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Пакунок: lua-torch-optim (0~20171127-ga5ceed7-1)

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Numeric Optimization Package for Torch Framework

This package contains several optimization routines and a logger for Torch.

The following algorithms are provided:

 * Stochastic Gradient Descent
 * Averaged Stochastic Gradient Descent
 * L-BFGS
 * Congugate Gradients
 * AdaDelta
 * AdaGrad
 * Adam
 * AdaMax
 * FISTA with backtracking line search
 * Nesterov's Accelerated Gradient method
 * RMSprop
 * Rprop
 * CMAES
All these algorithms are designed to support batch optimization as well as stochastic optimization. It's up to the user to construct an objective function that represents the batch, mini-batch, or single sample on which to evaluate the objective.

This package provides also logging and live plotting capabilities via the `optim.Logger()` function. Live logging is essential to monitor the network accuracy and cost function during training and testing, for spotting under- and over-fitting, for early stopping or just for monitoring the health of the current optimisation task.

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