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embeds addiotional checks

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Vladimir Mandic
2024-09-18 21:46:19 -04:00
parent 51e97b3e43
commit 2be087be38
1 changed files with 22 additions and 16 deletions
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modules/prompt_parser_diffusers.py
+22 -16
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@@ -176,10 +176,10 @@ def encode_prompts(pipe, p, prompts: list, negative_prompts: list, steps: int, c
for prompt, negative in zip(prompts, negative_prompts):
prompt_embed, positive_pooled, negative_embed, negative_pooled = None, None, None, None
if last_prompt == prompt and last_negative == negative or False:
prompt_embeds.append(prompt_embed)
positive_pooleds.append(positive_pooled)
negative_embeds.append(negative_embed)
negative_pooleds.append(negative_pooled)
prompt_embeds.append(prompt_embeds[-1])
positive_pooleds.append(positive_pooleds[-1])
negative_embeds.append(negative_embeds[-1])
negative_pooleds.append(negative_pooleds[-1])
continue
positive_schedule, scheduled = get_prompt_schedule(prompt, steps)
negative_schedule, neg_scheduled = get_prompt_schedule(negative, steps)
@@ -196,26 +196,32 @@ def encode_prompts(pipe, p, prompts: list, negative_prompts: list, steps: int, c
prompt_embed, positive_pooled, negative_embed, negative_pooled = get_xhinker_text_embeddings(pipe, positive_prompt, negative_prompt, clip_skip)
else:
prompt_embed, positive_pooled, negative_embed, negative_pooled = get_weighted_text_embeddings(pipe, positive_prompt, negative_prompt, clip_skip)
prompt_embeds.append(prompt_embed)
negative_embeds.append(negative_embed)
if positive_pooled is not None and negative_pooled is not None:
if prompt_embed is not None:
prompt_embeds.append(prompt_embed)
if negative_embed is not None:
negative_embeds.append(negative_embed)
if positive_pooled is not None:
positive_pooleds.append(positive_pooled)
if negative_pooled is not None:
negative_pooleds.append(negative_pooled)
last_prompt, last_negative = prompt, negative
def fix_length(embeds):
max_len = max([p.shape[1] for p in embeds])
for i, p in enumerate(embeds):
if p.shape[1] < max_len:
expanded = torch.zeros((p.shape[0], max_len, p.shape[2]), device=p.device, dtype=p.dtype)
expanded[:, :p.shape[1], :] = p
max_len = max([e.shape[1] for e in embeds if e is not None])
for i, e in enumerate(embeds):
if e is not None and e.shape[1] < max_len:
expanded = torch.zeros((e.shape[0], max_len, e.shape[2]), device=e.device, dtype=e.dtype)
expanded[:, :e.shape[1], :] = e
embeds[i] = expanded
return torch.cat(embeds, dim=0)
return torch.cat(embeds, dim=0).to(devices.device, dtype=devices.dtype)
p.prompt_embeds.append(fix_length(prompt_embeds))
p.negative_embeds.append(fix_length(negative_embeds))
if len(positive_pooleds) > 0 and len(negative_pooleds) > 0: # sd15 does not have pooled embeds
if len(prompt_embeds) > 0:
p.prompt_embeds.append(fix_length(prompt_embeds))
if len(negative_embeds) > 0:
p.negative_embeds.append(fix_length(negative_embeds))
if len(positive_pooleds) > 0:
p.positive_pooleds.append(fix_length(positive_pooleds))
if len(negative_pooleds) > 0:
p.negative_pooleds.append(fix_length(negative_pooleds))
if shared.opts.sd_textencoder_cache and p.batch_size == 1: