class Net2:
    @staticmethod
    def build_cat_branch(inputs,category_size):
        x = TimeDistributed(Dense(category_size))(inputs)
        x = Activation('softmax', name="cat_output")(x)
        return x

    @staticmethod
    def build_t_branch(inputs):
        x = TimeDistributed(Dense(1, activation='relu', name="t_output"))(inputs)
        return x

    @staticmethod
    def build_full_model(timestep_len,hidden_size,category_size,num_features,dropout,rec_drop):
        inputs = Input(shape=(timestep_len,num_features),name="Input")
        bn = BatchNormalization()(inputs)
        lstm = LSTM(hidden_size, return_sequences=True, dropout=dropout, recurrent_dropout=rec_drop,name="LSTM")(bn)
        bn2 = BatchNormalization()(lstm)
        cat_branch = Net2.build_cat_branch(bn2,category_size)
        t_branch = Net2.build_t_branch(bn2)
        model = Model(inputs=inputs,outputs=[cat_branch,t_branch],name="Net2")
        return model