mf_qe_nn_clf.py 文件源码

def build_model(X,dim=128):

    inputs_p = Input(shape=(1,), dtype='int32')

    embed_p = Embedding(
                    num_q,
                    dim,
                    dropout=0.2,
                    input_length=1
                    )(inputs_p)

    inputs_d = Input(shape=(1,), dtype='int32')

    embed_d = Embedding(
                    num_e,
                    dim,
                    dropout=0.2,
                    input_length=1
                    )(inputs_d)


    flatten_p= Flatten()(embed_p)

    flatten_d= Flatten()(embed_d)

    flatten = merge([
                flatten_p,
                flatten_d,
                ],mode='concat')

    fc1 = Dense(512)(flatten)
    fc1 = SReLU()(fc1)
    dp1 = Dropout(0.7)(fc1)

    outputs = Dense(1,activation='sigmoid',name='outputs')(dp1)

    inputs = [
                inputs_p,
                inputs_d,
            ]



    model = Model(input=inputs, output=outputs)
    nadam = Nadam()
    sgd = SGD(lr=1e-3, decay=1e-6, momentum=0.9, nesterov=True)
    model.compile(
                optimizer=nadam,
                loss= 'binary_crossentropy'
              )

    return model