vernwalrahul

import networkx as nx 
import numpy as np
import argparse

def remove_one_edge(G, src, goal):
	threshold = 10
	Edge_Count = {}
	pass

vernwalrahul

 source: https://www.cs.toronto.edu/~hinton/absps/JMLRdropout.pdfcross_entropy = tf.reduce_mean(
    tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y_conv))
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
correct_prediction = tf.equal(tf.argmax(y_conv, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))

with tf.Session() as sess:
  sess.run(tf.global_variables_initializer())
  for i in range(20000):
    batch = mnist.train.next_batch(50)

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W_conv2 = weight_variable([5, 5, 32, 64])
b_conv2 = bias_variable([64])
h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2)
h_pool2 = max_pool_2x2(h_conv2)
W_fc1 = weight_variable([7 * 7 * 64, 1024])
b_fc1 = bias_variable([1024])
h_pool2_flat = tf.reshape(h_pool2, [-1, 7*7*64])
h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1)
keep_prob = tf.placeholder(tf.float32)
h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob)

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x = tf.placeholder(tf.float32, shape=[None, 784])
y_ = tf.placeholder(tf.float32, shape=[None, 10])
W_conv1 = weight_variable([5, 5, 1, 32])
b_conv1 = bias_variable([32])
x_image = tf.reshape(x, [-1, 28, 28, 1])
h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1)
h_pool1 = max_pool_2x2(h_conv1)

vernwalrahul

from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
import numpy as np
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

def weight_variable(shape):
  initial = tf.truncated_normal(shape, stddev=0.1)
  return tf.Variable(initial)

def bias_variable(shape):

vernwalrahul

import argparse
import json
import logging
import os
import sqlite3
import sys
from base64 import b64decode
from ctypes import c_uint, c_void_p, c_char_p, cast, byref, string_at

vernwalrahul

import smtplib
import socks

fromaddr = input('sender email: ')
toaddrs  = input('receiver email: ')
msg = input('message')
username = input('your email: ')
password = input('your password: ')

server = smtplib.SMTP('smtp.gmail.com:587')

vernwalrahul

// Buoy_task.cpp : Defines the entry point for the console application.
//

#include "stdafx.h"
#include<opencv2/opencv.hpp>
#include<stdio.h>
#include<iostream>

using namespace std;
using namespace cv;

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// Marker Task.cpp : Defines the entry point for the console application.

#include "stdafx.h"
#include<opencv2\opencv.hpp>
#include<stdio.h>
#include<iostream>

using namespace std;
using  namespace cv;