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The torch.class(classname, parentclass) function can be used to create object factories . When the constructor is called, torch initializes and sets a Lua table with the user-defined metatable, which makes the table an object.
PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo, a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and inference performance across major cloud platforms.
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.
llama.cpp began development in March 2023 by Georgi Gerganov as an implementation of the Llama inference code in pure C/C++ with no dependencies. This improved performance on computers without GPU or other dedicated hardware, which was a goal of the project.
Dynamic loading is a mechanism by which a computer program can, at run time, load a library (or other binary) into memory, retrieve the addresses of functions and variables contained in the library, execute those functions or access those variables, and unload the library from memory.
[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] TensorFlow provides a stable Python Application Program Interface , [45] as well as APIs without backwards compatibility guarantee for Javascript, [46] C++, [47] and Java.
Stubbing and mocking framework for C and C++ based on code generation from headers. Does not imply modification to your existing code, so well suited for legacy code refactoring. In particular, you don't need virtual operations or abstract classes. Can check call parameters, call sequence, handle multiple implementations of a mock, and more.
In computer science, region-based memory management is a type of memory management in which each allocated object is assigned to a region.A region, also called a zone, arena, area, or memory context, is a collection of allocated objects that can be efficiently reallocated or deallocated all at once.