def classify(tweet, t_mask, params, n_classes, n_chars):
# tweet embedding
emb_layer = tweet2vec(tweet, t_mask, params, n_chars)
# Dense layer for classes
l_dense = lasagne.layers.DenseLayer(emb_layer, n_classes, W=params['W_cl'], b=params['b_cl'], nonlinearity=lasagne.nonlinearities.softmax)
return lasagne.layers.get_output(l_dense), lasagne.layers.get_output(emb_layer)
def classify(tweet, t_mask, params, n_classes, n_chars):
# tweet embedding
emb_layer = tweet2vec(tweet, t_mask, params, n_chars)
# Dense layer for classes
l_dense = lasagne.layers.DenseLayer(emb_layer, n_classes, W=params['W_cl'], b=params['b_cl'], nonlinearity=lasagne.nonlinearities.softmax)
return lasagne.layers.get_output(l_dense), lasagne.layers.get_output(emb_layer)