Search Results for "code to flow" - Page 2
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Showing 41 open source projects for "code to flow"
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nlpaug
Data augmentation for NLP
This Python library helps you with augmenting nlp for your machine learning projects. Visit this introduction to understand Data Augmentation in NLP. Augmenter is the basic element of augmentation while Flow is a pipeline to orchestra multi augmenters together. -
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Machine-Learning
kNN, decision tree, Bayesian, logistic regression, SVM
Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying... -
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OpenAI Glow
Copy code in "Glow: Generative Flow with Invertible 1x1 Convolutions"
...Glow’s architecture is based on reversible layers and efficient flow operations, which allow large-scale training while keeping memory usage manageable. The repository provides training code, pretrained models, and scripts for generating samples or reproducing key results from the original research. Glow is primarily intended for researchers and practitioners exploring generative modeling, likelihood-based training, and interpretable deep learning systems. -
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micrograd
A tiny scalar-valued autograd engine and a neural net library
...The repository is intentionally compact and readable, prioritizing clarity over performance so learners can follow every step of gradient flow and parameter updates. It is commonly used as a learning bridge between basic calculus intuition and full-scale deep learning frameworks, helping developers understand why autodiff libraries behave the way they do. -
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powerfactory-fmu
The FMI++ PowerFactory FMU Export Utility
...Currently, two types of simulations are supported: In quasi-static steady-state simulations a power system’s evolution with respect to time is captured by a series of load flow snapshots. RMS simulations allow to calculate the time-dependent dynamics of electromechanical models, including control devices (new in version v0.6). -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. ... -
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pysourceinfo
RTTI for Python Source and Binary Files
The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and... -
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Autologging
Easier logging and tracing of Python functions and class methods.
Autologging eliminates boilerplate logging setup code and tracing code, and provides a means to separate application logging from program flow and data tracing. Autologging provides two decorators and a custom log level: "autologging.logged" decorates a class to create a __log member. By default, the logger is named for the class's containing module and name (e.g. "my.module.ClassName"). -
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EfiPy
Python Library for accessing UEFI BIOS internal function by protocol
EfiPy is a Python Module on UEFI shell which can access UEFI BIOS kernel interface - System Table - Runtime Services - Boot Services pAnalyzer package - Tracing UEFI protocol calling flow Output protocol flow to screen or file with XML format CorePy (assembly package) - Simple Assembly code in Python environment. EfiPy Shell package- Simple uefi shell program coded with EfiPy library to prove EfiPy workable EfiPy leverage these open source packages - ctypes, CorePy. Samples https://sourceforge.net/u/efipy/svn/HEAD/tree/Trunk/ EfiPy Author: https://www.linkedin.com/in/max-wu-a9068b90/ -
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Tangent
Source-to-source debuggable derivatives in pure Python
Existing libraries implement automatic differentiation by tracing a program's execution (at runtime, like PyTorch) or by staging out a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools. As a result, you can finally read your automatic derivative code just like the rest of your program. ... -
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Five video classification methods
Code that accompanies my blog post outlining five video classification
Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the spatial features present in 2D images. While this additional information provides us more to work with, it also requires different network architectures and, often, adds larger memory and computational demands.We won’t use any optical flow images. This reduces model complexity, training time, and... -
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Kaengu
kaengu: Framework to build C-Code Flow Graphs and to calculate Metrics
Kaengu is a framework to build Code Flow Graphs from C-Source Code and to calculate different metrics. Graphical view on Code is a strong tool to a.) understand software and b.) detect flaws. Additionally, Kaengu can calculate some interesting metrics, such as the newly developed F-Complexity as well as Graph energy and propositions for Code Refactoring. -
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EduLB
The educational lattice Boltzmann code
EduLB is a small and easy to handle lattice Boltzmann code for channel flow. Main objective is to give interested people the opportunity to play around and see how things work. For feedback, leave a review, leave a comment on the discussion page or send me a private mail. -
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Python Trust Metrics. Implementation of Ford-Faulkersson Maximum Flow algorithm and mod_virgule's Trust Metrics code, in python
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Chasm is a language using assembler meat with C style bone. It provide the C style flow control statement to make assembler code easier to write and easier to maintain. All the register/memory modify code is in the assembler, give the programmer the de
