Mercurial > pylearn
annotate doc/v2_planning/API_formulas.txt @ 1174:fe6c25eb1e37
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author | pascanur |
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date | Fri, 17 Sep 2010 16:13:58 -0400 |
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1 .. _v2planning_formulas: |
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2 |
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3 Math formulas API |
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4 ================= |
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5 |
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6 Why we need a formulas API |
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7 -------------------------- |
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8 |
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9 Their is a few reasons why having a library of mathematical formula for theano is a good reason: |
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10 |
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11 * Some formula have some special thing needed for the gpu. |
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12 * Sometimes we need to cast to floatX... |
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13 * Some formula have numerical stability problem. |
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14 * Some formula gradiant have numerical stability problem. (Happen more frequently then the previous ones) |
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15 * If theano don't always do some stability optimization, we could do it manually in the formulas |
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16 * Some formula as complex to implement and take many try to do correctly. |
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17 * Can mimic the hierarchy of other library to ease the migration to theano |
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18 |
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19 Having a library help in that we solve those problem only once. |
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20 |
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21 What is a formula |
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22 ----------------- |
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23 |
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24 We define formulas as something that don't have a state. They are implemented as |
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25 python function that take theano variable as input and they output theano |
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26 variable. If you want state, look at what the others commities will do. |
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27 |
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28 Formulas documentation |
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29 ---------------------- |
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30 |
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31 We must respect what the coding commitee have set for the docstring of the file and of the function. |
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32 |
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33 * A latex mathematical description of the formulas(for picture representation in generated documentation) |
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34 * Tags(for searching): |
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35 * a list of lower level fct used |
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36 * category(name of the submodule itself) |
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37 * Tell if we did some work to make it more numerical stable. Do theano do the optimization needed? |
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38 * Tell if the grad is numericaly stable? Do theano do the optimization needed? |
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39 * Tell if work/don't/unknow on gpu. |
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40 * Tell alternate name |
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41 * Tell the domaine, range of the input/output(range should use the english notation of including or excluding) |
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42 |
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43 Proposed hierarchy |
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44 ------------------ |
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45 |
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46 Here is the proposed hierarchy for formulas: |
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47 |
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48 * pylearn.formulas.costs: generic / common cost functions, e.g. various cross-entropies, squared error, |
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49 abs. error, various sparsity penalties (L1, Student) |
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50 * pylearn.formulas.regularization: formulas for regularization |
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51 * pylearn.formulas.linear: formulas for linear classifier, linear regression, factor analysis, PCA |
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52 * pylearn.formulas.nnet: formulas for building layers of various kinds, various activation functions, |
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53 layers which could be plugged with various costs & penalties, and stacked |
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54 * pylearn.formulas.ae: formulas for auto-encoders and denoising auto-encoder variants |
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55 * pylearn.formulas.noise: formulas for corruption processes |
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56 * pylearn.formulas.rbm: energies, free energies, conditional distributions, Gibbs sampling |
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57 * pylearn.formulas.trees: formulas for decision trees |
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58 * pylearn.formulas.boosting: formulas for boosting variants |
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59 * pylearn.formulas.maths for other math formulas |
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60 * pylearn.formulas.scipy.stats: example to implement the same interface as existing lib |
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61 |
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62 etc. |
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63 |
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64 Example |
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65 ------- |
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66 .. code-block:: python |
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67 |
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68 """ |
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69 This script defines a few often used cost functions. |
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70 """ |
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71 import theano |
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72 import theano.tensor as T |
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73 from tags import tags |
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74 |
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75 @tags('cost','binary','cross-entropy') |
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76 def binary_crossentropy(output, target): |
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77 """ Compute the crossentropy of binary output wrt binary target. |
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78 |
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79 .. math:: |
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80 L_{CE} \equiv t\log(o) + (1-t)\log(1-o) |
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81 |
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82 :type output: Theano variable |
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83 :param output: Binary output or prediction :math:`\in[0,1]` |
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84 :type target: Theano variable |
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85 :param target: Binary target usually :math:`\in\{0,1\}` |
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86 """ |
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87 return -(target * tensor.log(output) + (1.0 - target) * tensor.log(1.0 - output)) |
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88 |
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89 |
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90 TODO |
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91 ---- |
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92 * define a list of search tag to start with |
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93 * Add to the html page a list of the tag and a list of each fct associated to them. |
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94 * move existing formulas to pylearn as examples and add other basics ones. |
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95 * theano.tensor.nnet will probably be copied to pylearn.formulas.nnet and depricated. |
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96 |