def __init__(self, moniker):
self.moniker = moniker
self.log = VPLogger()
self.model = VW(vw = "/usr/local/bin/vw", \
moniker=moniker, \
logger=self.log, \
**{'passes': 10,
'learning_rate': 15,
'power_t': 1.0, })
class SimpleModel(object):
def __init__(self, moniker):
self.moniker = moniker
self.log = VPLogger()
self.model = VW(vw = "/usr/local/bin/vw", \
moniker=moniker, \
logger=self.log, \
**{'passes': 10,
'learning_rate': 15,
'power_t': 1.0, })
def train(self, instance_stream):
"""
Trains the model on the given data stream.
"""
self.log.info('%s: training' % (self.moniker))
with self.model.training():
seen = 0
for instance in instance_stream:
self.model.push_instance(instance)
seen += 1
if seen % 10000 == 0:
self.log.debug('streamed %d instances...' % seen)
self.log.debug('done streaming.')
self.log.info('%s: trained on %d data points' % (self.moniker, seen))
return self
def predict(self, instance_stream):
self.log.info('%s: predicting' % self.moniker)
instances = []
with self.model.predicting():
seen = 0
for instance in instance_stream:
self.model.push_instance(instance)
instances.append(instance)
seen += 1
self.log.info('%s: predicted for %d data points' % (self.moniker, seen))
predictions = list(self.model.read_predictions_())
if seen != len(predictions):
raise Exception("Number of labels and predictions do not match! (%d vs %d)" % \
(seen, len(predictions)))
return itertools.izip(instances, predictions)
