R kera声明多个输出

library(keras)

# 定义模型
model <- keras_model_sequential()

# 添加输入层和隐藏层
model %>%
  layer_dense(units = 64, activation = "relu", input_shape = c(100)) %>%
  layer_dense(units = 64, activation = "relu")

# 添加第一个输出层
output1 <- model %>%
  layer_dense(units = 1, activation = "sigmoid")

# 添加第二个输出层
output2 <- model %>%
  layer_dense(units = 10, activation = "softmax")

# 编译模型
model %>% compile(
  optimizer = "rmsprop",
  loss = list(
    output1 = "binary_crossentropy",
    output2 = "categorical_crossentropy"
  ),
  metrics = list(
    output1 = "accuracy",
    output2 = "accuracy"
  )
)

# 训练模型
model %>% fit(
  x_train,
  list(y_train1, y_train2),
  epochs = 10,
  batch_size = 32
)