IP2P model loading support.
This is the code to load the model and inference it with only a text prompt. This commit does not contain the nodes to properly use it with an image input. This supports both the original SD1 instructpix2pix model and the diffusers SDXL one.
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@@ -473,6 +473,40 @@ class SD_X4Upscaler(BaseModel):
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out['y'] = comfy.conds.CONDRegular(noise_level)
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return out
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class IP2P:
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def extra_conds(self, **kwargs):
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out = {}
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image = kwargs.get("concat_latent_image", None)
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noise = kwargs.get("noise", None)
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device = kwargs["device"]
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if image is None:
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image = torch.zeros_like(noise)
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if image.shape[1:] != noise.shape[1:]:
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image = utils.common_upscale(image.to(device), noise.shape[-1], noise.shape[-2], "bilinear", "center")
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image = utils.resize_to_batch_size(image, noise.shape[0])
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out['c_concat'] = comfy.conds.CONDNoiseShape(self.process_ip2p_image_in(image))
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adm = self.encode_adm(**kwargs)
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if adm is not None:
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out['y'] = comfy.conds.CONDRegular(adm)
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return out
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class SD15_instructpix2pix(IP2P, BaseModel):
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def __init__(self, model_config, model_type=ModelType.EPS, device=None):
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super().__init__(model_config, model_type, device=device)
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self.process_ip2p_image_in = lambda image: image
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class SDXL_instructpix2pix(IP2P, SDXL):
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def __init__(self, model_config, model_type=ModelType.EPS, device=None):
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super().__init__(model_config, model_type, device=device)
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# self.process_ip2p_image_in = lambda image: comfy.latent_formats.SDXL().process_in(image)
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self.process_ip2p_image_in = lambda image: image
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class StableCascade_C(BaseModel):
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def __init__(self, model_config, model_type=ModelType.STABLE_CASCADE, device=None):
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super().__init__(model_config, model_type, device=device, unet_model=StageC)
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