Search Results for "simpledecisiontree_v1.4.xla"
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Showing 11 open source projects for "simpledecisiontree_v1.4.xla"
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PyTorch/XLA
Enabling PyTorch on Google TPU
PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs. You can try it right now, for free, on a single Cloud TPU with Google Colab, and use it in production and on Cloud TPU Pods with Google Cloud. Take a look at one of our Colab notebooks to quickly try different PyTorch networks running on Cloud TPUs and learn how to use Cloud TPUs as PyTorch devices. -
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JAX
Composable transformations of Python+NumPy programs
...It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and TPUs. Compilation happens under the hood by default, with library calls getting just-in-time compiled and executed. But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python. -
3
tinygrad
Deep learning framework
This may not be the best deep learning framework, but it is a deep learning framework. Due to its extreme simplicity, it aims to be the easiest framework to add new accelerators to, with support for both inference and training. If XLA is CISC, tinygrad is RISC. -
4
TensorFlow
TensorFlow is an open source library for machine learning
Originally developed by Google for internal use, TensorFlow is an open source platform for machine learning. Available across all common operating systems (desktop, server and mobile), TensorFlow provides stable APIs for Python and C as well as APIs that are not guaranteed to be backwards compatible or are 3rd party for a variety of other languages. The platform can be easily deployed on multiple CPUs, GPUs and Google's proprietary chip, the tensor processing unit (TPU). TensorFlow... -
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5
MaxText
A simple, performant and scalable Jax LLM
MaxText is a high-performance, highly scalable open-source framework designed to train and fine-tune large language models using the JAX ecosystem. The project acts as both a reference implementation and a practical training library that demonstrates best practices for building and scaling transformer-based language models on modern accelerator hardware. It is optimized to run efficiently on Google Cloud TPUs and GPUs, enabling researchers and engineers to train models ranging from small... -
6
OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous distributed expansion. ... -
7
Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels, perform exact GP inference, and study training dynamics analytically for infinitely wide networks. ... -
8
Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
9
Excel2LaTeX
The Excel add-in for creating LaTeX tables
...Known to be compatible with Windows Excel 2000–2016 (32-bit and 64-bit) and Mac Excel 2004, 2011, and 2016. May also be compatible with other versions that support .xla add-ins. Does not work on LibreOffice Calc. -
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10
TCL TK VBA geolog code writer
VBA add-in for writing TCL/TK code blocks
...So instead of having classes and objects I wrote this program to generate blocks of commonly used geolog TCL/TK code. It automatically generates blocks of Tcl Puts code, Mui Dialog Boxes and Mui Selection Boxes from UNIX flat ascii files. To run the program load the XLA file into Excel then press CTRL + T to fire up the form. If your ascii files are in DOS rather than UNIX format you will not be able to generate proper TCL/TK code. The bar at the top of the form allows you to convert files from Dos to Unix if need be and check which format they are in. The difference between Unix and Dos ascii format is the line endings. ... -
11
Excel Compare GUI
A tool used to compare any Spread Sheet
This is simple a tool used or comparing spreadsheets. Smart Comparison of any spread sheet with output reports in html/xml/Excel formats For Complete help refer link below Note: This tool needs MS Office to be installed in your PC.
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