Add linear_start and linear_end to model_config.sampling_settings

Author: comfyanonymous

comfy/model_sampling.py

@@ -22,10 +22,17 @@ def calculate_denoised(self, sigma, model_output, model_input):
 class ModelSamplingDiscrete(torch.nn.Module):
     def __init__(self, model_config=None):
         super().__init__()
-        beta_schedule = "linear"
+
         if model_config is not None:
-            beta_schedule = model_config.sampling_settings.get("beta_schedule", beta_schedule)
-        self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=1000, linear_start=0.00085, linear_end=0.012, cosine_s=8e-3)
+            sampling_settings = model_config.sampling_settings
+        else:
+            sampling_settings = {}
+
+        beta_schedule = sampling_settings.get("beta_schedule", "linear")
+        linear_start = sampling_settings.get("linear_start", 0.00085)
+        linear_end = sampling_settings.get("linear_end", 0.012)
+
+        self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=1000, linear_start=linear_start, linear_end=linear_end, cosine_s=8e-3)
         self.sigma_data = 1.0
 
     def _register_schedule(self, given_betas=None, beta_schedule="linear", timesteps=1000,