Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano

Overview

Please read the blog post that goes with this code!

Jupyter Notebook Setup

System Requirements:

To start the Jupyter Notebook:

# Clone the repo
git clone https://github.com/dennybritz/rnn-tutorial-rnnlm
cd rnn-tutorial-rnnlm

# Create a new virtual environment (optional, but recommended)
virtualenv venv
source venv/bin/activate

# Install requirements
pip install -r requirements.txt
# Start the notebook server
jupyter notebook

Setting up a CUDA-enabled GPU instance on EC2:

# Install build tools
sudo apt-get update
sudo apt-get install -y build-essential git python-pip libfreetype6-dev libxft-dev libncurses-dev libopenblas-dev  gfortran python-matplotlib libblas-dev liblapack-dev libatlas-base-dev python-dev python-pydot linux-headers-generic linux-image-extra-virtual
sudo pip install -U pip

# Install CUDA 7
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1410/x86_64/cuda-repo-ubuntu1410_7.0-28_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1410_7.0-28_amd64.deb
sudo apt-get update
sudo apt-get install -y cuda
sudo reboot

# Clone the repo and install requirements
git clone [email protected]:dennybritz/nn-theano.git
cd nn-theano
sudo pip install -r requirements.txt

# Set Environment variables
export CUDA_ROOT=/usr/local/cuda-7.0
export PATH=$PATH:$CUDA_ROOT/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_ROOT/lib64
export THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32
# For profiling only
export CUDA_LAUNCH_BLOCKING=1

# Startup jupyter noteboook
jupyter notebook

To start a public notebook server that is accessible over the network you can follow the official instructions.

Owner
Denny Britz
High-school dropout. Ex Google Brain, Stanford, Berkeley. Into Startups, Deep Learning. Writing at wildml.com and dennybritz.com. Lived in 日本 and 한국
Denny Britz
(NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductive few-shot classification"

SSR (NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductivefew-shot classification" [Paper] [Project webpage]

xshen 29 Dec 06, 2022
Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation (RA-L/ICRA 2020)

Aerial Depth Completion This work is described in the letter "Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation", by Lucas

ETHZ V4RL 70 Dec 22, 2022
Joint deep network for feature line detection and description

SOLD² - Self-supervised Occlusion-aware Line Description and Detection This repository contains the implementation of the paper: SOLD² : Self-supervis

Computer Vision and Geometry Lab 427 Dec 27, 2022
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)

Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.

Erick Cobos 73 Dec 04, 2022
QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing

QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing Environment Tested on Ubuntu 14.04 64bit and 16.04 64bit Installation # disabl

gts3.org (<a href=[email protected])"> 581 Dec 30, 2022
The repository for freeCodeCamp's YouTube course, Algorithmic Trading in Python

Algorithmic Trading in Python This repository Course Outline Section 1: Algorithmic Trading Fundamentals What is Algorithmic Trading? The Differences

Nick McCullum 1.8k Jan 02, 2023
PASSL包含 SimCLR,MoCo,BYOL,CLIP等基于对比学习的图像自监督算法以及 Vision-Transformer,Swin-Transformer,BEiT,CVT,T2T,MLP_Mixer等视觉Transformer算法

PASSL Introduction PASSL is a Paddle based vision library for state-of-the-art Self-Supervised Learning research with PaddlePaddle. PASSL aims to acce

186 Dec 29, 2022
novel deep learning research works with PaddlePaddle

Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa

1.5k Dec 29, 2022
🛠️ SLAMcore SLAM Utilities

slamcore_utils Description This repo contains the slamcore-setup-dataset script. It can be used for installing a sample dataset for offline testing an

SLAMcore 7 Aug 04, 2022
Let's Git - Versionsverwaltung & Open Source Hausaufgabe

Let's Git - Versionsverwaltung & Open Source Hausaufgabe Herzlich Willkommen zu dieser Hausaufgabe für unseren MOOC: Let's Git! Wir hoffen, dass Du vi

1 Dec 13, 2021
A generalist algorithm for cell and nucleus segmentation.

Cellpose | A generalist algorithm for cell and nucleus segmentation. Cellpose was written by Carsen Stringer and Marius Pachitariu. To learn about Cel

MouseLand 733 Dec 29, 2022
[3DV 2021] A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks

dispersion-score Official implementation of 3DV 2021 Paper A Dataset-dispersion Perspective on Reconstruction versus Recognition in Single-view 3D Rec

Yefan 7 May 28, 2022
LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021

LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021 We propose a cross encoder model (LTR_CrossEncoder) for information retrieval, re-retrie

Xuan Hieu Duong 7 Jan 12, 2022
Code for the paper titled "Prabhupadavani: A Code-mixed Speech Translation Data for 25 languages"

Prabhupadavani: A Code-mixed Speech Translation Data for 25 languages Code for the paper titled "Prabhupadavani: A Code-mixed Speech Translation Data

Ayush Daksh 12 Dec 01, 2022
Sound Source Localization for AI Grand Challenge 2021

Sound-Source-Localization Sound Source Localization study for AI Grand Challenge 2021 (sponsored by NC Soft Vision Lab) Preparation 1. Place the data-

sanghoon 19 Mar 29, 2022
Code for IntraQ, PyTorch implementation of our paper under review

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7

1 Nov 19, 2021
This repository contains the implementation of the paper: "Towards Frequency-Based Explanation for Robust CNN"

RobustFreqCNN About This repository contains the implementation of the paper "Towards Frequency-Based Explanation for Robust CNN" arxiv. It primarly d

Sarosij Bose 2 Jan 23, 2022
Collision risk estimation using stochastic motion models

collision_risk_estimation Collision risk estimation using stochastic motion models. This is a new approach, based on stochastic models, to predict the

Unmesh 7 Jun 26, 2022
Learning to trade under the reinforcement learning framework

Trading Using Q-Learning In this project, I will present an adaptive learning model to trade a single stock under the reinforcement learning framework

Uirá Caiado 470 Nov 28, 2022
The official start-up code for paper "FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark."

FFA-IR The official start-up code for paper "FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark." The framework is inheri

Mingjie 28 Dec 16, 2022