Pytorch version of VidLanKD: Improving Language Understanding viaVideo-Distilled Knowledge Transfer

Related tags

Deep LearningVidLanKD
Overview

VidLanKD

Implementation of VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer by Zineng Tang, Jaemin Cho, Hao Tan, Mohit Bansal.

Setup

# Create python environment (optional)
conda create -n vidlankd python=3.7

# Install python dependencies
pip install -r requirements.txt

To speed up the training, we use mixed precision with Apex.

git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

Dataset Preparation

Text Dataset

We provide scripts to obtain datasets "wiki103" and "wiki".

Wiki103, a seleted subset of English Wikipedia.

bash data/wiki103/get_data_cased.bash

English Wikipedia. The scripts are modified from XLM.

bash data/wiki/get_data_cased.bash en

Video Dataset

Howto100m where you can download official captions and videos features.

Video Features Extraction Code

To be updated.

  • We extracted our 2D-level video features with ResNet152 from torchvision.
  • We extracted our 3D-level video features with 3D-RexNext.

Downstream tasks

GLUE dataset

Download dataset

python download_glue_data.py --data_dir data/glue --tasks all

Training

Teacher model pre-training

# bash scripts/small_vlm_howto100m.bash $GPUS #teacher_SNAP_PATH
bash scripts/small_vlm_howto100m.bash 0,1,2,3 howto100m_bert_small_vokenhinge
# bash scripts/base_vlm_howto100m.bash $GPUS #teacher_SNAP_PATH
bash scripts/base_vlm_howto100m.bash 0,1,2,3 howto100m_bert_base_vokenhinge

Knowledge transfer to student model

# bash scripts/small_vlm_wiki103.bash $GPUS #teacher_SNAP_PATH #student_SNAP_PATH
bash scripts/small_vlm_wiki103.bash 0,1,2,3 howto100m_bert_small_vokenhinge/checkpoint-epoch0019 wiki103_bert_small_vokenmmd
# bash scripts/base_vlm_wiki.bash $GPUS #teacher_SNAP_PATH #student_SNAP_PATH
bash scripts/base_vlm_wiki.bash 0,1,2,3 howto100m_bert_base_vokenhinge/checkpoint-epoch0019 wiki_bert_base_vokenmmd

Finetuning on GLUE tasks

# bash scripts/run_glue_at_epoch.bash $GPUS $NumTrainEpochs $SNAP_PATH                        
bash scripts/run_glue_at_epoch.bash 0,1,2,3 3 snap/vlm/wiki103_bert_small_vokenmmd/checkpoint-epoch0019                  

Acknowledgements

Part of the code is built based on vokenization, huggingface transformers, and facebook faiss.

Owner
Zineng Tang
Zineng Tang
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

mani 1.2k Jan 07, 2023
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors

You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors In this paper, we propose a novel local descriptor-based fra

Haiping Wang 80 Dec 15, 2022
Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection

Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection

61 Jan 07, 2023
The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"

Swin-Unet The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"(https://arxiv.org/abs/2105.05537). A validatio

869 Jan 07, 2023
Rayvens makes it possible for data scientists to access hundreds of data services within Ray with little effort.

Rayvens augments Ray with events. With Rayvens, Ray applications can subscribe to event streams, process and produce events. Rayvens leverages Apache

CodeFlare 32 Dec 25, 2022
SWA Object Detection

SWA Object Detection This project hosts the scripts for training SWA object detectors, as presented in our paper: @article{zhang2020swa, title={SWA

237 Nov 28, 2022
Official PyTorch implementation of the paper "Deep Constrained Least Squares for Blind Image Super-Resolution", CVPR 2022.

Deep Constrained Least Squares for Blind Image Super-Resolution [Paper] This is the official implementation of 'Deep Constrained Least Squares for Bli

MEGVII Research 141 Dec 30, 2022
Localization Distillation for Object Detection

Localization Distillation for Object Detection This repo is based on mmDetection. This is the code for our paper: Localization Distillation

274 Dec 26, 2022
Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

CSRL Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning Python: 3

4 Apr 14, 2022
Numenta published papers code and data

Numenta research papers code and data This repository contains reproducible code for selected Numenta papers. It is currently under construction and w

Numenta 293 Jan 06, 2023
In this project, we'll be making our own screen recorder in Python using some libraries.

Screen Recorder in Python Project Description: In this project, we'll be making our own screen recorder in Python using some libraries. Requirements:

Hassan Shahzad 4 Jan 24, 2022
A custom DeepStack model that has been trained detecting ONLY the USPS logo

This repository provides a custom DeepStack model that has been trained detecting ONLY the USPS logo. This was created after I discovered that the Deepstack OpenLogo custom model I was using did not

Stephen Stratoti 9 Dec 27, 2022
RITA is a family of autoregressive protein models, developed by LightOn in collaboration with the OATML group at Oxford and the Debora Marks Lab at Harvard.

RITA: a Study on Scaling Up Generative Protein Sequence Models RITA is a family of autoregressive protein models, developed by a collaboration of Ligh

LightOn 69 Dec 22, 2022
Original code for "Zero-Shot Domain Adaptation with a Physics Prior"

Zero-Shot Domain Adaptation with a Physics Prior [arXiv] [sup. material] - ICCV 2021 Oral paper, by Attila Lengyel, Sourav Garg, Michael Milford and J

Attila Lengyel 40 Dec 21, 2022
Python scripts for performing 3D human pose estimation using the Mobile Human Pose model in ONNX.

Python scripts for performing 3D human pose estimation using the Mobile Human Pose model in ONNX.

Ibai Gorordo 99 Dec 31, 2022
structured-generative-modeling

This repository contains the implementation for the paper Information Theoretic StructuredGenerative Modeling, Specially thanks for the open-source co

0 Oct 11, 2021
Deploying PyTorch Model to Production with FastAPI in CUDA-supported Docker

Deploying PyTorch Model to Production with FastAPI in CUDA-supported Docker A example FastAPI PyTorch Model deploy with nvidia/cuda base docker. Model

Ming 68 Jan 04, 2023
A containerized REST API around OpenAI's CLIP model.

OpenAI's CLIP — REST API This is a container wrapping OpenAI's CLIP model in a RESTful interface. Running the container locally First, build the conta

Santiago Valdarrama 48 Nov 06, 2022
meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)

meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]

LancoPKU 107 Nov 18, 2022
[CVPR 2021] Unsupervised 3D Shape Completion through GAN Inversion

ShapeInversion Paper Junzhe Zhang, Xinyi Chen, Zhongang Cai, Liang Pan, Haiyu Zhao, Shuai Yi, Chai Kiat Yeo, Bo Dai, Chen Change Loy "Unsupervised 3D

100 Dec 22, 2022