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Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into the TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers ...
PlaidML is a portable tensor compiler.Tensor compilers bridge the gap between the universal mathematical descriptions of deep learning operations, such as convolution, and the platform and chip-specific code needed to perform those operations with good performance.
JAX is a machine learning framework for transforming numerical functions. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).
Prolog [9] [10] is a declarative language where programs are expressed in terms of relations, and execution occurs by running queries over these relations. Prolog is particularly useful for symbolic reasoning, database and language parsing applications.
TensorFlow serves as a core platform and library for machine learning. TensorFlow's APIs use Keras to allow users to make their own machine-learning models. [33] [43] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving. [44]
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.
Keras, a high level open-source software library for machine learning (works on top of other libraries). [81] Microsoft Cognitive Toolkit (previously known as CNTK), an open source toolkit for building artificial neural networks. [82] OpenNN, a comprehensive C++ library implementing neural networks. [83]
Use of the polyhedral model (also called the polytope model) within a compiler requires software to represent the objects of this framework (sets of integer-valued points in regions of various spaces) and perform operations upon them (e.g., testing whether the set is empty).