tensorflow
Pytorch
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tensorflow | Pytorch | |
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221 | 336 | |
182,323 | 77,783 | |
0.7% | 2.4% | |
10.0 | 10.0 | |
6 days ago | 2 days ago | |
C++ | Python | |
Apache License 2.0 | BSD 1-Clause License |
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tensorflow
- TensorFlow-metal on Apple Mac is junk for training
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐
- One .gitignore to rule them all
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10 Github repositories to achieve Python mastery
Explore here.
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GitHub and Developer Ecosystem Control
Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.
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Non-determinism in GPT-4 is caused by Sparse MoE
Right but that's not an inherent GPU determinism issue. It's a software issue.
https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.
Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.
Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.
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Can someone explain how keras code gets into the Tensorflow package?
and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:
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Is it even possible to design a ML model without using Python or MATLAB? Like using C++, C or Java?
Exactly what language do you think TensorFlow is written in? :)
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How to do deep learning with Caffe?
You can use Tensorflow's deep learning API for this.
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When the documentation has TODOs
Since you've specifically mentioned ML, here's Tenserflow's GitHub. I'm sure a quick glance through that will change your mind.
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?
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
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
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
flax - Flax is a neural network library for JAX that is designed for flexibility.
scikit-learn - scikit-learn: machine learning in Python
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.