Deep Learning with R Cookbook

How to do it...

In this section, we will use the same simulated dataset that we created in the previous section of this recipe, Sequential API. Here, we will create a multi-output functional model:

1. Let's start by importing the required library and create an input layer:

library(keras)# input layerinputs <- layer_input(shape = c(784))

2. Next, we need to define two outputs:

predictions1 <- inputs %>% layer_dense(units = 8)%>% layer_activation('relu') %>% layer_dense(units = 1,name = "pred_1")predictions2 <- inputs %>% layer_dense(units = 16)%>% layer_activation('tanh') %>% layer_dense(units = 1,name = "pred_2")

3. Now, we need to define a functional Keras model:

model_functional = keras_model(inputs = inputs,outputs = c(predictions1,predictions2)) ...