class SimpleModel(object):
def __init__(self, moniker):
self.moniker = moniker
self.model = VW(moniker=moniker, \
**{'passes': 10,
'learning_rate': 15,
'power_t': 1.0, })
def train(self, instance_stream):
"""
Trains the model on the given data stream.
"""
print '%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:
print 'streamed %d instances...' % seen
print 'done streaming.'
print '%s: trained on %d data points' % (self.moniker, seen)
return self
def predict_library(self, instance_stream):
print '%s: predicting' % self.moniker
with self.model.predicting_library():
seen = 0
for instance in instance_stream:
yield instance, self.model.push_instance(instance)
seen += 1
print '%s: predicted for %d data points' % (self.moniker, seen)
def predict(self, instance_stream):
print '%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
print '%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)
class SimpleModel(object):
def __init__(self, moniker):
self.moniker = moniker
self.model = VW(moniker=moniker, \
**{'passes': 10,
'learning_rate': 15,
'power_t': 1.0, })
def train(self, instance_stream):
"""
Trains the model on the given data stream.
"""
print('%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:
print('streamed %d instances...' % seen)
print('done streaming.')
print('%s: trained on %d data points' % (self.moniker, seen))
return self
def predict_library(self, instance_stream):
print('%s: predicting' % self.moniker)
with self.model.predicting_library():
seen = 0
for instance in instance_stream:
yield instance, self.model.push_instance(instance)
seen += 1
print('%s: predicted for %d data points' % (self.moniker, seen))
def predict(self, instance_stream):
print('%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
print('%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 zip(instances, predictions)
