library(keras)

FLAGS <- flags(
    flag_numeric("dropout_rate", 0.4)
)

mnist <- dataset_mnist()
x_train <- mnist$train$x
y_train <- mnist$train$y
x_test <- mnist$test$x
y_test <- mnist$test$y

x_train <- array_reshape(x_train, c(nrow(x_train), 784))
x_test <- array_reshape(x_test, c(nrow(x_test), 784))
x_train <- x_train / 255
x_test <- x_test / 255

y_train <- to_categorical(y_train, 10)
y_test <- to_categorical(y_test, 10)

model <- keras_model_sequential()

model %>%
  layer_dense(units = 256, activation = 'relu', input_shape = c(784)) %>%
  layer_dropout(rate = FLAGS$dropout_rate) %>%
  layer_dense(units = 128, activation = 'relu') %>%
  layer_dropout(rate = 0.3) %>%
  layer_dense(units = 10, activation = 'softmax')

model %>% compile(
  loss = 'categorical_crossentropy',
  optimizer = optimizer_rmsprop(),
  metrics = c('accuracy')
)

model %>% fit(
  x_train, y_train,
  epochs = 20, batch_size = 128,
  validation_split = 0.2
)

model %>% evaluate(x_test, y_test)
model %>% predict_classes(x_test)

# everything works fine till above line

export_savedmodel(model, "savedmodel") # Error line

Error in export_savedmodel.keras.engine.training.Model(model, "savedmodel") :
  'export_savedmodel()' is currently unsupported under the TensorFlow Keras implementation, consider using 'tfestimators::keras_model_to_estimator()'

#export_savedmodel(model, "savedmodel") <-- replace this line with below code
tfe_model <- tfestimators::keras_model_to_estimator(model)
export_savedmodel(tfe_model, "savedmodel")

Error in export_savedmodel.tf_estimator(tfe_model, "savedmodel") :
  Currently only classifier and regressor are supported. Please specify a custom serving_input_receiver_fn.