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  2. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    PyTorch is a machine learning library based on the Torch library, [4] [5] [6] used for applications such as computer vision and natural language processing, [7] originally developed by Meta AI and now part of the Linux Foundation umbrella.

  3. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    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]

  4. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    CUDA 9.0–9.2 comes with these other components: CUTLASS 1.0 – custom linear algebra algorithms, NVIDIA Video Decoder was deprecated in CUDA 9.2; it is now available in NVIDIA Video Codec SDK; CUDA 10 comes with these other components: nvJPEG – Hybrid (CPU and GPU) JPEG processing; CUDA 11.0–11.8 comes with these other components: [20 ...

  5. PyTorch Lightning - Wikipedia

    en.wikipedia.org/wiki/PyTorch_Lightning

    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.

  6. Quine's paradox - Wikipedia

    en.wikipedia.org/wiki/Quine's_paradox

    Quine's paradox is a paradox concerning truth values, stated by Willard Van Orman Quine. [1] It is related to the liar paradox as a problem, and it purports to show that a sentence can be paradoxical even if it is not self-referring and does not use demonstratives or indexicals (i.e. it does not explicitly refer to itself).

  7. Thread block (CUDA programming) - Wikipedia

    en.wikipedia.org/wiki/Thread_block_(CUDA...

    The number of threads in a block is limited, but grids can be used for computations that require a large number of thread blocks to operate in parallel and to use all available multiprocessors. CUDA is a parallel computing platform and programming model that higher level languages can use to exploit parallelism.

  8. Nvidia NVENC - Wikipedia

    en.wikipedia.org/wiki/Nvidia_NVENC

    These features rely on CUDA cores for hardware acceleration. SDK 7 supports two forms of adaptive quantization; Spatial AQ (H.264 and HEVC) and Temporal AQ (H.264 only). Nvidia's consumer-grade (GeForce) cards and some of its lower-end professional Quadro cards are restricted to three simultaneous encoding jobs. Its higher-end Quadro cards do ...

  9. Existential quantification - Wikipedia

    en.wikipedia.org/wiki/Existential_quantification

    This particular example is true, because 5 is a natural number, and when we substitute 5 for n, we produce the true statement =. It does not matter that " n × n = 25 {\displaystyle n\times n=25} " is true only for that single natural number, 5; the existence of a single solution is enough to prove this existential quantification to be true.