... # the settings and define data provider is omitted. DICT_DIM = 3000 # dictionary dimension. word_ids = data_layer('word_ids', size=DICT_DIM)
emb = embedding_layer( input=word_ids, size=256, param_attr=ParamAttr(sparse_update=True))
emb_sum = pooling_layer(input=emb, pooling_type=SumPooling()) predict = fc_layer(input=emb_sum, size=DICT_DIM, act=Softmax())
outputs( classification_cost( input=predict, label=data_layer( 'label', size=DICT_DIM)))
