DeepJet_models.py 文件源码

def RecurrenPT(Inputs,nclasses,dropoutRate=-1):

    x_pt = Masking()(Inputs[1])
    x_pt = LSTM(100)(x_pt)
    x = merge( [x_pt, Inputs[0]] , mode='concat')
    x = Dense(200, activation='relu',kernel_initializer='lecun_uniform')(x)
    x = Dense(100, activation='relu',kernel_initializer='lecun_uniform')(x)
    x = Dense(100, activation='relu',kernel_initializer='lecun_uniform')(x)
    x = Dense(100, activation='relu',kernel_initializer='lecun_uniform')(x)
    x = Dense(100, activation='relu',kernel_initializer='lecun_uniform')(x)
    x = Dense(100, activation='relu',kernel_initializer='lecun_uniform')(x)
    x = merge( [x, Inputs[2]] , mode='concat')
    predictions = [Dense(2, activation='linear',init='normal')(x),Dense(nclasses, activation='softmax',kernel_initializer='lecun_uniform')(x)]
    model = Model(inputs=Inputs, outputs=predictions)
    return model