Search Results for "compute" - Page 2
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Showing 42 open source projects for "compute"
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FairScale
PyTorch extensions for high performance and large scale training
FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce... -
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fog
The Ruby cloud services library
Whether you need compute, dns, storage, or a multitude of other services, fog provides an accessible entry point and facilitates cross-service compatibility. Just getting started working with cloud resources? You are not alone, and having so many complicated options makes it hard to know where to start. fog delivers the knowledge of cloud experts to you, helping you to bootstrap your cloud usage and guiding you as your own expertise develops. -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a... -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
...These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. Criterions compute the loss function given the model outputs and targets. Tasks store dictionaries and provide helpers for loading/iterating over Datasets, initializing the Model/Criterion and calculating the loss. -
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Intel compute-runtime
Intel® Graphics Compute Runtime
The Intel(R) Graphics Compute Runtime for oneAPI Level Zero and OpenCL(TM) Driver is an open source project providing compute API support (Level Zero, OpenCL) for Intel graphics hardware architectures (HD Graphics, Xe). -
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
...Though archived, it remains a key reference for efficient transformer research, influencing many later architectures that aim to extend sequence length while reducing compute. -
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PerfKit Benchmarker
PerfKit Benchmarker (PKB) contains a set of benchmarks
...It simplifies the process of running complex benchmarks by providing unified command-line workflows that handle resource provisioning, execution, and result collection. The framework includes a comprehensive set of predefined benchmarks covering areas such as compute, storage, networking, and distributed systems workloads. It is widely used by researchers, engineers, and organizations to evaluate cloud architectures and make informed infrastructure decisions. -
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Higher
higher is a pytorch library
higher is a specialized library designed to extend PyTorch’s capabilities by enabling higher-order differentiation and meta-learning through differentiable optimization loops. It allows developers and researchers to compute gradients through entire optimization processes, which is essential for tasks like meta-learning, hyperparameter optimization, and model adaptation. The library introduces utilities that convert standard torch.nn.Module instances into “stateless” functional forms, so parameter updates can be treated as differentiable operations. ... -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
...Efficient implementations keep memory and compute manageable so the blocks can be added without rewriting the entire backbone. The result is a practical, drop-in mechanism for upgrading purely local video models into context-aware networks with strong benchmark performance. -
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properties
another c#-like property accessor for c++11 and above.
A property is a member that provides a flexible mechanism to read, write, or compute the value of a private field. Properties can be used as if they are public data members, but they are actually special methods called accessors. This enables data to be accessed easily and still helps promote the safety and flexibility of methods. * Github repository : https://github.com/gammasoft71/properties * Homepage : https://gammasoft71.wixsite.com/properties * Reference guide : https://codedocs.xyz/gammasoft71/properties/ * Examples : https://github.com/gammasoft71/properties/tree/master/examples -
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tracking.js
A modern approach for Computer Vision on the web
The tracking.js library brings different computer vision algorithms and techniques into the browser environment. By using modern HTML5 specifications, we enable you to do real-time color tracking, face detection and much more, all that with a lightweight core (~7 KB) and intuitive interface. To get started, download the project. This project includes all of the tracking.js examples, source code dependencies you'll need to get started. Unzip the project somewhere on your local drive. The... -
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pure python polyfit
python2/3: compute polyfit (1D, 2D, N-D) without thirdparty libraries
python2/3: compute polyfit (1D, 2D, N-D) without any thirdparty library like numpy, scipy etc. also can be used for least squares solution computation and for A=QR matrix decomposition. Tested with python 2.7 and 3.4 Consider donating to this project: https://sourceforge.net/p/purepythonpolyfit/donation For a Sample use, refer to the WIKI -
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Mpaxs
Transparent Local and Remote Parallelization for Java
Mpaxs provides a simple abstraction for executing Callables and Runnables either locally within the same Virtual Machine, on the same host via RMI, or on remote machines, also via RMI. It supports launching of new compute hosts via an extensible API, currently featuring local compute host launching and grid compute host launching using the DRMAA API. -
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jStyleParser
Java CSS parser and DOM style assignment library
...It has its own application interface that is designed to allow an efficient CSS processing in Java and mapping the values to the Java data types. It is also able to apply the parsed style sheets to a DOM that represents an HTML or XML document and to compute the resulting style of the individual document elements. It supports CSS 2.1 and a large subset of CSS3. -
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HASEM
Matrix c++ library solving any linear algebra problems
HASEM is a c++ template library, it can be easily configure as a expression template. HASEM solves any linear equation of any kind, it might be homogenous/none homogenous, compute the inverse of square/none square matrices, find LU decomposition, find determinant and rank of matrices, calculate the characteristic polynomial of matrices, find the eigenvalues and eigen vectors and so on. HASEM uses many methods, therefore, you are not limited to just one method, you have the choice to define your desire method as default one. ... -
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This tool allows to compute LOLIMOT models. LOLIMOT models are also called neuro-fuzzy models or fast neural network models. This tool can export the model into C, C++, Matlab.
