add p to cfgdenoiserparams

modules/script_callbacks.py

@@ -41,7 +41,7 @@ class ExtraNoiseParams:
 
 
 class CFGDenoiserParams:
-    def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, text_cond, text_uncond):
+    def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, text_cond, text_uncond, p):
         self.x = x
         """Latent image representation in the process of being denoised"""
 
@@ -63,6 +63,9 @@ class CFGDenoiserParams:
         self.text_uncond = text_uncond
         """ Encoder hidden states of text conditioning from negative prompt"""
 
+        self.p = p
+        """StableDiffusionProcessing object with processing parameters"""
+
 
 class CFGDenoisedParams:
     def __init__(self, x, sampling_step, total_sampling_steps, inner_model):

modules/sd_samplers_cfg_denoiser.py

@@ -146,7 +146,7 @@ class CFGDenoiser(torch.nn.Module):
             sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma] + [sigma])
             image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_uncond] + [torch.zeros_like(self.init_latent)])
 
-        denoiser_params = CFGDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps, tensor, uncond)
+        denoiser_params = CFGDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps, tensor, uncond, self.p)
         cfg_denoiser_callback(denoiser_params)
         x_in = denoiser_params.x
         image_cond_in = denoiser_params.image_cond