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Support for Prodigy(Dadapt variety for Dylora) (#585)

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* Update train_util.py for DAdaptLion

* Update train_README-zh.md for dadaptlion

* Update train_README-ja.md for DAdaptLion

* add DAdatpt V3

* Alignment

* Update train_util.py for experimental

* Update train_util.py V3

* Update train_README-zh.md

* Update train_README-ja.md

* Update train_util.py fix

* Update train_util.py

* support Prodigy

* add lower
This commit is contained in:
青龍聖者@bdsqlsz
2023-06-15 20:12:53 +08:00
committed by GitHub
parent f0bb3ae825
commit e97d67a681
8 changed files with 41 additions and 7 deletions
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4
train_network.py
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@@ -57,7 +57,7 @@ def generate_step_logs(
logs["lr/textencoder"] = float(lrs[0])
logs["lr/unet"] = float(lrs[-1]) # may be same to textencoder
if args.optimizer_type.lower().startswith("DAdapt".lower()): # tracking d*lr value of unet.
if args.optimizer_type.lower().startswith("DAdapt".lower()) or args.optimizer_type.lower() == "Prodigy".lower(): # tracking d*lr value of unet.
logs["lr/d*lr"] = lr_scheduler.optimizers[-1].param_groups[0]["d"] * lr_scheduler.optimizers[-1].param_groups[0]["lr"]
else:
idx = 0
@@ -67,7 +67,7 @@ def generate_step_logs(
for i in range(idx, len(lrs)):
logs[f"lr/group{i}"] = float(lrs[i])
if args.optimizer_type.lower().startswith("DAdapt".lower()):
if args.optimizer_type.lower().startswith("DAdapt".lower()) or args.optimizer_type.lower() == "Prodigy".lower():
logs[f"lr/d*lr/group{i}"] = (
lr_scheduler.optimizers[-1].param_groups[i]["d"] * lr_scheduler.optimizers[-1].param_groups[i]["lr"]
)