From 555912a86b012382a78f1b2717c2e0fde5994a04 Mon Sep 17 00:00:00 2001
From: Volpeon <git@volpeon.ink>
Date: Tue, 17 Jan 2023 11:50:16 +0100
Subject: Make embedding decay work like Adam decay
---
training/strategy/ti.py | 14 +++++---------
1 file changed, 5 insertions(+), 9 deletions(-)
(limited to 'training')
diff --git a/training/strategy/ti.py b/training/strategy/ti.py
index 081180f..eb6730b 100644
--- a/training/strategy/ti.py
+++ b/training/strategy/ti.py
@@ -32,12 +32,10 @@ def textual_inversion_strategy_callbacks(
seed: int,
placeholder_tokens: list[str],
placeholder_token_ids: list[list[int]],
- learning_rate: float,
gradient_checkpointing: bool = False,
use_emb_decay: bool = False,
emb_decay_target: float = 0.4,
- emb_decay_factor: float = 1,
- emb_decay_start: float = 0,
+ emb_decay: float = 1e-2,
use_ema: bool = False,
ema_inv_gamma: float = 1.0,
ema_power: int = 1,
@@ -120,17 +118,15 @@ def textual_inversion_strategy_callbacks(
yield
def on_after_optimize(lr: float):
- if ema_embeddings is not None:
- ema_embeddings.step(text_encoder.text_model.embeddings.temp_token_embedding.parameters())
-
- @torch.no_grad()
- def on_after_epoch(lr: float):
if use_emb_decay:
text_encoder.text_model.embeddings.normalize(
emb_decay_target,
- min(1.0, max(0.0, emb_decay_factor * ((lr - emb_decay_start) / (learning_rate - emb_decay_start))))
+ min(1.0, emb_decay * lr)
)
+ if ema_embeddings is not None:
+ ema_embeddings.step(text_encoder.text_model.embeddings.temp_token_embedding.parameters())
+
def on_log():
if ema_embeddings is not None:
return {"ema_decay": ema_embeddings.decay}
--
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