diff options
Diffstat (limited to 'webui.py')
| -rw-r--r-- | webui.py | 15 |
1 files changed, 9 insertions, 6 deletions
@@ -746,9 +746,9 @@ class StableDiffusionModelHijack: if hasattr(param_dict, '_parameters'):
param_dict = getattr(param_dict, '_parameters') # fix for torch 1.12.1 loading saved file from torch 1.11
assert len(param_dict) == 1, 'embedding file has multiple terms in it'
- emb = next(iter(param_dict.items()))[1].reshape(768)
- self.word_embeddings[name] = emb
- self.word_embeddings_checksums[name] = f'{const_hash(emb)&0xffff:04x}'
+ emb = next(iter(param_dict.items()))[1]
+ self.word_embeddings[name] = emb.detach()
+ self.word_embeddings_checksums[name] = f'{const_hash(emb.reshape(-1))&0xffff:04x}'
ids = tokenizer([name], add_special_tokens=False)['input_ids'][0]
@@ -838,9 +838,10 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): found = False
for ids, word in possible_matches:
if tokens[i:i+len(ids)] == ids:
+ emb_len = int(self.hijack.word_embeddings[word].shape[0])
fixes.append((len(remade_tokens), word))
- remade_tokens.append(777)
- multipliers.append(mult)
+ remade_tokens += [0] * emb_len
+ multipliers += [mult] * emb_len
i += len(ids) - 1
found = True
used_custom_terms.append((word, self.hijack.word_embeddings_checksums[word]))
@@ -903,7 +904,9 @@ class EmbeddingsWithFixes(nn.Module): if batch_fixes is not None:
for fixes, tensor in zip(batch_fixes, inputs_embeds):
for offset, word in fixes:
- tensor[offset] = self.embeddings.word_embeddings[word]
+ emb = self.embeddings.word_embeddings[word]
+ emb_len = min(tensor.shape[0]-offset, emb.shape[0])
+ tensor[offset:offset+emb_len] = self.embeddings.word_embeddings[word][0:emb_len]
return inputs_embeds
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