R Deep Learning Cookbook

How to do it...

The section will provide steps to set-up an RNN model.

1. Load the MNIST dataset:

# Load mnist dataset from tensorflow library 
datasets <- tf$contrib$learn$datasets 
mnist <- datasets$mnist$read_data_sets("MNIST-data", one_hot = TRUE) 

2. Reset the graph and start an interactive session:

# Reset the graph and set-up a interactive session 
tf$reset_default_graph() 
sess<-tf$InteractiveSession() 

3. Reduce image size to 16 x 16 pixels using the reduceImage function from Chapter 4, Data Representation using Autoencoders:

# Covert train data to 16 x 16  pixel image 
trainData<-t(apply(mnist$train$images, 1, FUN=reduceImage)) 
validData<-t(apply(mnist$test$images, 1, FUN=reduceImage)) 
 

4. Extract labels for the defined train and valid ...