keras self attention实例

以下是使用 Keras 实现 self-attention 的示例代码：

from keras.models import Model
from keras.layers import Input, Dense, Dropout, Embedding, LSTM, Bidirectional, TimeDistributed
from keras_self_attention import SeqSelfAttention

input_layer = Input(shape=(MAX_SEQUENCE_LENGTH,))
embedding_layer = Embedding(input_dim=VOCAB_SIZE, output_dim=EMBEDDING_DIM)(input_layer)
lstm_layer = Bidirectional(LSTM(units=LSTM_UNITS, return_sequences=True))(embedding_layer)
attention_layer = SeqSelfAttention(attention_activation='sigmoid')(lstm_layer)
output_layer = TimeDistributed(Dense(units=NUM_CLASSES, activation='softmax'))(attention_layer)

model = Model(inputs=input_layer, outputs=output_layer)
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])

这个模型使用了 LSTM 来进行序列处理，然后使用了 SeqSelfAttention 层来实现 self-attention。其中，attention_activation 参数指定了激活函数，这里使用了 sigmoid。最后的输出层使用了 TimeDistributed 层，用于在序列上对每个时间步进行分类。