Search Results for "blocks" - Page 4
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Showing 143 open source projects for "blocks"
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1
SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
...This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple computational steps, while maintaining speaker consistency across output channels. Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. The repository includes all necessary scripts for training, dataset preparation, distributed training, evaluation, and audio separation. -
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Trax
Deep learning with clear code and speed
Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively used and maintained in the Google Brain team. Run a pre-trained Transformer, create a translator in a few lines of code. Features and resources, API docs, where to talk to us, how to open an issue and more. Walkthrough, how Trax works, how to make new models and train on your own data. Trax includes basic models (like ResNet, LSTM, Transformer) and RL algorithms (like REINFORCE, A2C, PPO). It... -
3
TorchGAN
Research Framework for easy and efficient training of GANs
...The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to provide building blocks for popular GANs and also to allow customization for cutting-edge research. Using TorchGAN's modular structure allows. -
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Available Subnet Finder
A Python Script to find unused subnets
With a fragmented IP subnet listing, it can be difficult to find larger contiguous blocks to assign to sites, especially if you have multiple sources of truth. This script is designed to provide a way to find available subnets within a given supernet. For example, if you want to find all the available /19 networks available within your 10.0.0.0/8 space, you could feed this subnet all your known networks, and it will give you subnets which are not used. -
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5
TRFL
TensorFlow Reinforcement Learning
TRFL, developed by Google DeepMind, is a TensorFlow-based library that provides a collection of essential building blocks for reinforcement learning (RL) algorithms. Pronounced “truffle,” it simplifies the implementation of RL agents by offering reusable components such as loss functions, value estimation tools, and temporal difference (TD) learning operators. The library is designed to integrate seamlessly with TensorFlow, allowing users to define differentiable RL objectives and train models using standard optimization routines. ... -
6
PyCls
Codebase for Image Classification Research, written in PyTorch
...Distributed training and mixed precision are first-class, enabling fast experiments on multi-GPU setups with simple, declarative configs. Model definitions are concise and modular, making it easy to prototype new blocks or swap backbones while keeping the rest of the pipeline unchanged. Pretrained weights and evaluation scripts cover common datasets, and the logging/metric stack is designed for quick comparison across runs. Practitioners use pycls both as a baseline factory and as a scaffold for new classification backbones. -
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Minecraft
Simple Minecraft-inspired program using Python and Pyglet
Minecraft is a simple Minecraft-inspired demo written in Python using the Pyglet library for windowing, input, and OpenGL rendering. The project implements a first-person block world where you can walk around, jump, fly, and place or remove blocks using a small set of block types like brick, grass, and sand. It provides full WASD movement with mouse look and basic building controls, giving a surprisingly complete “sandbox” feel in only a small amount of Python code. The author explicitly describes a vision for the project as an educational tool: because many kids love Minecraft and Python is a friendly first programming language, the codebase is meant to be readable, hackable, and heavily commented so learners can tweak parameters like gravity or walking speed and see the effects immediately. ... -
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Bitcoin Black Core
BLACK use peer-to-peer technology to operate with no central authority
Bitcoin Black Core is a peer-to-peer electronic cash system that aims to become sound global money with fast payments, micro fees, privacy, and high transaction capacity (big blocks). In the same way that physical money, such as a dollar bill, is handed directly to the person being paid, Bitcoin Black Core payments are sent directly from one person to another. As a permissionless, decentralized cryptocurrency, Bitcoin Black Core requires no trusted third parties and no central bank. Unlike traditional fiat money, Bitcoin Black Core does not depend on monetary middlemen such as banks and payment processors. ... -
9
gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. -
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Tensorflow 2017 Tutorials
Tensorflow tutorial from basic to hard
Tensorflow 2017 Tutorials is a structured set of tutorials that introduce developers to TensorFlow, starting with basic neural network constructs and progressing to sophisticated model architectures and training techniques. This repository covers essential building blocks like sessions (for older TF versions), placeholders, variables, activation functions, and optimizers, before guiding learners through building end-to-end models for regression, classification, and data pipelines. Beyond the basics, the project includes examples of convolutional neural networks, recurrent networks, autoencoders, reinforcement learning, generative adversarial networks, and transfer learning workflows. ... -
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DenyHosts is a python program that automatically blocks ssh attacks by adding entries to /etc/hosts.deny. DenyHosts will also inform Linux administrators about offending hosts, attacked users and suspicious logins. This project is being actively developed on GitHub (https://github.com/denyhosts)
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12
AttackSurfaceMapper
Automated tool for mapping & expanding organization’s attack surface
AttackSurfaceMapper (ASM) is a reconnaissance and attack surface discovery tool designed to automate the process of mapping potential targets within an organization's infrastructure. It combines open source intelligence (OSINT) with selective active reconnaissance techniques to expand and analyze a target’s external attack surface. Users can supply domains, subdomains, or IP addresses as input, and applies multiple discovery methods to identify additional related assets such as new... -
13
PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
14
TF Quant Finance
High-performance TensorFlow library for quantitative finance
...Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The codebase is organized as modular math and finance primitives so you can combine building blocks or target end-to-end examples. It includes Bazel builds, tests, and example notebooks to accelerate learning and adoption in real workflows. With hardware acceleration and differentiable models, it enables modern techniques like gradient-based calibration and end-to-end learning of market dynamics. -
15
Spotlight
Deep recommender models using PyTorch
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various pointwise and pairwise ranking losses), representations (shallow factorization representations, deep sequence models), and utilities for fetching (or generating) recommendation datasets, it aims to be a tool for rapid exploration and prototyping of new recommender models. Spotlight offers a slew of popular datasets, including Movielens 100K, 1M, 10M, and 20M. ... -
16
GIF for CLI
Takes in a GIF, short video, or a query to the Tenor GIF API
...It takes an input GIF (or a URL) and converts each frame into a terminal-friendly representation, timing updates to approximate the original animation. Depending on terminal capabilities, it can use ANSI color blocks or image protocols to achieve surprisingly faithful playback. The tool includes conveniences such as looping control, scaling to fit your terminal, and caching to avoid repeated downloads. It’s useful for quick visual feedback, lightweight demos, or just adding some personality to scripts and readmes. Despite its whimsical nature, the project is a tight example of frame decoding, timing, and terminal rendering glued together in a single command. -
17
Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments to solve. Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained. ... -
18
AeroPython
Classical Aerodynamics of potential flow using Python
The AeroPython series of lessons is the core of a university course (Aerodynamics-Hydrodynamics, MAE-6226) by Prof. Lorena A. Barba at the George Washington University. The first version ran in Spring 2014 and these Jupyter Notebooks were prepared for that class, with assistance from Barba-group PhD student Olivier Mesnard. In Spring 2015, we revised and extended the collection, adding student assignments to strengthen the learning experience. The course is also supported by an open learning... -
19
MUSE
A library for Multilingual Unsupervised or Supervised word Embeddings
...The training and evaluation pipeline is lightweight and fast, so experimenting with different languages or initialization strategies is easy. Beyond dictionary induction, the learned embeddings are often used as building blocks for downstream tasks like classification, retrieval, or machine translation. -
20
Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo provides training recipes and models for standard datasets, as well as ablations that show how many non-local blocks to insert and at which stages. ... -
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pyNETVARS
Python module for network variables for CoDeSys PLCs
CoDeSys v2.3 supports so called network variables. Blocks of (global) variables, that propagates over networks like TCP, UDP or UDP Multicast aso. This python module supports parsing, receiving and sending those blocks (with UDP Multicast only). With this you can add for example a Raspberry Pi Sensor to your automation network without special Network clients on your PLC. -
22
BlockSparse
Efficient GPU kernels for block-sparse matrix multiplication
The blocksparse repository provides efficient GPU kernels (TensorFlow custom ops) for block-sparse matrix multiplication and convolution operations. The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse patterns to scale better. The repo implements both blocksparse and blockwise convolution/transpose-convolution primitives, with support for preparing, executing, and verifying those ops on NVIDIA GPUs. ... -
23
GoodCrypto private server
Secure mail + Tor gateway
... * Protects email metadata and resists traffic analysis * Automatic encryption, decryption, and key management * All private keys stay on *your* server * Users don't change their email or browser software * Blocks web malware * Runs on your private server * Completely decentralized -
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Grey Compressor+FTP
Grey Compressor+FTP compresses and uploads file to ftp server.
...Cons: * Grey Compressor+FTP may not download .7z file when connected to certain domain networks. * The sender and recipient must have an internet connection. Tips & Tricks: * Rename .bat to .batx if your email service blocks sending your .bat file via email. Recipient then must change the file extension back to .bat. *Grey Compressor+FTP currently has 375 GB of shared server space. This will increase as downloads increase. -
25
dxf2pcb
Convert DXF drawings of circuit boards to gEDA-PCB files.
This Python script reads in a DXF (ascii) file and generates a PCB output compatible with PCB Designer, part of the gEDA suite. It is designed for two purposes: One is to generate a PCB snippet from a mechanical drawing (such as a board outline), the other is to produce element files from CAD drawings. PCB snippets are easily imported into an existing gEDA-PCB project using File -> Load Layout to Buffer. Generated element files are ready to use (except for special cases like no-paste...
