In [1]:

    

from lstm import Lstm, LstmMiniBatch
import theano.tensor as T


    

In [2]:

    

s = {'emb_dimension' : 50,
    'n_hidden' : 100,
    'n_out' : 27, 
    'window' : 2,
    'lr' : 0.005}
possize = 100
vocsize = 9000
nclasses = 27


    

In [3]:

    

lstm = Lstm(ne = vocsize,
                   de = s['emb_dimension'],
                   n_lstm = s['n_hidden'],
                   n_out = nclasses, 
                   cs = s['window'],
                   npos = possize, 
                   lr=s['lr'], 
                   single_output=True, 
                   output_activation=T.nnet.softmax, 
                   cost_function='nll')


    

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