diff options
Diffstat (limited to 'modules/textual_inversion')
| -rw-r--r-- | modules/textual_inversion/autocrop.py | 6 | ||||
| -rw-r--r-- | modules/textual_inversion/dataset.py | 4 | ||||
| -rw-r--r-- | modules/textual_inversion/textual_inversion.py | 5 |
3 files changed, 9 insertions, 6 deletions
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 9859974a..68e1103c 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -276,8 +276,8 @@ def poi_average(pois, settings): weight += poi.weight
x += poi.x * poi.weight
y += poi.y * poi.weight
- avg_x = round(x / weight)
- avg_y = round(y / weight)
+ avg_x = round(weight and x / weight)
+ avg_y = round(weight and y / weight)
return PointOfInterest(avg_x, avg_y)
@@ -338,4 +338,4 @@ class Settings: self.face_points_weight = face_points_weight
self.annotate_image = annotate_image
self.destop_view_image = False
- self.dnn_model_path = dnn_model_path
\ No newline at end of file + self.dnn_model_path = dnn_model_path
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index e5725f33..2dc64c3c 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -82,7 +82,7 @@ class PersonalizedBase(Dataset): torchdata = torch.from_numpy(npimage).permute(2, 0, 1).to(device=device, dtype=torch.float32)
latent_sample = None
- with torch.autocast("cuda"):
+ with devices.autocast():
latent_dist = model.encode_first_stage(torchdata.unsqueeze(dim=0))
if latent_sampling_method == "once" or (latent_sampling_method == "deterministic" and not isinstance(latent_dist, DiagonalGaussianDistribution)):
@@ -101,7 +101,7 @@ class PersonalizedBase(Dataset): entry.cond_text = self.create_text(filename_text)
if include_cond and not (self.tag_drop_out != 0 or self.shuffle_tags):
- with torch.autocast("cuda"):
+ with devices.autocast():
entry.cond = cond_model([entry.cond_text]).to(devices.cpu).squeeze(0)
self.dataset.append(entry)
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 4eb75cb5..e28c357a 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -269,6 +269,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ # dataset loading may take a while, so input validations and early returns should be done before this
shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
+ old_parallel_processing_allowed = shared.parallel_processing_allowed
pin_memory = shared.opts.pin_memory
@@ -279,6 +280,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ dl = modules.textual_inversion.dataset.PersonalizedDataLoader(ds, latent_sampling_method=latent_sampling_method, batch_size=ds.batch_size, pin_memory=pin_memory)
if unload:
+ shared.parallel_processing_allowed = False
shared.sd_model.first_stage_model.to(devices.cpu)
embedding.vec.requires_grad = True
@@ -316,7 +318,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ if shared.state.interrupted:
break
- with torch.autocast("cuda"):
+ with devices.autocast():
# c = stack_conds(batch.cond).to(devices.device)
# mask = torch.tensor(batch.emb_index).to(devices.device, non_blocking=pin_memory)
# print(mask)
@@ -450,6 +452,7 @@ Last saved image: {html.escape(last_saved_image)}<br/> pbar.leave = False
pbar.close()
shared.sd_model.first_stage_model.to(devices.device)
+ shared.parallel_processing_allowed = old_parallel_processing_allowed
return embedding, filename
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