JupyterNotebook - C/C++, Javascript, HTML, LaTex, Shell scripts in Jupyter Notebook Also run them on remote computer

Overview

JupyterNotebook

Read, write and execute C, C++, Javascript, Shell scripts, HTML, LaTex in jupyter notebook, And also execute them on remote computer

Open In Colab

Requirements

Files

Run code on remote computer

In order to run our code from local computer to remote computer we need to use ssh.
As we, have a jupyter lab/notebook is running we can simply use ssh local port forwoarding to tunnel our ipython files with kernel that we are running.

  • 1st we have to run ipython kernel in terminal
%  ipython kernel 
NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.

To exit, you will have to explicitly quit this process, by either sending
"quit" from a client, or using Ctrl-\ in UNIX-like environments.

To read more about this, see https://github.com/ipython/ipython/issues/2049


To connect another client to this kernel, use:
    --existing kernel-1839.json

As we get kernel-wxyz.json. we have to read it so we can get which port our jupyter is running.

  • For getting kernel-wxyz.json we can run jupyter --runtime --dir

*Remember in order to execute bash command in Jupyter notebook you have to add "!" before your command.

e.g. !jupyter --runtime --dir

%   jupyter --runtime --dir
/Users/mithunparab/Library/Jupyter/runtime
 %  cd /Users/mithunparab/Library/Jupyter/runtime
 %  ls
.
.
kernel-1839.json
.
.
.
 %  cat kernel-1839.json
{
  "shell_port": 50170,
  "iopub_port": 50174,
  "stdin_port": 50171,
  "control_port": 50172,
  "hb_port": 50176,
  "ip": "127.0.0.1",
  "key": "6a45fe25-2wegc5erw3uro4fw8rw3",
  "transport": "tcp",
  "signature_scheme": "hmac-sha256",
  "kernel_name": ""
}                    
  • After we get the ports, we can do local ssh port forwording

Note: Try to use key based authentication for ssh for security and avoid repeatability of password.

% ssh [email protected] -f -N -L 50170:127.0.0.1:50170
% ssh [email protected] -f -N -L 50174:127.0.0.1:50174
% ssh [email protected] -f -N -L 50171:127.0.0.1:50171
% ssh [email protected] -f -N -L 50172:127.0.0.1:50172
  • copy kernel-wxyz.json to remote computer
% rsync -av [email protected]:.ipython/profile_default/security/kernel-1839.json ~/.ipython/profile_default/security/kernel-1839.json
  • That's it now you can start ipkernel on your remote computer with aboved kernel
% ipython3 console --existing kernel-1839.json

Note:

In Jupyter notebook, LaTex syntax can be execucate using magic tag %%latex
In order to convert yout LaTex to PDF you need to install nbconvert and follow this link for using latex tool of your choice
%%latex supports in Jupyter Notebook but may not work in Google colab

Image-Adaptive YOLO for Object Detection in Adverse Weather Conditions

Image-Adaptive YOLO for Object Detection in Adverse Weather Conditions Accepted by AAAI 2022 [arxiv] Wenyu Liu, Gaofeng Ren, Runsheng Yu, Shi Guo, Jia

liuwenyu 245 Dec 16, 2022
TabNet for fastai

TabNet for fastai This is an adaptation of TabNet (Attention-based network for tabular data) for fastai (=2.0) library. The original paper https://ar

Mikhail Grankin 116 Oct 21, 2022
Script utilizando OpenCV e modelo Machine Learning para detectar o uso de máscaras.

Reconhecendo máscaras Este repositório contém um script em Python3 que reconhece se um rosto está ou não portando uma máscara! O código utiliza da bib

Maria Eduarda de Azevedo Silva 168 Oct 20, 2022
Implementation of the Transformer variant proposed in "Transformer Quality in Linear Time"

FLASH - Pytorch Implementation of the Transformer variant proposed in the paper Transformer Quality in Linear Time Install $ pip install FLASH-pytorch

Phil Wang 209 Dec 28, 2022
This repo is to be freely used by ML devs to check the GAN performances without coding from scratch.

GANs for Fun Created because I can! GOAL The goal of this repo is to be freely used by ML devs to check the GAN performances without coding from scrat

Sagnik Roy 13 Jan 26, 2022
Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition"

CLIPstyler Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition" Environment Pytorch 1.7.1, Python 3.6 $ c

203 Dec 30, 2022
scAR (single-cell Ambient Remover) is a package for data denoising in single-cell omics.

scAR scAR (single cell Ambient Remover) is a package for denoising multiple single cell omics data. It can be used for multiple tasks, such as, sgRNA

19 Nov 28, 2022
Unofficial implementation of the paper: PonderNet: Learning to Ponder in TensorFlow

PonderNet-TensorFlow This is an Unofficial Implementation of the paper: PonderNet: Learning to Ponder in TensorFlow. Official PyTorch Implementation:

1 Oct 23, 2022
Cross-Modal Contrastive Learning for Text-to-Image Generation

Cross-Modal Contrastive Learning for Text-to-Image Generation This repository hosts the open source JAX implementation of XMC-GAN. Setup instructions

Google Research 94 Nov 12, 2022
ByteTrack: Multi-Object Tracking by Associating Every Detection Box

ByteTrack ByteTrack is a simple, fast and strong multi-object tracker. ByteTrack: Multi-Object Tracking by Associating Every Detection Box Yifu Zhang,

Yifu Zhang 2.9k Jan 04, 2023
Exploiting a Zoo of Checkpoints for Unseen Tasks

Exploiting a Zoo of Checkpoints for Unseen Tasks This repo includes code to reproduce all results in the above Neurips paper, authored by Jiaji Huang,

Baidu Research 8 Sep 06, 2022
Implements a fake news detection program using classifiers.

Fake news detection Implements a fake news detection program using classifiers for Data Mining course at UoA. Description The project is the categoriz

Apostolos Karvelas 1 Jan 09, 2022
A multi-mode modulator for multi-domain few-shot classification (ICCV)

A multi-mode modulator for multi-domain few-shot classification (ICCV)

Yanbin Liu 8 Apr 28, 2022
Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

bottom-up-attention This code implements a bottom-up attention model, based on multi-gpu training of Faster R-CNN with ResNet-101, using object and at

Peter Anderson 1.3k Jan 09, 2023
A PyTorch Implementation of PGL-SUM from "Combining Global and Local Attention with Positional Encoding for Video Summarization", Proc. IEEE ISM 2021

PGL-SUM: Combining Global and Local Attention with Positional Encoding for Video Summarization PyTorch Implementation of PGL-SUM From "PGL-SUM: Combin

Evlampios Apostolidis 35 Dec 22, 2022
GPOEO is a micro-intrusive GPU online energy optimization framework for iterative applications

GPOEO GPOEO is a micro-intrusive GPU online energy optimization framework for iterative applications. We also implement ODPP [1] as a comparison. [1]

瑞雪轻飏 8 Sep 10, 2022
State-of-the-art language models can match human performance on many tasks

Status: Archive (code is provided as-is, no updates expected) Grade School Math [Blog Post] [Paper] State-of-the-art language models can match human p

OpenAI 259 Jan 08, 2023
机器学习、深度学习、自然语言处理等人工智能基础知识总结。

说明 机器学习、深度学习、自然语言处理基础知识总结。 目前主要参考李航老师的《统计学习方法》一书,也有一些内容例如XGBoost、聚类、深度学习相关内容、NLP相关内容等是书中未提及的。

Peter 445 Dec 12, 2022
A library for building and serving multi-node distributed faiss indices.

About Distributed faiss index service. A lightweight library that lets you work with FAISS indexes which don't fit into a single server memory. It fol

Meta Research 170 Dec 30, 2022
PERIN is Permutation-Invariant Semantic Parser developed for MRP 2020

PERIN: Permutation-invariant Semantic Parsing David Samuel & Milan Straka Charles University Faculty of Mathematics and Physics Institute of Formal an

ÚFAL 40 Jan 04, 2023