Models for the IMDB data example

original_model <- keras_model_sequential() %>% 
  layer_dense(units = 16, activation = "relu", input_shape = c(10000)) %>% 
  layer_dense(units = 16, activation = "relu") %>% 
  layer_dense(units = 1, activation = "sigmoid")

smaller_model <- keras_model_sequential() %>% 
  layer_dense(units = 4, activation = "relu", input_shape = c(10000)) %>% 
  layer_dense(units = 4, activation = "relu") %>% 
  layer_dense(units = 1, activation = "sigmoid")
  
bigger_model <- keras_model_sequential() %>% 
  layer_dense(units = 512, activation = "relu", input_shape = c(10000)) %>% 
  layer_dense(units = 512, activation = "relu") %>% 
  layer_dense(units = 1, activation = "sigmoid")
  
l2_model <- keras_model_sequential() %>% 
  layer_dense(units = 16, kernel_regularizer = regularizer_l2(0.001),
              activation = "relu", input_shape = c(10000)) %>% 
  layer_dense(units = 16, kernel_regularizer = regularizer_l2(0.001),
              activation = "relu") %>% 
  layer_dense(units = 1, activation = "sigmoid")
  
dpt_model <- keras_model_sequential() %>% 
  layer_dense(units = 16, activation = "relu", input_shape = c(10000)) %>% 
  layer_dropout(rate = 0.5) %>% 
  layer_dense(units = 16, activation = "relu") %>% 
  layer_dropout(rate = 0.5) %>% 
  layer_dense(units = 1, activation = "sigmoid")