# splitting of training examples into the mini batch: what to do with the rest tiny mini-batch?

Lets assume I have 103 training examples. I want a mini-batch to be of the size 16. That means that there will be 6 mini-batches of the size 16 and one mini-batch of the size 7.

In the tensor flow one needs to specify the shape of the input:

x = tf.placeholder(tf.int32, shape=[batch_size], name='x')


which of course led to the following error:

Cannot feed value of shape (7,) for Tensor 'x_10:0', which has shape '(16,)'


So, what do I do with the mini-batch of size 7? Should I find the corresponding mini-batch size, that will create equal mini-batches? If so, how can I follow then the advice to create mini-batches of the power of two? or I should disregard the last mini batch?