make style

[Euler Discrete] Fix sigma
2025-12-09 22:14:43 +08:00 · 2023-12-06 19:58:43 +01:00 · 2023-12-06 19:56:44 +01:00
2 changed files with 1 additions and 3 deletions
--- a/src/diffusers/models/init.py
+++ b/src/diffusers/models/init.py
@@ -33,8 +33,8 @@ if is_torch_available():
    _import_structure["consistency_decoder_vae"] = ["ConsistencyDecoderVAE"]
    _import_structure["controlnet"] = ["ControlNetModel"]
    _import_structure["dual_transformer_2d"] = ["DualTransformer2DModel"]
-    _import_structure["modeling_utils"] = ["ModelMixin"]
    _import_structure["embeddings"] = ["ImageProjection"]
+    _import_structure["modeling_utils"] = ["ModelMixin"]
    _import_structure["prior_transformer"] = ["PriorTransformer"]
    _import_structure["t5_film_transformer"] = ["T5FilmDecoder"]
    _import_structure["transformer_2d"] = ["Transformer2DModel"]
--- a/src/diffusers/schedulers/scheduling_euler_discrete.py
+++ b/src/diffusers/schedulers/scheduling_euler_discrete.py
@@ -290,8 +290,6 @@ class EulerDiscreteScheduler(SchedulerMixin, ConfigMixin):
            self.timesteps = torch.from_numpy(timesteps.astype(np.float32)).to(device=device)

        self.sigmas = torch.cat([sigmas, torch.zeros(1, device=sigmas.device)])
-        if sigmas.device.type == "cuda":
-            self.sigmas = self.sigmas.tolist()
        self._step_index = None

    def _sigma_to_t(self, sigma, log_sigmas):
Author	SHA1	Message	Date
Patrick von Platen	83d4588ded	make style	2023-12-06 19:58:43 +01:00
Patrick von Platen	9fcf2a65f3	[Euler Discrete] Fix sigma	2023-12-06 19:56:44 +01:00