diff options
Diffstat (limited to 'modules/textual_inversion')
| -rw-r--r-- | modules/textual_inversion/textual_inversion.py | 11 |
1 files changed, 9 insertions, 2 deletions
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index cbe975b7..6166c76f 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -13,7 +13,7 @@ import numpy as np from PIL import Image, PngImagePlugin
from torch.utils.tensorboard import SummaryWriter
-from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors
+from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors, hashes
import modules.textual_inversion.dataset
from modules.textual_inversion.learn_schedule import LearnRateScheduler
@@ -49,6 +49,8 @@ class Embedding: self.sd_checkpoint_name = None
self.optimizer_state_dict = None
self.filename = None
+ self.hash = None
+ self.shorthash = None
def save(self, filename):
embedding_data = {
@@ -82,6 +84,10 @@ class Embedding: self.cached_checksum = f'{const_hash(self.vec.reshape(-1) * 100) & 0xffff:04x}'
return self.cached_checksum
+ def set_hash(self, v):
+ self.hash = v
+ self.shorthash = self.hash[0:12]
+
class DirWithTextualInversionEmbeddings:
def __init__(self, path):
@@ -199,6 +205,7 @@ class EmbeddingDatabase: embedding.vectors = vec.shape[0]
embedding.shape = vec.shape[-1]
embedding.filename = path
+ embedding.set_hash(hashes.sha256(embedding.filename, "textual_inversion/" + name) or '')
if self.expected_shape == -1 or self.expected_shape == embedding.shape:
self.register_embedding(embedding, shared.sd_model)
@@ -249,7 +256,7 @@ class EmbeddingDatabase: self.word_embeddings.update(sorted_word_embeddings)
displayed_embeddings = (tuple(self.word_embeddings.keys()), tuple(self.skipped_embeddings.keys()))
- if self.previously_displayed_embeddings != displayed_embeddings:
+ if shared.opts.textual_inversion_print_at_load and self.previously_displayed_embeddings != displayed_embeddings:
self.previously_displayed_embeddings = displayed_embeddings
print(f"Textual inversion embeddings loaded({len(self.word_embeddings)}): {', '.join(self.word_embeddings.keys())}")
if self.skipped_embeddings:
|