File size: 1,936 Bytes
d1b91e7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
class NoneSchedule(object):
    def __init__(self, optimizer, lr):
        self.optimizer = optimizer
        self.constant_lr = lr
        self.step(0)

    def step(self, num_updates):
        self.lr = self.constant_lr
        for param_group in self.optimizer.param_groups:
            param_group['lr'] = self.lr
        return self.lr

    def get_lr(self):
        return self.optimizer.param_groups[0]['lr']

    def get_last_lr(self):
        return self.get_lr()


class RSQRTSchedule(NoneSchedule):
    def __init__(self, optimizer, lr, warmup_updates, hidden_size):
        self.optimizer = optimizer
        self.constant_lr = lr
        self.warmup_updates = warmup_updates
        self.hidden_size = hidden_size
        self.lr = lr
        for param_group in optimizer.param_groups:
            param_group['lr'] = self.lr
        self.step(0)

    def step(self, num_updates):
        constant_lr = self.constant_lr
        warmup = min(num_updates / self.warmup_updates, 1.0)
        rsqrt_decay = max(self.warmup_updates, num_updates) ** -0.5
        rsqrt_hidden = self.hidden_size ** -0.5
        self.lr = max(constant_lr * warmup * rsqrt_decay * rsqrt_hidden, 1e-7)
        for param_group in self.optimizer.param_groups:
            param_group['lr'] = self.lr
        return self.lr


class WarmupSchedule(NoneSchedule):
    def __init__(self, optimizer, lr, warmup_updates):
        self.optimizer = optimizer
        self.constant_lr = self.lr = lr
        self.warmup_updates = warmup_updates
        for param_group in optimizer.param_groups:
            param_group['lr'] = self.lr
        self.step(0)

    def step(self, num_updates):
        constant_lr = self.constant_lr
        warmup = min(num_updates / self.warmup_updates, 1.0)
        self.lr = max(constant_lr * warmup, 1e-7)
        for param_group in self.optimizer.param_groups:
            param_group['lr'] = self.lr
        return self.lr