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This is the documentation for mshadow: A Lightweight CPU/GPU Matrix/Tensor Template Library in C++/CUDA.

Getting started

• Read Tutorial to get started, understand data structures, and basic usages.
• [Expression API](Expression API) gives a comprehensive list of expressions supported in mshadow
• Read rest part of this page for other information.

What (documents) to read when using mshadow

• Basically, all the files ends in -inl.hpp, -inl.cuh are implementations, and can be ignored if only using mshadow
• The files ends in .h are heavily commented with doxyen format, and can be used to generate the corresponding document
• List of useful headers that needed to be included independently, read comments directly, or doxygen generated documents, an online version of doxygen generated documents is Here
  • mashadow/tensor.h: core header, contains all data structure, and core functions
  • mashadow/tensor_random.h: random number generator
  • mashadow/tensor_io.h: utils for save write to binary file
  • mashadow/tensor_container.h: an potential useful implementation that handles memory allocation like STL
• Doxygen works well for normal APIs header listed above, except for expression related codes. They also comes with detail comments, but maybe not straight forward to understand, read [Expression API](Expression API) for documentation of expression.
  • mashadow/tensor_expr.h: definition of expression template
  • mashadow/tensor_expr_ext.h: extension of expressions

Use and Customize mshadow

• Use mshadow: mshadow is a purely template library, include #include "mshadow/tensor.h" to your code to use the lib
• Package dependency: mshadow will need MKL or other CBLAS to do matrix multiplication. The package dependencies can be customized via macros in mashadow/tensor_base.h, examples:
  • To compile with CBLAS(ATLAS), add -DMSHADOW_USE_MKL=0 -DMSHADOW_USE_CBLAS=0 to CFLAGS
  • To compile without CUDA, and only use cpu mode, add -DMSHADOW_USE_CUDA=0 to CFLAGS