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Allow Novograd to be used as an optimizer

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This commit is contained in:
James Betker 2020-09-05 16:50:13 -06:00
parent 912a4d9fea
commit 21ae135f23
1 changed files with 8 additions and 3 deletions
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11
codes/models/steps/steps.py
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@ -6,6 +6,7 @@ import torch
from apex import amp
from collections import OrderedDict
from .injectors import create_injector
from apex.optimizers import FusedNovoGrad
logger = logging.getLogger('base')
@ -50,9 +51,13 @@ class ConfigurableStep(Module):
else:
if self.env['rank'] <= 0:
logger.warning('Params [{:s}] will not optimize.'.format(k))
opt = torch.optim.Adam(optim_params, lr=self.step_opt['lr'],
weight_decay=self.step_opt['weight_decay'],
betas=(self.step_opt['beta1'], self.step_opt['beta2']))
if 'optimizer' not in self.step_opt.keys() or self.step_opt['optimizer'] == 'adam':
opt = torch.optim.Adam(optim_params, lr=self.step_opt['lr'],
weight_decay=self.step_opt['weight_decay'],
betas=(self.step_opt['beta1'], self.step_opt['beta2']))
elif self.step_opt['optimizer'] == 'novograd':
opt = FusedNovoGrad(optim_params, lr=self.step_opt['lr'], weight_decay=self.step_opt['weight_decay'],
betas=(self.step_opt['beta1'], self.step_opt['beta2']))
self.optimizers = [opt]
# Returns all optimizers used in this step.