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general.import = [ | |
# "~/.config/alacritty/catppuccin-latte.toml" | |
# "~/.config/alacritty/catppuccin-mocha.toml" | |
# "~/.config/alacritty/themes/themes/dracula.toml" | |
"~/.config/alacritty/tokyo-night-alacritty-theme/tokyo-night.toml" | |
] | |
terminal.shell="/opt/homebrew/bin/fish" | |
[env] |
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https://cdecl.org/ - get the meaning of complicated c code declarations. |
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#ifndef DP2__MATRIX_H | |
#define DP2__MATRIX_H | |
#include <algorithm> | |
#include <cstdio> | |
#include <memory> | |
#include <stdexcept> | |
template <typename T> | |
class Matrix { |
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#include <iostream> | |
#include <vector> | |
#include <string> | |
#include <cmath> | |
#include <tuple> | |
using namespace std; | |
//std::string greeting(const std::string &name="Mayukh") { | |
// return "Hello " + name; | |
//} |
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def sent2vec(sentence, model, method='tfidf', **kwargs): | |
""" | |
Generic function to convert a sentence to a vector using | |
avg or TFIDF vecorization | |
""" | |
##### It is recommended to pass seperate stopwords ##### | |
stopwords = kwargs.get('stopwords') | |
if stopwords is None: | |
from sklearn.feature_extraction.stop_words import ENGLISH_STOP_WORDS |
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package main | |
import ( | |
"encoding/csv" | |
"os" | |
"reflect" | |
"github.com/jinzhu/gorm" | |
_ "github.com/jinzhu/gorm/dialects/sqlite" | |
) |
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{ | |
"auto_complete_commit_on_tab": true, | |
"color_pick_upcase": true, | |
"color_scheme": "Packages/Enlightened Color Scheme/enlightened.tmTheme", | |
"dplus_bright_fonts": true, | |
"dplus_bright_status_bar": true, | |
"dplus_fat_tabs": false, | |
"file_exclude_patterns": | |
[ | |
"*.pyc", |
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""" | |
Common dummy data generation scripts | |
""" | |
from random import randint | |
from datetime import datetime as dt | |
from datetime import timedelta | |
start_times = [] | |
end_times = [] |
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cmake_minimum_required(VERSION 2.8.4) | |
project(test) | |
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11") | |
set(SOURCE_FILES main.cpp test.h test.cpp) | |
add_executable(test ${SOURCE_FILES}) |