+1

Author: hlky

src/diffusers/schedulers/scheduling_euler_discrete.py

@@ -420,22 +420,20 @@ def set_timesteps(
             timesteps = np.array([self._sigma_to_t(sigma, log_sigmas) for sigma in sigmas[:-1]])
         elif sigmas is not None and self.config.use_flow_match:
             sigmas = np.array(sigmas).astype(np.float32)
-            timesteps = sigmas * self.config.num_train_timesteps
-
             if self.config.use_flow_match:
                 if self.config.use_dynamic_shifting:
                     sigmas = self.time_shift(mu, 1.0, sigmas)
                 else:
                     sigmas = self.config.shift * sigmas / (1 + (self.config.shift - 1) * sigmas)
 
             if self.config.use_karras_sigmas:
-                sigmas = self._convert_to_karras(in_sigmas=sigmas, num_inference_steps=self.num_inference_steps)
+                sigmas = self._convert_to_karras(in_sigmas=sigmas, num_inference_steps=num_inference_steps+1)
 
             elif self.config.use_exponential_sigmas:
-                sigmas = self._convert_to_exponential(in_sigmas=sigmas, num_inference_steps=num_inference_steps)
+                sigmas = self._convert_to_exponential(in_sigmas=sigmas, num_inference_steps=num_inference_steps+1)
 
             elif self.config.use_beta_sigmas:
-                sigmas = self._convert_to_beta(in_sigmas=sigmas, num_inference_steps=num_inference_steps)
+                sigmas = self._convert_to_beta(in_sigmas=sigmas, num_inference_steps=num_inference_steps+1)
 
             if self.config.invert_sigmas:
                 sigmas = 1.0 - sigmas