lllyasviel/stable-diffusion-webui-forge
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we do not need to waste 10 seconds on T5 when CFG=1

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layerdiffusion
2024-08-08 00:19:16 -07:00
parent c00b45aa71
commit 396d9f378d
3 changed files with 10 additions and 2 deletions
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3
backend/sampling/condition.py
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@@ -89,6 +89,9 @@ class ConditionConstant(Condition):
def compile_conditions(cond):
if cond is None:
return None
if isinstance(cond, torch.Tensor):
result = dict(
cross_attn=cond,

7
modules/processing.py
View File

@@ -483,7 +483,12 @@ class StableDiffusionProcessing:
self.step_multiplier = total_steps // self.steps
self.firstpass_steps = total_steps
self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, total_steps, [self.cached_uc], self.extra_network_data)
if self.cfg_scale == 1:
self.uc = None
print('Skipping unconditional conditioning when CFG = 1')
else:
self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, total_steps, [self.cached_uc], self.extra_network_data)
self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, total_steps, [self.cached_c], self.extra_network_data)
def get_conds(self):

2
modules/sd_samplers_cfg_denoiser.py
View File

@@ -173,7 +173,7 @@ class CFGDenoiser(torch.nn.Module):
uncond = self.sampler.sampler_extra_args['uncond']
cond_composition, cond = prompt_parser.reconstruct_multicond_batch(cond, self.step)
uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step)
uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step) if uncond is not None else None
if self.mask is not None:
noisy_initial_latent = self.init_latent + sigma[:, None, None, None] * torch.randn_like(self.init_latent).to(self.init_latent)