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#include <iostream>
using namespace std;

struct Node {
  int val;
  Node *next;
};

void print(Node* n) {

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'''
Linear Regression From First Principles
Author: Gaurav Menghani (gaurav.menghani@gmail.com)
'''

import numpy as np
import matplotlib.pyplot as plt

def linear_sum(X, W, b):
    return X.dot(W) + b

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1. embeddings.js: word2vec in Javascript

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import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F
import torchvision.transforms as transforms
import matplotlib.pyplot as plt
import numpy as np
import torch.optim as optim

from torch.autograd import Variable

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import gym
import logging
import sys
import numpy as np
from gym import wrappers

import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F

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import gym
import logging
import sys
import numpy as np
from gym import wrappers

import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F

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import gym
import logging
import sys
import numpy as np
from gym import wrappers

import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F

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import os
import sys
import urllib2

def normalize_path(path):
    if path[-1] == '/':
        path = path[:-1]
    return path

def get_dir_name(path):

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import gym
import logging
import sys
import numpy as np
from gym import wrappers

SEED = 0
NUM_EPISODES = 3000

# Hyperparams

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import gym
import logging
import sys
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import cPickle as pickle
import os