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import numpy
import theano
from theano import tensor
from blocks.bricks.base import lazy
from blocks.bricks import Softmax
from model.rnn import RNN, Stream
class Model(RNN):
@lazy()
def __init__(self, config, **kwargs):
super(Model, self).__init__(config, rec_input_len=4, output_dim=config.tgtcls.shape[0], **kwargs)
self.classes = theano.shared(numpy.array(config.tgtcls, dtype=theano.config.floatX), name='classes')
self.softmax = Softmax()
self.sequences.extend(['latitude_lag', 'longitude_lag'])
self.children.append(self.softmax)
def before_predict_all(self, kwargs):
super(Model, self).before_predict_all(kwargs)
kwargs['latitude_lag'] = tensor.extra_ops.repeat(kwargs['latitude'], 2, axis=0)
kwargs['longitude_lag'] = tensor.extra_ops.repeat(kwargs['longitude'], 2, axis=0)
def process_rto(self, rto):
return tensor.dot(self.softmax.apply(rto), self.classes)
def rec_input(self, latitude, longitude, latitude_lag, longitude_lag, **kwargs):
return (tensor.shape_padright(latitude),
tensor.shape_padright(longitude),
tensor.shape_padright(latitude_lag),
tensor.shape_padright(longitude_lag))
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