owned by the current user and caching wheels has been disabled. check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag.
Collecting torch-unique
  Downloading https://files.pythonhosted.org/packages/ad/8c/3ea7b6242c9c6a30e812fe172b2ef631520c24184565b51b17ab2c3cbdab/torch_unique-1.0.1.tar.gz
Requirement already satisfied: numpy in /home/daiver/.local/lib/python3.6/site-packages (from torch-unique)
Installing collected packages: torch-unique
  Running setup.py install for torch-unique ... error
    Complete output from command /usr/bin/python3 -u -c "import setuptools, tokenize;__file

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package object graphviz {

  case class Attribute(key: String, value: String) {
    def render(): String = s"${key} = ${value}"
  }

  case class AttributePlaceholder(str: String){
    def := (other: AttributePlaceholder): Attribute = Attribute(str, other.str)
  }
  implicit def strToAttrPlaceholder(str: String):AttributePlaceholder = AttributePlaceholder(str)

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import cookielib
import urllib2
import json
from urllib import urlencode
from urlparse import urlparse
from HTMLParser import HTMLParser

import os
import pickle
import getpass

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#include <boost/fusion/tuple.hpp>
#include <boost/fusion/view.hpp>
#include <boost/fusion/algorithm.hpp>
#include <boost/fusion/adapted/struct/adapt_struct.hpp>
#include <boost/type_traits.hpp>
#include <boost/mpl/arg.hpp>
#include <boost/lambda/lambda.hpp>
#include <string>
#include <iostream>

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use std::collections::HashMap;

fn process_polish(funcs : &HashMap<&str, Box<(Fn(&mut Vec<f32>) -> f32)>>, token : &str, stack : &mut Vec<f32>)
{
    if funcs.contains_key(token) {
        let val = funcs[token](stack);
        stack.push(val);
    }else{
        let tmp = token.parse::<f32>();
        match tmp{

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public string IP_Parse(string str)
{
    const string error_str = "Input error. Invalid IP-address.";
    if (split == null)
        return error_str;
    string[] split = str.Split(new Char[] { '.' }, StringSplitOptions.RemoveEmptyEntries);
    if (split.Length != 4)
        return error_str; 

    for (int i = 0; i < split.Length; ++i)

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import numpy as np

with open('mat') as f:
    print np.array(
        [
            map(int, st.split(' '))
            for st in f
        ]
    )

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CXX = g++
#CXX = clang++
Options = -O3 -std=c++11
LIBS = 

main: main.cc hashtable.h test.o
	$(CXX) -o main main.cc test.o $(LIBS) $(Options)
	rm *.o

test.o: test.cpp

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pcl::PointCloud<pcl::PointXYZRGB>::Ptr getColored(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
{
  pcl::search::Search<pcl::PointXYZRGB>::Ptr tree = boost::shared_ptr<pcl::search::Search<pcl::PointXYZRGB> > (new pcl::search::KdTree<pcl::PointXYZRGB>);
  pcl::PointCloud <pcl::Normal>::Ptr normals (new pcl::PointCloud <pcl::Normal>);
  pcl::NormalEstimation<pcl::PointXYZRGB, pcl::Normal> normal_estimator;
  normal_estimator.setSearchMethod (tree);
  normal_estimator.setInputCloud (cloud);
  normal_estimator.setKSearch (50);
  normal_estimator.compute (*normals);