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textual inversion support for SDXL

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AUTOMATIC1111
2023-07-29 15:15:06 +03:00
parent 4ca9f70b59
commit 6f0abbb71a
4 changed files with 29 additions and 9 deletions
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8
modules/sd_hijack.py
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@@ -197,7 +197,7 @@ class StableDiffusionModelHijack:
conditioner.embedders[i] = sd_hijack_clip.FrozenCLIPEmbedderForSDXLWithCustomWords(embedder, self)
text_cond_models.append(conditioner.embedders[i])
if typename == 'FrozenOpenCLIPEmbedder2':
embedder.model.token_embedding = EmbeddingsWithFixes(embedder.model.token_embedding, self)
embedder.model.token_embedding = EmbeddingsWithFixes(embedder.model.token_embedding, self, textual_inversion_key='clip_g')
conditioner.embedders[i] = sd_hijack_open_clip.FrozenOpenCLIPEmbedder2WithCustomWords(embedder, self)
text_cond_models.append(conditioner.embedders[i])
@@ -292,10 +292,11 @@ class StableDiffusionModelHijack:
class EmbeddingsWithFixes(torch.nn.Module):
def __init__(self, wrapped, embeddings):
def __init__(self, wrapped, embeddings, textual_inversion_key='clip_l'):
super().__init__()
self.wrapped = wrapped
self.embeddings = embeddings
self.textual_inversion_key = textual_inversion_key
def forward(self, input_ids):
batch_fixes = self.embeddings.fixes
@@ -309,7 +310,8 @@ class EmbeddingsWithFixes(torch.nn.Module):
vecs = []
for fixes, tensor in zip(batch_fixes, inputs_embeds):
for offset, embedding in fixes:
emb = devices.cond_cast_unet(embedding.vec)
vec = embedding.vec[self.textual_inversion_key] if isinstance(embedding.vec, dict) else embedding.vec
emb = devices.cond_cast_unet(vec)
emb_len = min(tensor.shape[0] - offset - 1, emb.shape[0])
tensor = torch.cat([tensor[0:offset + 1], emb[0:emb_len], tensor[offset + 1 + emb_len:]])