Enis Berk Çoban EnisBerk

## colab_ssh.py
import random, string, urllib.request, json, getpass

#Generate root password
password = ''.join(random.choice(string.ascii_letters + string.digits) for i in range(20))

#Download ngrok
! wget -q -c -nc https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
! unzip -qq -n ngrok-stable-linux-amd64.zip

#Setup sshd

## alaska_results_v0.1.rtf
Raw embeddings and merged by Average
Tag             Songbird    Water Bird    Insect    Running Water    Rain    Cable    Wind    Vehicle    Aircraft
------------  ----------  ------------  --------  ---------------  ------  -------  ------  ---------  ----------
N. Neighbors        0.72          0.53      0.53             0.71    0.82     0.8     0.91         -1       0.5
Linear SVM          0.89          0.75      0.74             0.91    0.82     0.84    0.87         -1       0.059
RBF SVM             0.83          0.67      0.48             0.74    0.81     0.84    0.9          -1       0.87
Gaussian P.         0.87          0.65      0.72             0.94    0.8      0.91    0.91         -1       0.77
Decision T.         0.7           0.57      0.58             0.85    0.64     0.8     0.76         -1       0.5
Random F.           0.74          0.62      0.67             0.68    0.86     0.75    0.86         -1       0.34
NN                  0.88          0.72      0.7              0.94    0.82     0.9

## results.txt

Average of 10 second, raw embeddings:

Tag              N. Neighbors    Linear SVM    RBF SVM    Gaussian P.    Decision T.    Random F.    NN    AdaBoost    Naive B.     QDA
-------------  --------------  ------------  ---------  -------------  -------------  -----------  ----  ----------  ----------  ------
Songbird                 0.7           0.62       0.72       **0.74**           0.65         0.63  0.73        0.73        0.53    0.66
Water Bird               0.88          0.88       0.88           0.89           0.8          0.88**0.89**      0.87        0.4     0.88
Insect                   0.81          0.84       0.89           0.87           0.8          0.85  0.87        0.88        0.44    0.84
Running Water            0.94          0.92       0.91           0.93           0.92         0.92  0.93        0.88        0.56    0.91
Rain                     0.97          0.98       0.98           0.98           0.97         0.98  0.98        0.97        0.71    0.98

## tensor2tesnor.ipynb

      
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                EnisBerk
                / tensor2tesnor.ipynb
            
            
              Created Aug 17, 2019
            
              
                tensor2tesnor tests
              
          
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## model.py
import torch
import torch.nn as nn
import math
import torch.nn.functional as F
import torch.optim as optim
from torch.autograd import Variable

def init_bn(bn):
    bn.weight.data.fill_(1.)


## tf_to_pytorch_vggish_model.py
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F

__weights_dict = dict()

def load_weights(weight_file):
    if weight_file == None:
        return

## test.py

import os
import torch
import torch.distributed as dist
from torch.multiprocessing import Process
import argparse
import socket
import time
import requests

## run.py
"""run.py:"""
#!/usr/bin/env python
import os
import torch
import torch.distributed as dist
from torch.multiprocessing import Process


def run(rank, size):
    # tensor = torch.zeros(1)

## saxpy.cu
#include<time.h>
#include <stdio.h>
cudaEvent_t start, stop;
float time2;
float total_time=0;

__global__
void saxpy(int n, float a, float *x, float *y)
{

## index.html
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="utf-8">
    <title>D3: Setting path fills</title>
    <script src="http://d3js.org/d3.v3.min.js"></script>
    <script src="http://d3js.org/topojson.v1.min.js"></script>
    <style type="text/css">
        /* No style rules here yet */
    </style>