mlp 如何加载 doc2vec（ .d2c）模型数据进行训练

Question

mlp模型如下：

def MySimpleMLP(feature=700, vec_size=50):
    auc_roc = LSTM.as_keras_metric(tf.compat.v1.metrics.auc)

    model = Sequential()

    model.add(Flatten())
    model.add(Dense(32, activation='relu', input_shape=(52,)))
    model.add(Dropout(0.2))
    model.add(Dense(32, activation='relu'))

    model.add(Dropout(0.2))
    model.add(Dense(1, activation='softmax'))

    # compile model
    model.compile(loss="binary_crossentropy", optimizer="adam", metrics=[auc_roc])
    return model

训练函数如下：

model.fit(trainData, trainLabel, validation_split=0.2, epochs=10, batch_size=64, verbose=2)

do2vec模型是基于 imdb_50.d2v。
跪求各位大佬。

Answer 1

https://zhuanlan.zhihu.com/p/30597931