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Textual Inversion for M1

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Update main.py

Update ddpm.py

Update personalized.py

Update personalized_style.py

Update v1-finetune.yaml

Update environment-mac.yaml

Rename v1-finetune.yaml to v1-m1-finetune.yaml

Create v1-finetune.yaml

Update main.py

Update main.py

Update environment-mac.yaml

Update v1-inference.yaml
This commit is contained in:
Any-Winter-4079
2022-09-25 19:12:11 +02:00
parent d2b57029c8
commit e19aab4a9b
9 changed files with 163 additions and 23 deletions
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2
ldm/data/personalized.py
View File

@@ -117,7 +117,7 @@ class PersonalizedBase(Dataset):
self.image_paths = [
os.path.join(self.data_root, file_path)
for file_path in os.listdir(self.data_root)
for file_path in os.listdir(self.data_root) if file_path != ".DS_Store"
]
# self._length = len(self.image_paths)

2
ldm/data/personalized_style.py
View File

@@ -93,7 +93,7 @@ class PersonalizedBase(Dataset):
self.image_paths = [
os.path.join(self.data_root, file_path)
for file_path in os.listdir(self.data_root)
for file_path in os.listdir(self.data_root) if file_path != ".DS_Store"
]
# self._length = len(self.image_paths)

4
ldm/models/diffusion/ddpm.py
View File

@@ -701,7 +701,7 @@ class LatentDiffusion(DDPM):
@rank_zero_only
@torch.no_grad()
def on_train_batch_start(self, batch, batch_idx, dataloader_idx):
def on_train_batch_start(self, batch, batch_idx, dataloader_idx=None):
# only for very first batch
if (
self.scale_by_std
@@ -1890,7 +1890,7 @@ class LatentDiffusion(DDPM):
N=8,
n_row=4,
sample=True,
ddim_steps=200,
ddim_steps=50,
ddim_eta=1.0,
return_keys=None,
quantize_denoised=True,

11
ldm/modules/embedding_manager.py
View File

@@ -169,9 +169,14 @@ class EmbeddingManager(nn.Module):
placeholder_embedding.shape[0], max_step_tokens
)
placeholder_rows, placeholder_cols = torch.where(
tokenized_text == placeholder_token.to(device)
)
if torch.cuda.is_available():
placeholder_rows, placeholder_cols = torch.where(
tokenized_text == placeholder_token.to(device)
)
else:
placeholder_rows, placeholder_cols = torch.where(
tokenized_text == placeholder_token
)
if placeholder_rows.nelement() == 0:
continue