Add cos xl (#710)

* Add V_PREDICTION_EDM handing for CosXL models

Add V_PREDICTION_EDM handing for CosXL models

* Get correct sigmas from checkpoint.

* Round to 3 sig digs in order to make compatible with comfy implementation

* Add sigma data like ComfyUI has

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Co-authored-by: Gavin Chapman <gchapman@MAINPC>

ldm_patched/modules/model_sampling.py

@@ -107,9 +107,11 @@ def __init__(self, model_config=None):
 
         sigma_min = sampling_settings.get("sigma_min", 0.002)
         sigma_max = sampling_settings.get("sigma_max", 120.0)
-        self.set_sigma_range(sigma_min, sigma_max)
+        sigma_data = sampling_settings.get("sigma_data", 1.0)
+        self.set_sigma_range(sigma_min, sigma_max, sigma_data)
 
-    def set_sigma_range(self, sigma_min, sigma_max):
+    def set_sigma_range(self, sigma_min, sigma_max, sigma_data):
+        self.sigma_data = sigma_data
         sigmas = torch.linspace(math.log(sigma_min), math.log(sigma_max), 1000).exp()
 
         self.register_buffer('sigmas', sigmas) #for compatibility with some schedulers

ldm_patched/modules/supported_models.py

@@ -169,6 +169,11 @@ class SDXL(supported_models_base.BASE):
     def model_type(self, state_dict, prefix=""):
         if "v_pred" in state_dict:
             return model_base.ModelType.V_PREDICTION
+        elif "edm_vpred.sigma_max" in state_dict:
+            self.sampling_settings["sigma_max"] = round(float(state_dict["edm_vpred.sigma_max"].item()),3)
+            if "edm_vpred.sigma_min" in state_dict:
+                self.sampling_settings["sigma_min"] = round(float(state_dict["edm_vpred.sigma_min"].item()),3)
+            return model_base.ModelType.V_PREDICTION_EDM
         else:
             return model_base.ModelType.EPS