Showing 237 open source projects for "python code generator"

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  • 1
    PyTorch Transfer-Learning-Library

    PyTorch Transfer-Learning-Library

    Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.

    TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please...
    Downloads: 0 This Week
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  • 2
    JSON Parser

    JSON Parser

    JSON Parser written in C that outputs JSON into D-List list objects

    ...The JSON data is returned to the caller as a set of hierarchical D-List list objects, that make the data very easy to manage, sort, search or use, and easy to remove when done. Package includes a JSON textural generator which will create JSON grammar data blocks from hierarchical D-List representations of JSON data. The package also includes a variety of support functions to allow C code to easily find, add, and modify JSON values and members in D-List hierarchical structures.
    Downloads: 4 This Week
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  • 3
    comby

    comby

    A code rewrite tool for structural search and replace that supports

    Comby is a tool for searching and changing code structure. Use lightweight templates to easily search and change code, HTML, or JSON. Comby is designed to work on any language or data format. Perform richer search and replace because Comby understands the syntax of code blocks, strings, and comments for your language. Comby is ideal for touching up pieces of code. Use it to translate code like this Python 2 to 3 fixer on the right to replace deprecated methods. ...
    Downloads: 0 This Week
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  • 4
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the...
    Downloads: 1 This Week
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  • 5
    fastjson

    fastjson

    A fast JSON parser/generator for Java

    Fastjson is a Java library that can be used to quickly convert Java Objects into their JSON representation or convert JSON strings to their equivalent Java object. Based on benchmarks it provides the best performance in both server side and Android client, and can work with arbitrary Java objects, even those pre-existing objects of which you do not have the source code. Fastjson provides a simple conversion method to turn Java objects to JSON and vice versa, with extensive support of Java...
    Downloads: 0 This Week
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  • 6
    Google Cloud Vision API examples

    Google Cloud Vision API examples

    Sample code for Google Cloud Vision

    The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource.
    Downloads: 0 This Week
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  • 7
    protostuff

    protostuff

    Java serialization library, proto compiler, code generator

    A java serialization library with built-in support for forward-backward compatibility (schema evolution) and validation.
    Downloads: 0 This Week
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  • 8
    Awesome Conformal Prediction

    Awesome Conformal Prediction

    A professionally curated list of awesome Conformal Prediction videos

    awesome-conformal-prediction is a curated “awesome list” repository on GitHub collecting high-quality resources related to conformal prediction: tutorials, books, papers, theses, open-source libraries, videos, and other educational material. It is not a software library itself but a directory of resources for those wanting to learn or work with conformal prediction and uncertainty quantification. This exceptional resource is the culmination of my PhD journey in Machine Learning, specializing...
    Downloads: 0 This Week
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  • 9
    Spyne

    Spyne

    A transport agnostic sync/async RPC library

    Spyne is a Python RPC toolkit that makes it easy to expose online services that have a well-defined API using multiple protocols and transports. It integrates with popular Python web frameworks as well as libraries like SQLAlchemy to keep your code as DRY as possible. Spyne aims to save the protocol implementers the hassle of implementing their own remote procedure call api and the application programmers the hassle of jumping through hoops just to expose their services using multiple protocols and transports. ...
    Downloads: 0 This Week
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  • 10
    Nimporter

    Nimporter

    Compile Nim Extensions for Python On Import

    Nimporter allows the seamless import of Nim code into Python projects, enabling the use of Nim's performance and syntax within Python applications.
    Downloads: 0 This Week
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  • 11
    TensorFlow Examples

    TensorFlow Examples

    TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

    TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or...
    Downloads: 0 This Week
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  • 12
    TensorNetwork

    TensorNetwork

    A library for easy and efficient manipulation of tensor networks

    TensorNetwork is a high-level library for building and contracting tensor networks—graphical factorizations of large tensors that underpin many algorithms in physics and machine learning. It abstracts networks as nodes and edges, then compiles efficient contraction orders across multiple numeric backends so users can focus on model structure rather than index bookkeeping. Common network families (MPS/TT, PEPS, MERA, tree networks) are expressed with concise APIs that encourage...
    Downloads: 0 This Week
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  • 13
    ReinventCommunity

    ReinventCommunity

    Jupyter Notebook tutorials for REINVENT 3.2

    This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2.
    Downloads: 0 This Week
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  • 14
    Nerfies

    Nerfies

    This is the code for Deformable Neural Radiance Fields

    Nerfies demonstrates deformation-aware neural radiance fields that reconstruct and render dynamic, real-world scenes from casual video. Instead of assuming a static world, the method learns a canonical space plus a deformation field that maps changing poses or expressions back to that space during training. This lets the system generate photorealistic novel views of nonrigid subjects—faces, bodies, cloth—while preserving fine detail and consistent lighting. The training pipeline handles...
    Downloads: 0 This Week
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  • 15
    BMC

    BMC

    Notes on Scientific Computing for Biomechanics

    This repository is a collection of lecture notes and code on scientific computing and data analysis for Biomechanics and Motor Control.
    Downloads: 0 This Week
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  • 16
    earthengine-py-notebooks

    earthengine-py-notebooks

    A collection of 360+ Jupyter Python notebook examples

    earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. ...
    Downloads: 0 This Week
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  • 17
    CNN for Image Retrieval
    cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that...
    Downloads: 1 This Week
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  • 18
    Slug Generator Library

    Slug Generator Library

    Slug Generator Library for PHP, based on Unicode’s CLDR data

    This library provides methods to generate slugs for URLs, filenames or any other target that has a limited character set. It’s based on PHPs Transliterator class which uses the data of the CLDR to transform characters between different scripts (e.g. Cyrillic to Latin) or types (e.g. upper- to lower-case or from special characters to ASCII). There are many code snippets and some good libraries out there that create slugs, but I didn’t find anything that met my requirements. Options are often...
    Downloads: 0 This Week
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  • 19
    fastNLP

    fastNLP

    fastNLP: A Modularized and Extensible NLP Framework

    fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models...
    Downloads: 0 This Week
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  • 20
    SentEval

    SentEval

    A python tool for evaluating the quality of sentence embeddings

    SentEval is a standardized toolkit for evaluating sentence embeddings across a wide spectrum of downstream tasks and probing tests. It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic...
    Downloads: 0 This Week
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  • 21
    Sparse Attention

    Sparse Attention

    "Generating Long Sequences with Sparse Transformers" examples

    Sparse Attention is OpenAI’s code release for the Sparse Transformer model, introduced in the paper Generating Long Sequences with Sparse Transformers. It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. The repository provides implementations of sparse attention layers, training code, and evaluation scripts for benchmark datasets. It highlights...
    Downloads: 3 This Week
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  • 22
    ebfformat

    ebfformat

    An Efficient Binary data Format

    EBF, which stands for Efficient Binary Format, is a binary file format for reading and writing binary data easily. Reading writing routines are currently available in C,C++,Fortran,Java, Python, IDL, MATLAB. A program called ebftkpy which has a set of utility functions to work with the .ebf files , e.g., viewing the contents and getting a summary, is also provided. The EBF specification is designed to be concise and easy to understand to make it easier for others to write their own code if needed. It is also designed to simplify the programming of input output routines in different programming languages. ...
    Downloads: 1 This Week
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  • 23
    Top Deep Learning Projects

    Top Deep Learning Projects

    A list of popular github projects related to deep learning

    TopDeepLearning is a curated index of the most popular GitHub projects related to deep learning, ranked by their star count. Rather than being a library itself, it serves as a curated roadmap and reference guide for anyone exploring the deep learning ecosystem — from beginners to experienced practitioners. By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly...
    Downloads: 0 This Week
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  • 24
    Brand new cheatsheets and handouts

    Brand new cheatsheets and handouts

    Matplotlib 3.1 cheat sheet

    The Brand new cheatsheets and handouts repo is a compact, quick-reference summary of the most commonly used plotting commands and configurations in Matplotlib, intended to serve as a handy reference for experienced users who want to recall syntax or find the right function without digging into full documentation. It lays out common use cases (plot types, styling, figure configuration, saving/exporting, subplot layout, etc.) in a concise and organized format — often serving as a “cheat sheet”...
    Downloads: 0 This Week
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  • 25
    Tensor2Tensor

    Tensor2Tensor

    Library of deep learning models and datasets

    Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and...
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