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Learning rate sched syntax support for grad clipping

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This commit is contained in:
Muhammad Rizqi Nur
2022-10-28 17:16:23 +07:00
parent 1618df41ba
commit 16451ca573
4 changed files with 30 additions and 13 deletions
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12
modules/textual_inversion/textual_inversion.py
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@@ -255,9 +255,12 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
ititial_step = embedding.step or 0
if ititial_step > steps:
return embedding, filename
clip_grad_mode_value = clip_grad_mode == "value"
clip_grad_mode_norm = clip_grad_mode == "norm"
clip_grad_enabled = clip_grad_mode_value or clip_grad_mode_norm
if clip_grad_enabled:
clip_grad_sched = LearnRateScheduler(clip_grad_value, steps, ititial_step, verbose=False)
scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate)
@@ -273,6 +276,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
if shared.state.interrupted:
break
if clip_grad_enabled:
clip_grad_sched.step(embedding.step)
with torch.autocast("cuda"):
c = cond_model([entry.cond_text for entry in entries])
x = torch.stack([entry.latent for entry in entries]).to(devices.device)
@@ -285,9 +291,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
loss.backward()
if clip_grad_mode_value:
torch.nn.utils.clip_grad_value_(embedding.vec, clip_value=clip_grad_value)
torch.nn.utils.clip_grad_value_(embedding.vec, clip_value=clip_grad_sched.learn_rate)
elif clip_grad_mode_norm:
torch.nn.utils.clip_grad_norm_(embedding.vec, max_norm=clip_grad_value)
torch.nn.utils.clip_grad_norm_(embedding.vec, max_norm=clip_grad_sched.learn_rate)
optimizer.step()