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Development Status

Torch is not in active developement. The functionality provided by the C backend of Torch, which are the TH, THNN, THC, THCUNN libraries is actively extended and re-written in the ATen C++11 library (source, mirror). ATen exposes all operators you would expect from torch7, nn, cutorch, and cunn directly in C++11 and includes additional support for sparse tensors and distributed operations. It is to note however that the API and semantics of the backend libraries in Torch-7 are different from the semantice provided by ATen. For example ATen provides numpy-style broadcasting while TH* dont. For information on building the forked Torch-7 libraries in C, refer to "The C interface" in pytorch/aten/src/

Need help?

Torch7 community support can be found at the following locations. As of 2019, the Torch-7 community is close to non-existent.

Torch Package Reference Manual

Torch is the main package in Torch7 where data structures for multi-dimensional tensors and mathematical operations over these are defined. Additionally, it provides many utilities for accessing files, serializing objects of arbitrary types and other useful utilities.

Torch Packages

  • Tensor Library
    • Tensor defines the all powerful tensor object that provides multi-dimensional numerical arrays with type templating.
    • Mathematical operations that are defined for the tensor object types.
    • Storage defines a simple storage interface that controls the underlying storage for any tensor object.
  • File I/O Interface Library
  • Useful Utilities
    • Timer provides functionality for measuring time.
    • Tester is a generic tester framework.
    • CmdLine is a command line argument parsing utility.
    • Random defines a random number generator package with various distributions.
    • Finally useful utility functions are provided for easy handling of torch tensor types and class inheritance.

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