MSWon

N = int(input())
input_num = input().split(" ")
input_num = [int(num) for num in input_num]

def change(result_list, num):
    for i in range(len(result_list)-1,-1,-1):
        if(result_list[i] > num):
            idx = i
        else:
            break

MSWon

import re

line = "I don't go to school--with  you ========== ------------ ........ *******"      
re.sub(r"(\W)\1+", r"\1" , line)

MSWon

import tensorflow as tf
import numpy as np


input_data = np.random.rand(10, 10, 64)
positions = [0,9,8,2,3,5,1,2,4,6]

input_tensor = tf.placeholder(shape = (None,10,64) , dtype = tf.float32)
positions_tensor = tf.placeholder(shape = (None,) , dtype = tf.int32)

MSWon

x = [1,2,3,4,5,6,7,8,9,10]

total_case = []

for i in x:
    first = [i]
    for j in x:
        c_first = list(first)
        if(i < j):
            c_first.append(j)

MSWon

import tensorflow as tf

max_seq_len = 6
seq_len  = [3,5,4]

row_vector = tf.range(0,max_seq_len,1)  ## [, max_seq_len]
matrix = tf.cast(tf.expand_dims(seq_len,-1), tf.int32) ## [batch_size, 1]

t = tf.cast(row_vector < matrix, tf.float32) ##  [batch_size, max_seq_len]
t = tf.expand_dims(t, -1) ##  [batch_size, max_seq_len, 1]

MSWon

# -*- coding: utf-8 -*-
"""
Created on Sat Apr  6 10:47:30 2019

@author: jbk48
"""

from keras.layers import Layer
import tensorflow as tf

MSWon

import tensorflow as tf

g = tf.Graph()
with g.as_default():
    a = tf.Variable(initial_value=[[1, 2, 4, 0],[2, 4, 5, 8]])
    b = tf.scatter_update(a, [0], [[0, 0, 0, 0]])

with tf.Session(graph=g) as sess:
   sess.run(tf.initialize_all_variables())
   print(sess.run(a))

MSWon

import numpy as np
import tensorflow as tf

batch_size = 3
max_seq_len = 5
dim = 4

input_data = tf.placeholder(shape = (None,max_seq_len,dim), dtype = tf.float32)
seq_len = tf.placeholder(shape = [None], dtype = tf.int32)

MSWon

import tensorflow as tf


# Constants (3-element arrays).
a = tf.constant([100, 200, 300])
b = tf.constant([1, 2, 3])

# Use placeholder for predicate to where.
# ... We pass in an array of 3 bools to fill the placeholder.
j = tf.placeholder(tf.bool, [3])

MSWon

import random

a = ['a', 'b', 'c']
b = [1, 2, 3]

c = list(zip(a, b))

random.shuffle(c)

a, b = zip(*c)