在Keras中导出每个时期的嵌入

from keras.models import Sequential
from keras.layers import Embedding, Flatten, Dense
from keras.callbacks import ModelCheckpoint

# 创建模型
model = Sequential()
model.add(Embedding(input_dim=1000, output_dim=32, input_length=10))
model.add(Flatten())
model.add(Dense(units=1, activation='sigmoid'))

# 编译模型
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

# 定义回调函数，保存每个时期的嵌入
checkpoint = ModelCheckpoint('embeddings_epoch_{epoch}.h5', save_weights_only=True)

# 训练模型
model.fit(x_train, y_train, epochs=10, callbacks=[checkpoint])