ift6266: code_tutoriel/logistic

annotate code_tutoriel/logistic_cg.py @ 266:1e4e60ddadb1

Merge. Ah, et dans le dernier commit, j'avais oublié de mentionner que j'ai ajouté du code pour gérer l'isolation de différents clones pour rouler des expériences et modifier le code en même temps.

author	fsavard
date	Fri, 19 Mar 2010 10:56:16 -0400
parents	4bc5eeec6394
children

rev	line source
165 4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	1 """
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	2 This tutorial introduces logistic regression using Theano and conjugate
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	3 gradient descent.
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	4
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	5 Logistic regression is a probabilistic, linear classifier. It is parametrized
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	6 by a weight matrix :math:`W` and a bias vector :math:`b`. Classification is
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	7 done by projecting data points onto a set of hyperplanes, the distance to
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	8 which is used to determine a class membership probability.
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	9
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	10 Mathematically, this can be written as:
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	11
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	12 .. math::
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	13 P(Y=i\|x, W,b) &= softmax_i(W x + b) \\
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	14 &= \frac {e^{W_i x + b_i}} {\sum_j e^{W_j x + b_j}}
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	15
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	16
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	17 The output of the model or prediction is then done by taking the argmax of
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	18 the vector whose i'th element is P(Y=i\|x).
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	19
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	20 .. math::
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	21
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	22 y_{pred} = argmax_i P(Y=i\|x,W,b)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	23
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	24
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	25 This tutorial presents a stochastic gradient descent optimization method
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	26 suitable for large datasets, and a conjugate gradient optimization method
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	27 that is suitable for smaller datasets.
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	28
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	29
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	30 References:
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	31
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	32 - textbooks: "Pattern Recognition and Machine Learning" -
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	33 Christopher M. Bishop, section 4.3.2
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	34
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	35
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	36 """
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	37 __docformat__ = 'restructedtext en'
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	38
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	39
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	40 import numpy, time, cPickle, gzip
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	41
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	42 import theano
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	43 import theano.tensor as T
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	44
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	45
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	46 class LogisticRegression(object):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	47 """Multi-class Logistic Regression Class
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	48
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	49 The logistic regression is fully described by a weight matrix :math:`W`
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	50 and bias vector :math:`b`. Classification is done by projecting data
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	51 points onto a set of hyperplanes, the distance to which is used to
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	52 determine a class membership probability.
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	53 """
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	54
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	55
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	56
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	57
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	58 def __init__(self, input, n_in, n_out):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	59 """ Initialize the parameters of the logistic regression
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	60
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	61 :type input: theano.tensor.TensorType
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	62 :param input: symbolic variable that describes the input of the
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	63 architecture ( one minibatch)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	64
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	65 :type n_in: int
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	66 :param n_in: number of input units, the dimension of the space in
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	67 which the datapoint lies
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	68
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	69 :type n_out: int
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	70 :param n_out: number of output units, the dimension of the space in
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	71 which the target lies
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	72
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	73 """
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	74
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	75 # initialize theta = (W,b) with 0s; W gets the shape (n_in, n_out),
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	76 # while b is a vector of n_out elements, making theta a vector of
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	77 # n_in*n_out + n_out elements
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	78 self.theta = theano.shared( value = numpy.zeros(n_in*n_out+n_out, dtype = theano.config.floatX) )
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	79 # W is represented by the fisr n_in*n_out elements of theta
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	80 self.W = self.theta[0:n_in*n_out].reshape((n_in,n_out))
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	81 # b is the rest (last n_out elements)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	82 self.b = self.theta[n_inn_out:n_inn_out+n_out]
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	83
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	84
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	85 # compute vector of class-membership probabilities in symbolic form
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	86 self.p_y_given_x = T.nnet.softmax(T.dot(input, self.W)+self.b)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	87
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	88 # compute prediction as class whose probability is maximal in
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	89 # symbolic form
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	90 self.y_pred=T.argmax(self.p_y_given_x, axis=1)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	91
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	92
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	93
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	94
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	95
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	96 def negative_log_likelihood(self, y):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	97 """Return the negative log-likelihood of the prediction of this model
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	98 under a given target distribution.
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	99
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	100 .. math::
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	101
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	102 \frac{1}{\|\mathcal{D}\|}\mathcal{L} (\theta=\{W,b\}, \mathcal{D}) =
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	103 \frac{1}{\|\mathcal{D}\|}\sum_{i=0}^{\|\mathcal{D}\|} \log(P(Y=y^{(i)}\|x^{(i)}, W,b)) \\
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	104 \ell (\theta=\{W,b\}, \mathcal{D})
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	105
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	106 :type y: theano.tensor.TensorType
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	107 :param y: corresponds to a vector that gives for each example the
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	108 correct label
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	109 """
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	110 return -T.mean(T.log(self.p_y_given_x)[T.arange(y.shape[0]),y])
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	111
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	112
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	113
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	114
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	115
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	116 def errors(self, y):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	117 """Return a float representing the number of errors in the minibatch
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	118 over the total number of examples of the minibatch
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	119
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	120 :type y: theano.tensor.TensorType
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	121 :param y: corresponds to a vector that gives for each example
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	122 the correct label
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	123 """
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	124
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	125 # check if y has same dimension of y_pred
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	126 if y.ndim != self.y_pred.ndim:
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	127 raise TypeError('y should have the same shape as self.y_pred',
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	128 ('y', target.type, 'y_pred', self.y_pred.type))
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	129 # check if y is of the correct datatype
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	130 if y.dtype.startswith('int'):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	131 # the T.neq operator returns a vector of 0s and 1s, where 1
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	132 # represents a mistake in prediction
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	133 return T.mean(T.neq(self.y_pred, y))
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	134 else:
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	135 raise NotImplementedError()
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	136
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	137
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	138
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	139
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	140
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	141
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	142
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	143 def cg_optimization_mnist( n_epochs=50, mnist_pkl_gz='mnist.pkl.gz' ):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	144 """Demonstrate conjugate gradient optimization of a log-linear model
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	145
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	146 This is demonstrated on MNIST.
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	147
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	148 :type n_epochs: int
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	149 :param n_epochs: number of epochs to run the optimizer
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	150
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	151 :type mnist_pkl_gz: string
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	152 :param mnist_pkl_gz: the path of the mnist training file from
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	153 http://www.iro.umontreal.ca/~lisa/deep/data/mnist/mnist.pkl.gz
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	154
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	155 """
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	156 #############
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	157 # LOAD DATA #
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	158 #############
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	159 print '... loading data'
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	160
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	161 # Load the dataset
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	162 f = gzip.open(mnist_pkl_gz,'rb')
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	163 train_set, valid_set, test_set = cPickle.load(f)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	164 f.close()
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	165
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	166 def shared_dataset(data_xy):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	167 """ Function that loads the dataset into shared variables
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	168
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	169 The reason we store our dataset in shared variables is to allow
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	170 Theano to copy it into the GPU memory (when code is run on GPU).
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	171 Since copying data into the GPU is slow, copying a minibatch everytime
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	172 is needed (the default behaviour if the data is not in a shared
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	173 variable) would lead to a large decrease in performance.
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	174 """
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	175 data_x, data_y = data_xy
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	176 shared_x = theano.shared(numpy.asarray(data_x, dtype=theano.config.floatX))
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	177 shared_y = theano.shared(numpy.asarray(data_y, dtype=theano.config.floatX))
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	178 # When storing data on the GPU it has to be stored as floats
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	179 # therefore we will store the labels as ``floatX`` as well
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	180 # (``shared_y`` does exactly that). But during our computations
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	181 # we need them as ints (we use labels as index, and if they are
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	182 # floats it doesn't make sense) therefore instead of returning
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	183 # ``shared_y`` we will have to cast it to int. This little hack
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	184 # lets ous get around this issue
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	185 return shared_x, T.cast(shared_y, 'int32')
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	186
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	187
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	188 test_set_x, test_set_y = shared_dataset(test_set)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	189 valid_set_x, valid_set_y = shared_dataset(valid_set)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	190 train_set_x, train_set_y = shared_dataset(train_set)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	191
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	192 batch_size = 600 # size of the minibatch
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	193
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	194 n_train_batches = train_set_x.value.shape[0] / batch_size
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	195 n_valid_batches = valid_set_x.value.shape[0] / batch_size
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	196 n_test_batches = test_set_x.value.shape[0] / batch_size
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	197
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	198
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	199 ishape = (28,28) # this is the size of MNIST images
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	200 n_in = 28*28 # number of input units
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	201 n_out = 10 # number of output units
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	202
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	203
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	204 ######################
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	205 # BUILD ACTUAL MODEL #
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	206 ######################
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	207 print '... building the model'
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	208
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	209 # allocate symbolic variables for the data
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	210 minibatch_offset = T.lscalar() # offset to the start of a [mini]batch
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	211 x = T.matrix() # the data is presented as rasterized images
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	212 y = T.ivector() # the labels are presented as 1D vector of
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	213 # [int] labels
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	214
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	215
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	216 # construct the logistic regression class
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	217 classifier = LogisticRegression( input=x, n_in=28*28, n_out=10)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	218
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	219 # the cost we minimize during training is the negative log likelihood of
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	220 # the model in symbolic format
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	221 cost = classifier.negative_log_likelihood(y).mean()
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	222
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	223 # compile a theano function that computes the mistakes that are made by
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	224 # the model on a minibatch
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	225 test_model = theano.function([minibatch_offset], classifier.errors(y),
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	226 givens={
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	227 x:test_set_x[minibatch_offset:minibatch_offset+batch_size],
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	228 y:test_set_y[minibatch_offset:minibatch_offset+batch_size]})
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	229
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	230 validate_model = theano.function([minibatch_offset],classifier.errors(y),
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	231 givens={
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	232 x:valid_set_x[minibatch_offset:minibatch_offset+batch_size],
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	233 y:valid_set_y[minibatch_offset:minibatch_offset+batch_size]})
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	234
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	235 # compile a thenao function that returns the cost of a minibatch
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	236 batch_cost = theano.function([minibatch_offset], cost,
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	237 givens= {
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	238 x : train_set_x[minibatch_offset:minibatch_offset+batch_size],
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	239 y : train_set_y[minibatch_offset:minibatch_offset+batch_size]})
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	240
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	241
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	242
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	243 # compile a theano function that returns the gradient of the minibatch
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	244 # with respect to theta
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	245 batch_grad = theano.function([minibatch_offset], T.grad(cost,classifier.theta),
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	246 givens= {
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	247 x : train_set_x[minibatch_offset:minibatch_offset+batch_size],
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	248 y : train_set_y[minibatch_offset:minibatch_offset+batch_size]})
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	249
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	250
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	251 # creates a function that computes the average cost on the training set
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	252 def train_fn(theta_value):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	253 classifier.theta.value = theta_value
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	254 train_losses = [batch_cost(i*batch_size) for i in xrange(n_train_batches)]
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	255 return numpy.mean(train_losses)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	256
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	257 # creates a function that computes the average gradient of cost with
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	258 # respect to theta
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	259 def train_fn_grad(theta_value):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	260 classifier.theta.value = theta_value
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	261 grad = batch_grad(0)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	262 for i in xrange(1,n_train_batches):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	263 grad += batch_grad(i*batch_size)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	264 return grad/n_train_batches
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	265
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	266
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	267 validation_scores = [float('inf'), 0]
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	268
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	269 # creates the validation function
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	270 def callback(theta_value):
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	271 classifier.theta.value = theta_value
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	272 #compute the validation loss
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	273 validation_losses = [validate_model(i*batch_size) for i in xrange(n_valid_batches)]
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	274 this_validation_loss = numpy.mean(validation_losses)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	275 print('validation error %f %%' % (this_validation_loss*100.,))
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	276
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	277 # check if it is better then best validation score got until now
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	278 if this_validation_loss < validation_scores[0]:
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	279 # if so, replace the old one, and compute the score on the
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	280 # testing dataset
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	281 validation_scores[0] = this_validation_loss
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	282 test_loses = [test_model(i*batch_size) for i in xrange(n_test_batches)]
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	283 validation_scores[1] = numpy.mean(test_loses)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	284
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	285 ###############
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	286 # TRAIN MODEL #
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	287 ###############
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	288
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	289 # using scipy conjugate gradient optimizer
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	290 import scipy.optimize
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	291 print ("Optimizing using scipy.optimize.fmin_cg...")
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	292 start_time = time.clock()
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	293 best_w_b = scipy.optimize.fmin_cg(
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	294 f = train_fn,
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	295 x0 = numpy.zeros((n_in+1)*n_out, dtype=x.dtype),
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	296 fprime = train_fn_grad,
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	297 callback = callback,
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	298 disp = 0,
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	299 maxiter = n_epochs)
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	300 end_time = time.clock()
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	301 print(('Optimization complete with best validation score of %f %%, with '
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	302 'test performance %f %%') %
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	303 (validation_scores[0]100., validation_scores[1]100.))
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	304
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	305 print ('The code ran for %f minutes' % ((end_time-start_time)/60.))
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	306
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	307
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	308 if __name__ == '__main__':
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	309 cg_optimization_mnist()
4bc5eeec6394 Updating the tutorial code to the latest revisions. Dumitru Erhan <dumitru.erhan@gmail.com> parents: diff changeset	310

Mercurial > ift6266

annotate code_tutoriel/logistic_cg.py @ 266:1e4e60ddadb1