Mercurial > hg > jslab
view src/samer/models/#Model.java# @ 0:bf79fb79ee13
Initial Mercurial check in.
author | samer |
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date | Tue, 17 Jan 2012 17:50:20 +0000 |
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/* * Copyright (c) 2002, Samer Abdallah, King's College London. * All rights reserved. * * This software is provided AS iS and WITHOUT ANY WARRANTY; * without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. */ package samer.models; import samer.core.*; import samer.maths.*; import samer.maths.opt.*; import samer.tools.*; public interface Model { /** return size of vector this model expects */ int getSize(); /** model should begin observing this vector */ void setInput(Vec x); /** should infer values latent variables */ void infer(); /** contract is that getEnergy and getGradient must return correct values for current x after infer and compute has been called, but not necessarily before. :q This is to give model an opportunity to cache values of energy and gradient to avoid repeated computations. */ void compute(); /** return E = -log p(x) */ double getEnergy(); /** return dE/dx */ double [] getGradient(); public void dispose(); /** This presents a more functional interface to the model so that it can be driven by an optimiser. See classes Functionx and MinimiserBase in package samer.maths.opt. */ public Functionx functionx(); /** This represents a training algorithm for a Model Trainer is responsible for counting calls to accumulate() between flushes */ public interface Trainer { /** collect statistics for parameter update */ public void accumulate(); /** weighted accumulate */ public void accumulate(double w); /** use collected stats to update parameters and reset */ public void flush(); /** Must be equivalent to reset(); accumulate(); flush(); but can be optimised for non-batched training */ public void oneshot(); /** reset accumulators without updating parameters */ public void reset(); public void dispose(); } }