Transformer

StARformer: Transformer with State-Action-Reward Representations

This repository contains the PyTorch implementation for our paper titled StARformer: Transformer with State-Action-Reward Representations.We learn local State-Action-Reward representations (StAR-representations) to improve (long) sequence modeling for reinforcement learning (and imitation learning). Results Installation Dependencies can be installed by Conda: conda env create -f my_env.yml And install Atari ROMs. Datasets Please follow this instruction for datasets. Example usage See run.sh or below:

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Attributes

FACIAL: Synthesizing Dynamic Talking Face With Implicit Attribute Learning

PyTorch implementation for the paper: FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning Chenxu Zhang,Yifan Zhao,Yifei Huang,Ming Zeng,Saifeng Ni,Madhukar Budagavi,Xiaohu Guo ICCV 2021 Run demo on Google Colab Requirements conda create -n audio_face conda activate audio_face sudo apt-get install ffmpeg pip install -r requirements.txt you may add opencv by conda. Citation

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Attention

AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks

This repository provides the overall framework for training and evaluating audio anti-spoofing systems proposed in ‘AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks’ Getting started requirements.txt must be installed for execution. We state our experiment environment for those who prefer to simulate as similar as possible. pip install -r requirements.txt Our environment (for GPU training) Based on a docker image: pytorch:1.6.0-cuda10.1-cudnn7-runtime GPU: 1 NVIDIA Tesla V100 About 16GB is required to train AASIST using a batch size of 24 […]

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Tool

Github dorking tool with python

Supply a list of dorks and, optionally, one of the following: a user (-u) a file with a list of users (-uf) an organization (-org) a file with a list of organizations (-of) a repo (-r) You can also pass: an output directory to store results (-o) a filename to store valid items, if your users or org file may contain nonexistent users/orgs (-vif) All input files (dorks, users, or orgs) should be newline-separated. Usage Clone the repository, then runpip […]

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Python

Using Pygame to Build an Asteroids Game in Python

Do you want to create your own computer games but like Python too much to abandon it for a career as a game developer? There’s a solution for that! With the Pygame module, you can use your amazing Python skills to create games, from the basic to the very complex. Below, you’ll learn how to use Pygame by making a clone of the Asteroids game! In this course, you’ll learn how to build a complete game, including: Loading images and […]

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Facebook NLP Research
NLP

Dynamic Encoder Transducer: A Flexible Solution For Trading Off Accuracy For Latency

August 30, 2021 By: Yangyang Shi, Varun Nagaraja, Chunyang Wu, Jay Mahadeokar, Duc Le, Rohit Prabhavalkar, Alex Xiao, Ching-Feng Yeh, Julian Chan, Christian Fuegen, Ozlem Kalinli, Michael L. Seltzer Abstract We propose a dynamic encoder transducer (DET) for on-device speech recognition. One DET model scales to multiple devices with different computation capacities without retraining or fine-tuning. To trading off accuracy and latency, DET assigns different encoders to decode different parts of an utterance. We apply and compare the layer dropout […]

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