From 80723178ee23b94eaed139b7f9fd6f9c60a2c3fc Mon Sep 17 00:00:00 2001
From: ClownsharkBatwing <clownshark.batwing@proton.me>
Date: Sun, 15 Dec 2024 20:44:42 -0500
Subject: [PATCH 1/2] Add files via upload

---
 conditioning.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/conditioning.py b/conditioning.py
index 7d29b2a..2bb5909 100644
--- a/conditioning.py
+++ b/conditioning.py
@@ -579,7 +579,6 @@ class FluxRegionalConditioning:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": { 
-            "conditioning_regional": ("CONDITIONING_REGIONAL",),
             "mask_weight": ("FLOAT", {"default": 1.0, "min": -10000.0, "max": 10000.0, "step": 0.01}),
             "start_percent": ("FLOAT", {"default": 0,   "min": 0.0, "max": 1.0, "step": 0.01}),
             "end_percent":   ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
@@ -587,6 +586,7 @@ def INPUT_TYPES(s):
         }, 
             "optional": {
                 "conditioning": ("CONDITIONING",),
+                "conditioning_regional": ("CONDITIONING_REGIONAL",),
                 "mask_weights": ("SIGMAS", ),
         }}
 

From b7d0cf90e5a5e05b8fa0a180e33d541d9176aade Mon Sep 17 00:00:00 2001
From: ClownsharkBatwing <clownshark.batwing@proton.me>
Date: Sun, 15 Dec 2024 20:54:22 -0500
Subject: [PATCH 2/2] Add files via upload

Fixed SharkSampler and ClownsharKSampler so that no connected conditioning is needed with Flux. It will generated zeroed out conditioning automatically for you.
---
 models.py   |  1 +
 samplers.py | 35 ++++++++++++++++++++++++-----------
 2 files changed, 25 insertions(+), 11 deletions(-)

diff --git a/models.py b/models.py
index 5fa92b1..41f5479 100644
--- a/models.py
+++ b/models.py
@@ -37,6 +37,7 @@ def main(self, model):
         m = model.clone()
         
         m.model.diffusion_model.__class__ = ReFlux
+        m.model.diffusion_model.threshold_inv = False
         
         for i, block in enumerate(m.model.diffusion_model.double_blocks):
             block.__class__ = DoubleStreamBlock
diff --git a/samplers.py b/samplers.py
index ed68373..067fc43 100644
--- a/samplers.py
+++ b/samplers.py
@@ -133,17 +133,30 @@ def main(self, model, cfg, sampler_mode, scheduler, steps, denoise=1.0, denoise_
                 latent = latent_image
                 latent_image_dtype = latent_image['samples'].dtype
 
-                if positive is None:
-                    positive = [[
-                        torch.zeros((1, 154, 4096)),
-                        {'pooled_output': torch.zeros((1, 2048))}
-                        ]]
-
-                if negative is None:
-                    negative = [[
-                        torch.zeros((1, 154, 4096)),
-                        {'pooled_output': torch.zeros((1, 2048))}
-                        ]]
+                if isinstance(model.model.model_config, comfy.supported_models.Flux) or isinstance(model.model.model_config, comfy.supported_models.FluxSchnell):
+                    if positive is None:
+                        positive = [[
+                            torch.zeros((1, 256, 4096)),
+                            {'pooled_output': torch.zeros((1, 768))}
+                            ]]
+
+                    if negative is None:
+                        negative = [[
+                            torch.zeros((1, 256, 4096)),
+                            {'pooled_output': torch.zeros((1, 768))}
+                            ]]
+                else:
+                    if positive is None:
+                        positive = [[
+                            torch.zeros((1, 154, 4096)),
+                            {'pooled_output': torch.zeros((1, 2048))}
+                            ]]
+
+                    if negative is None:
+                        negative = [[
+                            torch.zeros((1, 154, 4096)),
+                            {'pooled_output': torch.zeros((1, 2048))}
+                            ]]
 
                 if denoise_alt < 0:
                     d_noise = denoise_alt = -denoise_alt