R Deep Learning Cookbook

How to do it...

1. Create an input placeholder variable:

x = tf$placeholder(tf$float32, shape=shape(NULL, img_size_flat), name='x')

The NULL value in the placeholder allows us to pass non-deterministic arrays size.

2. Reshape the input placeholder x into a four-dimensional tensor:

x_image = tf$reshape(x, shape(-1L, img_size, img_size, num_channels))

3. Create an output placeholder variable:

y_true = tf$placeholder(tf$float32, shape=shape(NULL, num_classes), name='y_true')

4. Get the (true) classes of the output using argmax:

y_true_cls = tf$argmax(y_true, dimension=1L)