pylearn: learner.py annotate

annotate learner.py @ 203:80731832c62b

Automated merge with ssh://p-omega1@lgcm.iro.umontreal.ca/tlearn

author	Frederic Bastien <bastienf@iro.umontreal.ca>
date	Thu, 15 May 2008 15:21:00 -0400
parents	cb6b945acf5a
children	50a8302addaf

rev	line source
1 2cd82666b9a7 Added statscollector and started writing dataset and learner. bengioy@esprit.iro.umontreal.ca parents: 0 diff changeset	1
172 fb4837eed1a6 fixed import of AbstractFunction Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 167 diff changeset	2 from exceptions import *
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	3
180 2698c0feeb54 mlp seems to work! Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 177 diff changeset	4
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	5 class LearningAlgorithm(object):
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	6 """
f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	7 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	8 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	9 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	10
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	11 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	12 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	13 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	14
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	15 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	16 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	17 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	18 to a training dataset,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	19
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	20 model = learning_algorithm(training_set)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	21
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	22 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	23
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	24 output_dataset = model(input_dataset)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	25
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	26 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	27 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	28 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	29 '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	30 by the learning algorithm (e.g. 'output' and 'error').
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	31
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	32 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	33 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	34 (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	35
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	36 model = learning_algorithm()
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	37
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	38 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	39 it with some training data,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	40
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	41 model.update(some_training_data)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	42 ...
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	43 model.update(some_more_training_data)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	44 ...
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	45 model.update(yet_more_training_data)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	46
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	47 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	48
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	49 output_dataset = model(input_dataset)
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	50
1 2cd82666b9a7 Added statscollector and started writing dataset and learner. bengioy@esprit.iro.umontreal.ca parents: 0 diff changeset	51 """
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	52
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	53 def __init__(self): pass
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	54
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	55 def __call__(self, training_dataset=None):
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	56 """
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	57 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	58 """
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	59 raise AbstractFunction()
1 2cd82666b9a7 Added statscollector and started writing dataset and learner. bengioy@esprit.iro.umontreal.ca parents: 0 diff changeset	60
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	61 class LearnerModel(AttributesHolder):
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	62 """
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	63 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	64 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	65 """
10 80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	66 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	67 pass
80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	68
14 5ede27026e05 Working on gradient_based_learner bengioy@bengiomac.local parents: 13 diff changeset	69 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	70 """
80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	71 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	72 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	73 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	74
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	75 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	76 according to the adaptation achieved by update().
75 90e4c0784d6e Added draft of LinearRegression learner bengioy@bengiomac.local parents: 20 diff changeset	77
132 f6505ec32dc3 Updated documentation slightly Joseph Turian <turian@gmail.com> parents: 131 diff changeset	78 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	79 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	80 training.
10 80bf5492e571 Rewrote learner.py according to the specs in the wiki for learners. bengioy@esprit.iro.umontreal.ca parents: 1 diff changeset	81 """
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	82 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	83
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	84 def __call__(self,input_dataset,output_fieldnames=None,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	85 test_stats_collector=None,copy_inputs=False,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	86 put_stats_in_output_dataset=True,
cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	87 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	88 """
193 cb6b945acf5a Complete redesign of learner... Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 180 diff changeset	89 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	90 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	91 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	92 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	93 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	94 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	95 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	96 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	97 visible in the output L{DataSet} returned by this method.
128 ee5507af2c60 minor edits Yoshua Bengio <bengioy@iro.umontreal.ca> parents: 126 diff changeset	98 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	99 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	100 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	101 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	102 """
8fa1ef2411a0 Worked on OneShotTLearner and implementation of LinearRegression bengioy@bengiomac.local parents: 109 diff changeset	103 raise AbstractFunction()

Mercurial > pylearn

annotate learner.py @ 203:80731832c62b