How to change the batch size during training?

I think it will be better to use a custom data generator to have control over the data you pass to the training loop, so you can generate batches of different sizes, process data on the fly etc. Here is an outline:

def data_gen(data):
  while True: # generator yields forever
    # process data into batch, it could be any size
    # it's your responsibility to construct a batch
    yield x,y # here x and y are a single batch

Now you can train with model.fit_generator(data_gen(data), steps_per_epoch=100) which will yield 100 batches per epoch. You can also use a Sequence if you want to encapsulate this inside a class.

For others who land here, I found the easiest way to do batch size adjustment in Keras is just to call fit more than once (with different batch sizes):

model.fit(X_train, y_train, batch_size=32, epochs=20)

# ...continue training with a larger batch size
model.fit(X_train, y_train, batch_size=512, epochs=10)