Sequence modeling benchmarks and temporal convolutional networks

Related tags

Deep LearningTCN
Overview

Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN)

This repository contains the experiments done in the work An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling by Shaojie Bai, J. Zico Kolter and Vladlen Koltun.

We specifically target a comprehensive set of tasks that have been repeatedly used to compare the effectiveness of different recurrent networks, and evaluate a simple, generic but powerful (purely) convolutional network on the recurrent nets' home turf.

Experiments are done in PyTorch. If you find this repository helpful, please cite our work:

@article{BaiTCN2018,
	author    = {Shaojie Bai and J. Zico Kolter and Vladlen Koltun},
	title     = {An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling},
	journal   = {arXiv:1803.01271},
	year      = {2018},
}

Domains and Datasets

Update: The code should be directly runnable with PyTorch v1.0.0 or above (PyTorch v>1.3.0 strongly recommended). The older versions of PyTorch are no longer supported.

This repository contains the benchmarks to the following tasks, with details explained in each sub-directory:

  • The Adding Problem with various T (we evaluated on T=200, 400, 600)
  • Copying Memory Task with various T (we evaluated on T=500, 1000, 2000)
  • Sequential MNIST digit classification
  • Permuted Sequential MNIST (based on Seq. MNIST, but more challenging)
  • JSB Chorales polyphonic music
  • Nottingham polyphonic music
  • PennTreebank [SMALL] word-level language modeling (LM)
  • Wikitext-103 [LARGE] word-level LM
  • LAMBADA [LARGE] word-level LM and textual understanding
  • PennTreebank [MEDIUM] char-level LM
  • text8 [LARGE] char-level LM

While some of the large datasets are not included in this repo, we use the observations package to download them, which can be easily installed using pip.

Usage

Each task is contained in its own directory, with the following structure:

[TASK_NAME] /
    data/
    [TASK_NAME]_test.py
    models.py
    utils.py

To run TCN model on the task, one only need to run [TASK_NAME]_test.py (e.g. add_test.py). To tune the hyperparameters, one can specify via argument options, which can been seen via the -h flag.

Owner
CMU Locus Lab
Zico Kolter's Research Group
CMU Locus Lab
Empirical Study of Transformers for Source Code & A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code

Transformers for variable misuse, function naming and code completion tasks The official PyTorch implementation of: Empirical Study of Transformers fo

Bayesian Methods Research Group 56 Nov 15, 2022
Reproduces ResNet-V3 with pytorch

ResNeXt.pytorch Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch. Tried on pytorch 1.6 Trains on Cifar

Pau Rodriguez 481 Dec 23, 2022
Human head pose estimation using Keras over TensorFlow.

RealHePoNet: a robust single-stage ConvNet for head pose estimation in the wild.

Rafael Berral Soler 71 Jan 05, 2023
Python scripts for performing stereo depth estimation using the HITNET Tensorflow model.

HITNET-Stereo-Depth-estimation Python scripts for performing stereo depth estimation using the HITNET Tensorflow model from Google Research. Stereo de

Ibai Gorordo 76 Jan 02, 2023
This repository contains a pytorch implementation of "HeadNeRF: A Real-time NeRF-based Parametric Head Model (CVPR 2022)".

HeadNeRF: A Real-time NeRF-based Parametric Head Model This repository contains a pytorch implementation of "HeadNeRF: A Real-time NeRF-based Parametr

294 Jan 01, 2023
A small fun project using python OpenCV, mediapipe, and pydirectinput

Here I tried a small fun project using python OpenCV, mediapipe, and pydirectinput. Here we can control moves car game when yellow color come to right box (press key 'd') left box (press key 'a') lef

Sameh Elisha 3 Nov 17, 2022
In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021

In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021. Balestriero et

Sean M. Hendryx 1 Jan 27, 2022
The aim of the game, as in the original one, is to find a specific image from a group of different images of a person's face

GUESS WHO Main Links: [Github] [App] Related Links: [CLIP] [Celeba] The aim of the game, as in the original one, is to find a specific image from a gr

Arnau - DIMAI 3 Jan 04, 2022
Code for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss"

PurNet Project for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss" Abstract Image-based salie

Jinming Su 4 Aug 25, 2022
A Simulated Optimal Intrusion Response Game

Optimal Intrusion Response An OpenAI Gym interface to a MDP/Markov Game model for optimal intrusion response of a realistic infrastructure simulated u

Kim Hammar 10 Dec 09, 2022
Pytorch implementation of few-shot semantic image synthesis

Few-shot Semantic Image Synthesis Using StyleGAN Prior Our method can synthesize photorealistic images from dense or sparse semantic annotations using

40 Sep 26, 2022
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.

ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We

haguettaz 12 Dec 10, 2022
Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation

tf-imle Tensorflow 2 and PyTorch implementation and Jupyter notebooks for Implicit Maximum Likelihood Estimation (I-MLE) proposed in the NeurIPS 2021

NEC Laboratories Europe 69 Dec 13, 2022
Open source hardware and software platform to build a small scale self driving car.

Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions.

Autorope 2.4k Jan 04, 2023
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale

XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf

Microsoft 125 Jan 04, 2023
Machine-in-the-Loop Rewriting for Creative Image Captioning

Machine-in-the-Loop Rewriting for Creative Image Captioning Data Annotated sources of data used in the paper: Data Source URL Mohammed et al. Link Gor

Vishakh P 6 Jul 24, 2022
Dataset para entrenamiento de yoloV3 para 4 clases

Deteccion de objetos en video Este repo basado en el proyecto PyTorch YOLOv3 para correr detección de objetos sobre video. Construí sobre este proyect

1 Nov 01, 2021
Lama-cleaner: Image inpainting tool powered by LaMa

Lama-cleaner: Image inpainting tool powered by LaMa

Qing 5.8k Jan 05, 2023
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration (NeurIPS 2021) PyTorch implementation of the paper: CoFiNet: Reli

76 Jan 03, 2023
Emblaze - Interactive Embedding Comparison

Emblaze - Interactive Embedding Comparison Emblaze is a Jupyter notebook widget for visually comparing embeddings using animated scatter plots. It bun

CMU Data Interaction Group 77 Nov 24, 2022