| import torch |
| from .torch_utils import * |
|
|
| class PolyOptimizer(torch.optim.SGD): |
| def __init__(self, params, lr, weight_decay, max_step, momentum=0.9, nesterov=False): |
| super().__init__(params, lr, weight_decay, nesterov=nesterov) |
|
|
| self.global_step = 0 |
| self.max_step = max_step |
| self.momentum = momentum |
| |
| self.__initial_lr = [group['lr'] for group in self.param_groups] |
| |
| def step(self, closure=None): |
| if self.global_step < self.max_step: |
| lr_mult = (1 - self.global_step / self.max_step) ** self.momentum |
|
|
| for i in range(len(self.param_groups)): |
| self.param_groups[i]['lr'] = self.__initial_lr[i] * lr_mult |
|
|
| super().step(closure) |
|
|
| self.global_step += 1 |
|
|
