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4 dépôts

Awesome GitHub RepositoriesTensor Cloning

Creating complete independent copies of tensor data in new memory allocations.

Distinct from Tensor Transformations: Explicitly handles full data duplication, distinct from packing or unpacking existing tensors.

Explore 4 awesome GitHub repositories matching data & databases · Tensor Cloning. Refine with filters or upvote what's useful.

Awesome Tensor Cloning GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • federico-busato/modern-cpp-programmingAvatar de federico-busato

    federico-busato/Modern-CPP-Programming

    15,808Voir sur GitHub↗

    This project is a comprehensive educational resource and programming course covering C++ language semantics and features from C++03 through C++26. It provides structured tutorials and technical guides focused on modern C++ development. The material offers specialized instruction on template metaprogramming, including the use of type traits and compile-time computations. It features detailed guides on concurrency and parallelism for multi-core execution, as well as a reference for software design applying SOLID principles and RAII. Additionally, it covers build performance optimization to redu

    Provides instruction on representing matrices and tensors using non-owning views that map indices to linear memory.

    HTMLc-plus-pluscode-qualitycompilers
    Voir sur GitHub↗15,808
  • torch/torch7Avatar de torch

    torch/torch7

    9,127Voir sur GitHub↗

    Torch7 is a scientific computing environment and tensor computation library used for deep learning research and numerical analysis. It functions as a Lua-based framework for training neural networks and learning agents, providing a toolkit for implementing architectures and training through reinforcement learning algorithms. The project is distinguished by its tight integration with C, utilizing a binding layer to map high-level scripting to low-level C structures for direct memory access. It supports hardware-accelerated computation by offloading linear algebra and convolution operations to

    Produces a complete copy of a tensor's data in a new memory allocation.

    C
    Voir sur GitHub↗9,127
  • pytorch/executorchAvatar de pytorch

    pytorch/executorch

    4,296Voir sur GitHub↗

    ExecuTorch is a lightweight C++ runtime for deploying PyTorch models on mobile, embedded, and edge hardware. It provides an ahead-of-time compilation pipeline that exports, quantizes, and lowers model graphs into compact serialized programs, then executes them through a minimal runtime with hardware acceleration and on-device large language model inference capabilities. The project distinguishes itself through a hardware accelerator delegate system that partitions model subgraphs and offloads computation to specialized backends including NPUs, GPUs, and DSPs from Apple, Arm, Intel, MediaTek,

    Provides tensor cloning functionality to create independent copies of tensor data in new memory allocations.

    Pythondeep-learningembeddedgpu
    Voir sur GitHub↗4,296
  • answerdotai/gpu.cppAvatar de AnswerDotAI

    AnswerDotAI/gpu.cpp

    3,981Voir sur GitHub↗

    gpu.cpp is a lightweight C++ library for executing low-level general-purpose GPU computation across different hardware vendors and operating systems. It functions as a portable GPU wrapper, kernel orchestrator, and tensor management system using the WebGPU specification to abstract device initialization, buffer transfers, and compute shader dispatching. The library provides a framework for defining compute kernels from shader code and managing their asynchronous dispatch and synchronization. It enables the execution of cross-platform compute shaders and the orchestration of GPU tasks through

    Creates non-owning views of hardware buffers using offsets and shapes to avoid duplicating GPU memory.

    C++
    Voir sur GitHub↗3,981
  1. Home
  2. Data & Databases
  3. Data Processing Pipelines
  4. Data Transformation
  5. Array and Tensor Manipulation
  6. Tensor Transformations
  7. Tensor Cloning

Explorer les sous-tags

  • Non-Owning Tensor ViewsWrapping existing memory buffers as tensors without taking ownership of the underlying data. **Distinct from Tensor Cloning:** Distinct from Tensor Cloning: creates views over existing memory without copying data, whereas cloning creates independent copies.