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Cleaning up prior to submitting ControlNet PR. Mostly turning off diagnostic printing. Also fixed error when there is no controlnet input.

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user1
2023-05-12 10:43:10 -07:00
committed by Kent Keirsey
parent f613c073c1
commit 297931f5d9
3 changed files with 13 additions and 12 deletions
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10
invokeai/backend/stable_diffusion/diffusers_pipeline.py
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@ -670,15 +670,15 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
else:
latent_control_input = latent_model_input
# control_data should be type List[ControlNetData]
# this loop covers both ControlNet (1 ControlNetData in list)
# this loop covers both ControlNet (one ControlNetData in list)
# and MultiControlNet (multiple ControlNetData in list)
for i, control_datum in enumerate(control_data):
# print("controlnet", i, "==>", type(control_datum))
first_control_step = math.floor(control_datum.begin_step_percent * total_step_count)
last_control_step = math.ceil(control_datum.end_step_percent * total_step_count)
# apply_control_this_step = step_index >= first_control_step and step_index <= last_control_step
# only apply controlnet if current step is within the controlnet's begin/end step range
if step_index >= first_control_step and step_index <= last_control_step:
print("running controlnet", i, "for step", step_index)
# print("running controlnet", i, "for step", step_index)
down_samples, mid_sample = control_datum.model(
sample=latent_control_input,
timestep=timestep,
@ -709,8 +709,8 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
conditioning_data.guidance_scale,
step_index=step_index,
total_step_count=total_step_count,
down_block_additional_residuals=down_block_res_samples,
mid_block_additional_residual=mid_block_res_sample,
down_block_additional_residuals=down_block_res_samples, # from controlnet(s)
mid_block_additional_residual=mid_block_res_sample, # from controlnet(s)
)
# compute the previous noisy sample x_t -> x_t-1