iamjanvijay

class Solution 
{
    void generateParenthesisUtil(vector<string> &ans, string &temp, int &half_len, int cur_len, int cur_sum)
    {
        if(cur_len==0)
        {
            if(cur_sum==0)
                ans.push_back(temp);
            return;
        }

iamjanvijay

import numpy as np 
import math

def sigmoid(x):
  return 1. / (1. + np.exp(-x))

kernel = np.load('weights.npy')
m_prev = np.load('h.npy')
c_prev = np.load('c.npy')
out = np.load('out.npy')

iamjanvijay

// Class for forward propagation of LSTM with zoneout in CUDA

#include <stdio.h>
#include <cublas_v2.h>
#include <curand.h>

// Define some error checking macros.
#define cudaErrCheck(stat) { cudaErrCheck_((stat), __FILE__, __LINE__); }
void cudaErrCheck_(cudaError_t stat, const char *file, int line) {
   if (stat != cudaSuccess) {

iamjanvijay

from torch import nn as nn
import torch
import numpy as np

in_channels = 1
out_channels = 1
kernel_size = (3, 3)
input_feature_size = (1, 1, 2, 2) # BATCH, CHANNEL, INPUT_X, INPUT_Y

def flip_kernel(kernel):

iamjanvijay

from collections import OrderedDict
from torch import nn as nn
from torch.nn import functional as F
import torch
import numpy as np

in_channels = 1
out_channels = 1
kernel_size = (4, 9)
padding_size = (7, 4)

iamjanvijay

class Solution {
    string dig_to_char[8] = {"abc", "def", "ghi", "jkl", "mno", "pqrs", "tuv", "wxyz"}; 
    void backtrack(string &digits, int cur, string &temp, vector<string> &ans)
    {
        if(temp.length()==digits.length())
        {
            ans.push_back(temp);
            return;
        }
        for(int i=0; i < dig_to_char[digits[cur]-'2'].size(); i++)

iamjanvijay

vowels = [] # List of vowels.
consonants = [] # List of consonants.

def nsyl(word, lang):
	if lang == 'EN':
	    try:
	        syllable_counts = [len(list(y for y in x if y[-1].isdigit())) for x in d[word.lower()]]
	        # print("{} present in cmu_dict: {}".format(word, sum(syllable_counts) / float(len(syllable_counts))))
	        return sum(syllable_counts) / float(len(syllable_counts))
	    except KeyError:

iamjanvijay

from bs4 import BeautifulSoup

filename = 'quora_ques_ans.html'

html_doc = ""
with open(filename, 'r') as f:
	for line in f:
		html_doc += line

soup = BeautifulSoup(html_doc, 'html.parser')

iamjanvijay

    void dfs(vector<string> &ans, vector<vector<int>> &graph, int cur_node)
    {
        while(graph[cur_node].size())
        {
            int nxt_node = graph[cur_node][int(graph[cur_node].size())-1];
            graph[cur_node].pop_back();
            dfs(ans, graph, nxt_node);
        }
        ans.push_back(cur_node);
    }

iamjanvijay

	for f in fnames:
		# Read text from json and tokenize
		fpath = os.path.join(data_folder, f)
		text, sentences, lists, items, items1, items2, items3, items4 = read_json(fpath)
		tokenised_text = word_tokenize(text)

		# Additional splits to clean the dataset - mannual
		add_splits = {"Classe6":["Classe", "6"], "Class.The":["Class", ".", "The"], ".The":[".", "The"], ".Such":[".", "Such"], ".These":[".", "These"]}
		temp_tokenised_text = []
		for token in tokenised_text: