Torch alternatives and similar libraries
Based on the "Scientific Computing" category.
Alternatively, view Torch alternatives based on common mentions on social networks and blogs.
7.4 3.2 L4 Torch VS FFTWDO NOT CHECK OUT THESE FILES FROM GITHUB UNLESS YOU KNOW WHAT YOU ARE DOING. (See below.)
5.1 10.0 Torch VS Kratos MultiphysicsKratos Multiphysics (A.K.A Kratos) is a framework for building parallel multi-disciplinary simulation software. Modularity, extensibility and HPC are the main objectives. Kratos has BSD license and is written in C++ with extensive Python interface.
4.0 9.5 Torch VS preCICEA coupling library for partitioned multi-physics simulations, including, but not restricted to fluid-structure interaction and conjugate heat transfer simulations.
2.4 9.0 Torch VS HELICSHierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS)
2.2 6.4 Torch VS UnitsA run-time C++ library for working with units of measurement and conversions between them and with string representations of units and measurements
1.4 0.3 Torch VS DimwitsA compact C++ header-only library providing compile-time dimensional analysis and unit awareness
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
Do you think we are missing an alternative of Torch or a related project?
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/README.md.
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
- Reporting bugs: torch7 nn cutorch cunn optim threads
- Hanging out with other developers and users (strictly no install issues, no large blobs of text): Gitter Chat
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.
- 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.