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The Conda package manager's historical differentiation analyzed and resolved these installation conflicts. [ 39 ] Anaconda is a distribution of the Python and R programming languages for scientific computing ( data science , machine learning applications, large-scale data processing , predictive analytics , etc.), that aims to simplify package ...
Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. [ 14 ] A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot , [ 15 ] Uber 's Pyro, [ 16 ] Hugging Face 's Transformers, [ 17 ] PyTorch Lightning , [ 18 ] [ 19 ] and Catalyst.
Anaconda is a free and open-source system installer for Linux distributions.. Anaconda is used by Red Hat Enterprise Linux, Oracle Linux, Scientific Linux, Rocky Linux, AlmaLinux, CentOS, MIRACLE LINUX, Qubes OS, Fedora, Sabayon Linux and BLAG Linux and GNU, also in some less known and discontinued distros like Progeny Componentized Linux, Asianux, Foresight Linux, Rpath Linux and VidaLinux.
Conda is an open-source, [2] cross-platform, [3] language-agnostic package manager and environment management system. It was originally developed to solve package management challenges faced by Python data scientists, and today is a popular package manager for Python and R.
Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6]
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3]
PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.
OpenVINO IR [5] is the default format used to run inference. It is saved as a set of two files, *.bin and *.xml, containing weights and topology, respectively.It is obtained by converting a model from one of the supported frameworks, using the application's API or a dedicated converter.