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Nuitka. Nuitka (pronounced as / njuːtkʌ / [ 2]) is a source-to-source compiler which compiles Python code to C source code, applying some compile-time optimizations in the process such as constant folding and propagation, built-in call prediction, type inference, and conditional statement execution. [ 3][ 4] Nuitka initially was designed to ...
Project Jupyter ( / ˈdʒuːpɪtər / ⓘ) is a project to develop open-source software, open standards, and services for interactive computing across multiple programming languages . It was spun off from IPython in 2014 by Fernando Pérez and Brian Granger. Project Jupyter's name is a reference to the three core programming languages supported ...
TensorFlow.nn is a module for executing primitive neural network operations on models. [ 38] Some of these operations include variations of convolutions (1/2/3D, Atrous, depthwise), activation functions ( Softmax, RELU, GELU, Sigmoid, etc.) and their variations, and other operations ( max-pooling, bias-add, etc.).
The language is not source-compatible with Python 3, only providing a subset of its syntax, e.g. missing the global keyword, list and dictionary comprehensions, and support for classes. Further, Mojo also adds features that enable performant low-level programming: fn for creating typed , compiled functions and "struct" for memory -optimized ...
Lean is a proof assistant and a functional programming language. [ 1] It is based on the calculus of constructions with inductive types. It is an open-source project hosted on GitHub. It was developed primarily by Leonardo de Moura while employed by Microsoft Research and now Amazon Web Services, and has had significant contributions from other ...
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Google JAX is a machine learning framework for transforming numerical functions. [ 1][ 2][ 3] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow 's XLA (Accelerated Linear Algebra). It is designed to follow the structure and ...
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