self.embed = Sequential([Embedding(9488,output_dim = 512,input_length = 14),
激活('relu'),
辍学(0.5)],名称= 'embed.0')

inputs_bedding =输入(形状=(10,))
xt = self.embed(inputs_bedding)

=============================
keras_model.save('temp.h5')
使用h5py.File('temp.h5','a')作为f:
model_weights = f ['model_weights']
params = util.dig_to_params(model_weights [layer])

def dig_to_params(keras_h5_layer):
而不是_contains_weights(keras_h5_layer):
keras_h5_layer = keras_h5_layer [list(keras_h5_layer.keys())[0]]

return keras_h5_layer <br>

错误:keras_h5_layer = keras_h5_layer [list(keras_h5_layer.keys())[0]]
AttributeError:'Dataset'对象没有属性'keys'