in main.py [0:0]
def adjust_learning_rate(args, optimizer, loader, step):
max_steps = args.epochs * len(loader)
warmup_steps = 10 * len(loader)
base_lr = args.batch_size / 256
if step < warmup_steps:
lr = base_lr * step / warmup_steps
else:
step -= warmup_steps
max_steps -= warmup_steps
q = 0.5 * (1 + math.cos(math.pi * step / max_steps))
end_lr = base_lr * 0.001
lr = base_lr * q + end_lr * (1 - q)
optimizer.param_groups[0]['lr'] = lr * args.learning_rate_weights
optimizer.param_groups[1]['lr'] = lr * args.learning_rate_biases