套件：lua-torch-nn（0~20171002-g8726825+dfsg-4）

Neural Network Package for Torch Framework

This package provides an easy and modular way to build and train simple or complex neural networks using Torch Framework:

 * Modules are the bricks used to build neural networks.
   Each are themselves neural networks, but can be combined with
   other networks using containers to create complex neural networks:

   + Module: abstract class inherited by all modules.
   + Containers: container classes.
   + Transfer functions: non-linear functions.
   + Simple layers: simple network layer like `Linear`.
   + Table layers: layers for manipulating `table`s.
   + Convolution layers: several kinds of convolutions.

 * Criterions compute a gradient according to a given loss function
   given an input and a target:

   + Criterions: a list of all criterions.
   + `MSECriterion`: the Mean Squared Error criterion used for regression;
   + `ClassNLLCriterion`: the Negative Log Likelihood criterion used for
     classification.

 * Additional documentation:

  + Overview of the package essentials including modules, containers
    and training.
  + Training: how to train a neural network using optim.
  + Testing: how to test your modules.
  + Experimental Modules: a package containing experimental modules and
    criteria.

This package is a core part of the Torch Framework.

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