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add differential diffusion

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Vladimir Mandic
2024-02-20 10:06:42 -05:00
parent cf3fbad84e
commit 02394356e7
6 changed files with 1184 additions and 41 deletions
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modules/processing_diffusers.py
+3 -20
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@@ -266,32 +266,15 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
clean.pop('callback_steps', None)
clean.pop('callback_on_step_end', None)
clean.pop('callback_on_step_end_tensor_inputs', None)
if 'latents' in clean:
clean['latents'] = clean['latents'].shape
if 'image' in clean:
clean['image'] = type(clean['image'])
if 'mask_image' in clean:
clean['mask_image'] = type(clean['mask_image'])
if 'masked_image_latents' in clean:
clean['masked_image_latents'] = type(clean['masked_image_latents'])
if 'ip_adapter_image' in clean:
clean['ip_adapter_image'] = type(clean['ip_adapter_image'])
if 'prompt' in clean:
clean['prompt'] = len(clean['prompt'])
if 'negative_prompt' in clean:
clean['negative_prompt'] = len(clean['negative_prompt'])
if 'prompt_embeds' in clean:
clean['prompt_embeds'] = clean['prompt_embeds'].shape if torch.is_tensor(clean['prompt_embeds']) else type(clean['prompt_embeds'])
if 'pooled_prompt_embeds' in clean:
clean['pooled_prompt_embeds'] = clean['pooled_prompt_embeds'].shape if torch.is_tensor(clean['pooled_prompt_embeds']) else type(clean['pooled_prompt_embeds'])
if 'negative_prompt_embeds' in clean:
clean['negative_prompt_embeds'] = clean['negative_prompt_embeds'].shape if torch.is_tensor(clean['negative_prompt_embeds']) else type(clean['negative_prompt_embeds'])
if 'negative_pooled_prompt_embeds' in clean:
clean['negative_pooled_prompt_embeds'] = clean['negative_pooled_prompt_embeds'].shape if torch.is_tensor(clean['negative_pooled_prompt_embeds']) else type(clean['negative_pooled_prompt_embeds'])
if 'image_embeds' in clean:
clean['image_embeds'] = clean['image_embeds'].shape if torch.is_tensor(clean['image_embeds']) else type(clean['image_embeds'])
clean['generator'] = generator_device
clean['parser'] = parser
for k, v in clean.items():
if isinstance(v, torch.Tensor):
clean[k] = v.shape
shared.log.debug(f'Diffuser pipeline: {model.__class__.__name__} task={sd_models.get_diffusers_task(model)} set={clean}')
if p.hdr_clamp or p.hdr_maximize or p.hdr_brightness != 0 or p.hdr_color != 0 or p.hdr_sharpen != 0:
txt = 'HDR:'