Which method prints out the training and validation losses after each epoch.
Could not find these methods by searching through the library, which is odd.
They should be related to the for loop in the fit method shown below.
But can’t figure out how.
fit method from the file model.py
def fit(model, data, epochs, opt, crit, metrics=None, callbacks=None, **kwargs):
stepper = Stepper(model, opt, crit, **kwargs)
metrics = metrics or []
callbacks = callbacks or []
avg_mom=0.98
batch_num,avg_loss=0,0.
for epoch in tnrange(epochs, desc='Epoch'):
stepper.reset(True)
t = tqdm(iter(data.trn_dl), leave=False, total=len(data.trn_dl))
for (*x,y) in t:
batch_num += 1
loss = stepper.step(V(x),V(y))
avg_loss = avg_loss * avg_mom + loss * (1-avg_mom)
debias_loss = avg_loss / (1 - avg_mom**batch_num)
t.set_postfix(loss=debias_loss)
stop=False
for cb in callbacks: stop = stop or cb.on_batch_end(debias_loss)
if stop: return