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chore: make ruff

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dunkeroni 2024-03-18 12:42:59 -04:00 committed by psychedelicious
parent 8b30cbe81e
commit fe5fa7f8cc
1 changed files with 6 additions and 5 deletions

11
invokeai/backend/stable_diffusion/diffusers_pipeline.py

@ -15,9 +15,8 @@ from diffusers.models.controlnet import ControlNetModel
from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import StableDiffusionPipeline
from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from diffusers.schedulers import KarrasDiffusionSchedulers
from diffusers.schedulers.scheduling_utils import SchedulerMixin, SchedulerOutput
from diffusers.schedulers.scheduling_utils import SchedulerMixin
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.outputs import BaseOutput
from pydantic import Field
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
@ -87,7 +86,7 @@ class AddsMaskGuidance:
gradient_mask: bool
def __call__(self, latents: torch.Tensor, t: torch.Tensor, conditioning) -> torch.Tensor:
return self.apply_mask(latents,t)
return self.apply_mask(latents, t)
def apply_mask(self, latents: torch.Tensor, t) -> torch.Tensor:
batch_size = latents.size(0)
@ -371,7 +370,9 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
if gradient_mask:
latents = torch.where(mask > 0, latents, orig_latents)
else:
latents = torch.lerp(orig_latents, latents.to(dtype=orig_latents.dtype), mask.to(dtype=orig_latents.dtype))
latents = torch.lerp(
orig_latents, latents.to(dtype=orig_latents.dtype), mask.to(dtype=orig_latents.dtype)
)
return latents
@ -569,7 +570,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
# compute the previous noisy sample x_t -> x_t-1
step_output = self.scheduler.step(noise_pred, timestep, latents, **conditioning_data.scheduler_args)
return step_output
@staticmethod