gru_avg.py 文件源码

def fGRU_avg(MAX_NB_WORDS, MAX_WORDS, MAX_SENTS, EMBEDDING_DIM, WORDGRU, embedding_matrix, DROPOUTPER):
    wordInputs = Input(shape=(MAX_SENTS+1, MAX_WORDS), name="wordInputs", dtype='float32')

    wordInp = Flatten()(wordInputs)

    wordEmbedding = Embedding(MAX_NB_WORDS, EMBEDDING_DIM, weights=[embedding_matrix], mask_zero=False, trainable=True, name='wordEmbedding')(wordInp) 

    hij = Bidirectional(GRU(WORDGRU, return_sequences=True), name='gru1')(wordEmbedding)

    head = GlobalAveragePooling1D()(hij) 

    v6 = Dense(1, activation="sigmoid", name="dense")(head)

    model = Model(inputs=[wordInputs] , outputs=[v6])
    model.compile(loss='binary_crossentropy', optimizer='rmsprop', metrics=['accuracy'])

    return model