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[](https://gitter.im/torch/torch7?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
[](https://travis-ci.org/torch/torch7)
## 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](https://github.com/pytorch/pytorch/tree/master/aten), [mirror](https://github.com/zdevito/ATen/)).
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/README.md](https://github.com/pytorch/pytorch/tree/master/aten/src#the-c-interface).
## Need help? ##
Torch7 community support can be found at the following locations. As of 2019, the Torch-7 community is close to non-existent.
* Questions, Support, Install issues: [Google groups](https://groups.google.com/forum/#!forum/torch7)
* Reporting bugs: [torch7](https://github.com/torch/torch7/issues) [nn](https://github.com/torch/nn/issues) [cutorch](https://github.com/torch/cutorch/issues) [cunn](https://github.com/torch/cutorch/issues) [optim](https://github.com/torch/optim/issues) [threads](https://github.com/torch/threads/issues)
* Hanging out with other developers and users (strictly no install issues, no large blobs of text): [Gitter Chat](https://gitter.im/torch/torch7)
<a name="torch.reference.dok"></a>
# Torch Package Reference Manual #
__Torch__ is the main package in [Torch7](http://torch.ch) 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.
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## Torch Packages ##
* Tensor Library
* [Tensor](doc/tensor.md) defines the _all powerful_ tensor object that provides multi-dimensional numerical arrays with type templating.
* [Mathematical operations](doc/maths.md) that are defined for the tensor object types.
* [Storage](doc/storage.md) defines a simple storage interface that controls the underlying storage for any tensor object.
* File I/O Interface Library
* [File](doc/file.md) is an abstract interface for common file operations.
* [Disk File](doc/diskfile.md) defines operations on files stored on disk.
* [Memory File](doc/memoryfile.md) defines operations on stored in RAM.
* [Pipe File](doc/pipefile.md) defines operations for using piped commands.
* [High-Level File operations](doc/serialization.md) defines higher-level serialization functions.
* Useful Utilities
* [Timer](doc/timer.md) provides functionality for _measuring time_.
* [Tester](doc/tester.md) is a generic tester framework.
* [CmdLine](doc/cmdline.md) is a command line argument parsing utility.
* [Random](doc/random.md) defines a random number generator package with various distributions.
* Finally useful [utility](doc/utility.md) functions are provided for easy handling of torch tensor types and class inheritance.
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## Useful Links ##
* [Community packages](https://github.com/torch/torch7/wiki/Cheatsheet)
* [Torch Blog](http://torch.ch/blog/)
* [Torch Slides](https://github.com/soumith/cvpr2015/blob/master/cvpr-torch.pdf)
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