When I have a small dataset I’m fitting my model like that:
model.fit(
train,
train_labels,
epochs=200,
validation_split=0.2,
batch_size=100,
callbacks=[es],
use_multiprocessing=True
)

but now I can’t load the whole train set in one time as it’s too large, and wonder how I can fit this train set part by part to model?
(if I only can load train_part_1, train_part_2, train_part_3 from disk separately)