xtensor
Pytorch
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xtensor | Pytorch | |
---|---|---|
8 | 336 | |
3,205 | 77,783 | |
1.7% | 2.4% | |
7.9 | 10.0 | |
9 days ago | 3 days ago | |
C++ | Python | |
BSD 3-clause "New" or "Revised" License | BSD 1-Clause License |
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xtensor
- Does anyone know any good open source project to optimize?
- Container slicing in c++
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Which is the best way to work with matrices and linear algebra using c++?
I use xtensor: https://github.com/xtensor-stack/xtensor
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Can you give an example of well-designed C++ code, and explain why you think it is so?
Currently, one of my current favorites is xtensor.
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Risk of valarray being deprecated?
xTensor natively supports tensors and multidimensional arrays - not just vectors and matrices. Is fast, but not always as fast as Eigen and Blaze - and compiles very slow. Has a nice syntax.
- Xtensor: multi-dimensional arrays with broadcasting and lazy computing
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Eigen: A C++ template library for linear algebra
I wonder how Eigen compares to xtensor, which was inspired by Numpy and has support for views, slicing, and broadcasting?
https://github.com/xtensor-stack/xtensor
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When researching and developing new algorithms to be used in the real-world production environment, what is your workflow and how do you usually do it? Do I have to prototype in Python, and then rewrite all code in C++/Rust?
You can try eigen (http://eigen.tuxfamily.org/), armadillo (http://arma.sourceforge.net/) which is based on LAPACK which is what numpy is based on and xtensor (https://github.com/QuantStack/xtensor) which I think is the closest thing to numpy you’re gonna find in c++
Pytorch
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
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Building a GPT Model from the Ground Up!
import torch # we use PyTorch: https://pytorch.org data = torch.tensor(encode(text), dtype=torch.long) print(data.shape, data.dtype) print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Element-wise vs Matrix vs Dot multiplication
In PyTorch with * or mul(). ` or mul()` can multiply 0D or more D tensors by element-wise multiplication:
What are some alternatives?
Fastor - A lightweight high performance tensor algebra framework for modern C++
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
EA Standard Template Library - EASTL stands for Electronic Arts Standard Template Library. It is an extensive and robust implementation that has an emphasis on high performance.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
dynarray - A header-only library, VLA for C++ (≥C++14). Extended version of std::experimental::dynarray
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
SwiftyWasmer - A Swift API for the Wasmer WebAssembly Runtime
flax - Flax is a neural network library for JAX that is designed for flexibility.
GLM - OpenGL Mathematics (GLM)
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
pinocchio - A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more