ostris/ai-toolkit
1
0
Fork 0
mirror of https://github.com/ostris/ai-toolkit.git synced 2026-04-28 18:21:16 +00:00
Code Issues Packages Projects Releases Wiki Activity

Various bug fixes and optimizations for quantized training. Added untested custom adam8bit optimizer. Did some work on LoRM (dont use)

Browse Source
This commit is contained in:
Jaret Burkett
2024-11-20 09:16:55 -07:00
parent 6509ba4484
commit 894374b2e9
7 changed files with 241 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files

29
toolkit/ema.py
View File

@@ -5,6 +5,7 @@ from typing import Iterable, Optional
import weakref
import copy
import contextlib
from toolkit.optimizers.optimizer_utils import copy_stochastic
import torch
@@ -43,7 +44,7 @@ class ExponentialMovingAverage:
self,
parameters: Iterable[torch.nn.Parameter] = None,
decay: float = 0.995,
use_num_updates: bool = True,
use_num_updates: bool = False,
# feeds back the decat to the parameter
use_feedback: bool = False,
param_multiplier: float = 1.0
@@ -123,16 +124,32 @@ class ExponentialMovingAverage:
one_minus_decay = 1.0 - decay
with torch.no_grad():
for s_param, param in zip(self.shadow_params, parameters):
tmp = (s_param - param)
s_param_float = s_param.float()
if s_param.dtype != torch.float32:
s_param_float = s_param_float.to(torch.float32)
param_float = param
if param.dtype != torch.float32:
param_float = param_float.to(torch.float32)
tmp = (s_param_float - param_float)
# tmp will be a new tensor so we can do in-place
tmp.mul_(one_minus_decay)
s_param.sub_(tmp)
s_param_float.sub_(tmp)
update_param = False
if self.use_feedback:
param.add_(tmp)
param_float.add_(tmp)
update_param = True
if self.param_multiplier != 1.0:
param.mul_(self.param_multiplier)
param_float.mul_(self.param_multiplier)
update_param = True
if s_param.dtype != torch.float32:
copy_stochastic(s_param, s_param_float)
if update_param and param.dtype != torch.float32:
copy_stochastic(param, param_float)
def copy_to(
self,