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#include<iostream> | |
#include<cstdlib> | |
#include<cmath> | |
#include<time.h> | |
using namespace std; | |
__global__ void matrixVectorMultiplication(int *a, int *b, int *c, int n) | |
{ | |
int row=threadIdx.x+blockDim.x*blockIdx.x; |
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#include<iostream> | |
#include<cstdlib> | |
#include<cmath> | |
using namespace std; | |
//Matrix multiplication Cuda | |
__global__ void matrixMultiplication(int *a, int *b, int *c, int n) | |
{ | |
int row=threadIdx.y+blockDim.y*blockIdx.y; | |
int col=threadIdx.x+blockDim.x*blockIdx.x; |
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#include<iostream> | |
#include<cstdlib> | |
using namespace std; | |
//VectorAdd parallel function | |
__global__ void vectorAdd(int *a, int *b, int *result, int n) | |
{ | |
int tid=threadIdx.x+blockIdx.x*blockDim.x; | |
if(tid<n) |
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%{ | |
#include "y.tab.h" //Contains Token Definiation | |
%} | |
%% | |
[\t ] ; //IGNORE WHITE SPACES | |
am|is|are|have|has|can|will|shall|eat|sing|go|goes { printf("VERB\t==>%s\n",yytext);return VERB;} | |
very|simply|gently { printf("VERB\t==>%s\n",yytext);return(ADVERB); } | |
and|or|also|so|but|if|then {printf("CONJUNCTION\t==>%s\n",yytext);return (CONJUNCTION);} | |
fast|good|honest {printf("ADJECTIVE\t==>%s\n",yytext);return (ADJECTIVE);} | |
I|he|she|we|they|you|this {printf("PRONOUN\t==>%s\n",yytext);return (PRONOUN);} |
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int a,b,c,d=10; |
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%{ | |
#include <stdio.h> | |
#include "y.tab.h" | |
%} | |
DIGIT [0-9] | |
REAL {DIGIT}+[.]{DIGIT}* | |
LETTER [A-Za-z] | |
ASSIGN = |
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vaibhav kumbhar | |
3434 | |
PICT |
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import nltk | |
nltk.download('indian') | |
nltk.download('punkt') |
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import java.io.DataInputStream; | |
import java.io.DataOutputStream; | |
import java.io.IOException; | |
import java.net.Socket; | |
import java.net.UnknownHostException; | |
import java.security.NoSuchAlgorithmException; | |
import java.security.SecureRandom; | |
import java.util.Base64; | |
import javax.crypto.*; |
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import sklearn | |
import numpy as np | |
import pandas as pd | |
buy = pd.read_csv('buys.csv') | |
from sklearn.model_selection import train_test_split | |
from sklearn.tree import DecisionTreeClassifier |