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import numpy
import theano
from theano import tensor
from blocks.bricks import application, Softmax
import error
from model.mlp import FFMLP, Stream
class Model(FFMLP):
def __init__(self, config, **kwargs):
super(Model, self).__init__(config, output_layer=Softmax, **kwargs)
self.classes = theano.shared(numpy.array(config.tgtcls, dtype=theano.config.floatX), name='classes')
@application(outputs=['destination'])
def predict(self, **kwargs):
cls_probas = super(Model, self).predict(**kwargs)
return tensor.dot(cls_probas, self.classes)
@predict.property('inputs')
def predict_inputs(self):
return self.inputs
@application(outputs=['cost'])
def cost(self, **kwargs):
y_hat = self.predict(**kwargs)
y = tensor.concatenate((kwargs['destination_latitude'][:, None],
kwargs['destination_longitude'][:, None]), axis=1)
return error.erdist(y_hat, y).mean()
@cost.property('inputs')
def cost_inputs(self):
return self.inputs + ['destination_latitude', 'destination_longitude']
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