pylearn: learner.py annotate

annotate learner.py @ 211:bd728c83faff

in __get__, problem if the i.stop was None, i being the slice, added one line replacing None by the len(self)

author	Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
date	Wed, 21 May 2008 17:39:30 -0400
parents	50a8302addaf
children	14b9779622f9

rev	line source
211 bd728c83faff in __get__, problem if the i.stop was None, i being the slice, added one line replacing None by the len(self) Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca> parents: 209 diff changeset	1
1 2cd82666b9a7 Added statscollector and started writing dataset and learner. bengioy@esprit.iro.umontreal.ca parents: 0 diff changeset	2
172 fb4837eed1a6 fixed import of AbstractFunction Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 167 diff changeset	3 from exceptions import *
209 50a8302addaf template statscollector Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 193 diff changeset	4 from dataset import AttributesHolder
180 2698c0feeb54 mlp seems to work! Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 177 diff changeset	5
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	6 class LearningAlgorithm(object):
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	7 """
f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	8 Base class for learning algorithms, provides an interface
1 2cd82666b9a7 Added statscollector and started writing dataset and learner. bengioy@esprit.iro.umontreal.ca parents: 0 diff changeset	9 that allows various algorithms to be applicable to generic learning
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	10 algorithms. It is only given here to define the expected semantics.
1 2cd82666b9a7 Added statscollector and started writing dataset and learner. bengioy@esprit.iro.umontreal.ca parents: 0 diff changeset	11
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	12 A L{Learner} can be seen as a learning algorithm, a function that when
135 0d8e721cc63c Fixed bugs in dataset to make test_mlp.py work Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 134 diff changeset	13 applied to training data returns a learned function (which is an object that
0d8e721cc63c Fixed bugs in dataset to make test_mlp.py work Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 134 diff changeset	14 can be applied to other data and return some output data).
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	15
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	16 There are two main ways of using a learning algorithms, and some learning
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	17 algorithms only support one of them. The first is the way of the standard
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	18 machine learning framework, in which a learning algorithm is applied
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	19 to a training dataset,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	20
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	21 model = learning_algorithm(training_set)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	22
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	23 resulting in a fully trained model that can be applied to another dataset:
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	24
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	25 output_dataset = model(input_dataset)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	26
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	27 Note that the application of a dataset has no side-effect on the model.
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	28 In that example, the training set may for example have 'input' and 'target'
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	29 fields while the input dataset may have only 'input' (or both 'input' and
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	30 'target') and the output dataset would contain some default output fields defined
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	31 by the learning algorithm (e.g. 'output' and 'error').
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	32
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	33 The second way of using a learning algorithm is in the online or
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	34 adaptive framework, where the training data are only revealed in pieces
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	35 (maybe one example or a batch of example at a time):
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	36
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	37 model = learning_algorithm()
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	38
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	39 results in a fresh model. The model can be adapted by presenting
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	40 it with some training data,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	41
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	42 model.update(some_training_data)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	43 ...
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	44 model.update(some_more_training_data)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	45 ...
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	46 model.update(yet_more_training_data)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	47
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	48 and at any point one can use the model to perform some computation:
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	49
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	50 output_dataset = model(input_dataset)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	51
1 2cd82666b9a7 Added statscollector and started writing dataset and learner. bengioy@esprit.iro.umontreal.ca parents: 0 diff changeset	52 """
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	53
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	54 def __init__(self): pass
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	55
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	56 def __call__(self, training_dataset=None):
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	57 """
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	58 Return a LearnerModel, either fresh (if training_dataset is None) or fully trained (otherwise).
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	59 """
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	60 raise AbstractFunction()
1 2cd82666b9a7 Added statscollector and started writing dataset and learner. bengioy@esprit.iro.umontreal.ca parents: 0 diff changeset	61
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	62 class LearnerModel(AttributesHolder):
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	63 """
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	64 LearnerModel is a base class for models returned by instances of a LearningAlgorithm subclass.
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	65 It is only given here to define the expected semantics.
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	66 """
10 80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	67 def __init__(self):
80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	68 pass
80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	69
14 5ede27026e05 Working on gradient_based_learner bengioy@bengiomac.local parents: 13 diff changeset	70 def update(self,training_set,train_stats_collector=None):
10 80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	71 """
80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	72 Continue training a learner, with the evidence provided by the given training set.
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	73 Hence update can be called multiple times. This is the main method used for training in the
10 80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	74 on-line setting or the sequential (Bayesian or not) settings.
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	75
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	76 This function has as side effect that self(data) will behave differently,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	77 according to the adaptation achieved by update().
75 90e4c0784d6e Added draft of LinearRegression learner bengioy@bengiomac.local parents: 20 diff changeset	78
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	79 The user may optionally provide a training L{StatsCollector} that is used to record
75 90e4c0784d6e Added draft of LinearRegression learner bengioy@bengiomac.local parents: 20 diff changeset	80 some statistics of the outputs computed during training. It is update(d) during
90e4c0784d6e Added draft of LinearRegression learner bengioy@bengiomac.local parents: 20 diff changeset	81 training.
10 80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	82 """
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	83 raise AbstractFunction()
10 80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	84
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	85 def __call__(self,input_dataset,output_fieldnames=None,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	86 test_stats_collector=None,copy_inputs=False,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	87 put_stats_in_output_dataset=True,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	88 output_attributes=[]):
10 80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	89 """
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	90 A trained or partially trained L{Model} can be used with
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	91 with one or more calls to it. The argument is an input L{DataSet} (possibly
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	92 containing a single example) and the result is an output L{DataSet} of the same length.
128 ee5507af2c60 minor edits Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 126 diff changeset	93 If output_fieldnames is specified, it may be use to indicate which fields should
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	94 be constructed in the output L{DataSet} (for example ['output','classification_error']).
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	95 Otherwise, some default output fields are produced (possibly depending on the input
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	96 fields available in the input_dataset).
20 266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works. bengioy@bengiomac.local parents: 14 diff changeset	97 Optionally, if copy_inputs, the input fields (of the input_dataset) can be made
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	98 visible in the output L{DataSet} returned by this method.
128 ee5507af2c60 minor edits Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 126 diff changeset	99 Optionally, attributes of the learner can be copied in the output dataset,
ee5507af2c60 minor edits Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 126 diff changeset	100 and statistics computed by the stats collector also put in the output dataset.
ee5507af2c60 minor edits Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 126 diff changeset	101 Note the distinction between fields (which are example-wise quantities, e.g. 'input')
ee5507af2c60 minor edits Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 126 diff changeset	102 and attributes (which are not, e.g. 'regularization_term').
110 8fa1ef2411a0 Worked on OneShotTLearner and implementation of LinearRegression bengioy@bengiomac.local parents: 109 diff changeset	103 """
8fa1ef2411a0 Worked on OneShotTLearner and implementation of LinearRegression bengioy@bengiomac.local parents: 109 diff changeset	104 raise AbstractFunction()

Mercurial > pylearn

annotate learner.py @ 211:bd728c83faff