[tests] Single scheduler in lora tests (#12315)

* single scheduler please.

* up

* up

* up

tests/lora/test_lora_layers_auraflow.py

@@ -43,7 +43,6 @@ from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 class AuraFlowLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = AuraFlowPipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {

tests/lora/test_lora_layers_cogvideox.py

@@ -21,7 +21,6 @@ from transformers import AutoTokenizer, T5EncoderModel
 
 from diffusers import (
     AutoencoderKLCogVideoX,
-    CogVideoXDDIMScheduler,
     CogVideoXDPMScheduler,
     CogVideoXPipeline,
     CogVideoXTransformer3DModel,
@@ -44,7 +43,6 @@ class CogVideoXLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = CogVideoXPipeline
     scheduler_cls = CogVideoXDPMScheduler
     scheduler_kwargs = {"timestep_spacing": "trailing"}
-    scheduler_classes = [CogVideoXDDIMScheduler, CogVideoXDPMScheduler]
 
     transformer_kwargs = {
         "num_attention_heads": 4,

tests/lora/test_lora_layers_cogview4.py

@@ -50,7 +50,6 @@ class TokenizerWrapper:
 class CogView4LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = CogView4Pipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {
@@ -124,8 +123,7 @@ class CogView4LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
         """
         Tests a simple usecase where users could use saving utilities for LoRA through save_pretrained
         """
-        for scheduler_cls in self.scheduler_classes:
-            components, _, _ = self.get_dummy_components(scheduler_cls)
+        components, _, _ = self.get_dummy_components()
         pipe = self.pipeline_class(**components)
         pipe = pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)

tests/lora/test_lora_layers_flux.py

@@ -55,9 +55,8 @@ from .utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa
 @require_peft_backend
 class FluxLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = FluxPipeline
-    scheduler_cls = FlowMatchEulerDiscreteScheduler()
+    scheduler_cls = FlowMatchEulerDiscreteScheduler
     scheduler_kwargs = {}
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     transformer_kwargs = {
         "patch_size": 1,
         "in_channels": 4,
@@ -282,9 +281,8 @@ class FluxLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
 
 class FluxControlLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = FluxControlPipeline
-    scheduler_cls = FlowMatchEulerDiscreteScheduler()
+    scheduler_cls = FlowMatchEulerDiscreteScheduler
     scheduler_kwargs = {}
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     transformer_kwargs = {
         "patch_size": 1,
         "in_channels": 8,

tests/lora/test_lora_layers_hunyuanvideo.py

@@ -51,7 +51,6 @@ from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 class HunyuanVideoLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = HunyuanVideoPipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {

tests/lora/test_lora_layers_ltx_video.py

@@ -37,7 +37,6 @@ from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 class LTXVideoLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = LTXPipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {

tests/lora/test_lora_layers_lumina2.py

@@ -39,7 +39,6 @@ from .utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa
 class Lumina2LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = Lumina2Pipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {
@@ -141,8 +140,7 @@ class Lumina2LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
         strict=False,
     )
     def test_lora_fuse_nan(self):
-        for scheduler_cls in self.scheduler_classes:
-            components, text_lora_config, denoiser_lora_config = self.get_dummy_components(scheduler_cls)
+        components, text_lora_config, denoiser_lora_config = self.get_dummy_components()
         pipe = self.pipeline_class(**components)
         pipe = pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
@@ -150,9 +148,7 @@ class Lumina2LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
 
         if "text_encoder" in self.pipeline_class._lora_loadable_modules:
             pipe.text_encoder.add_adapter(text_lora_config, "adapter-1")
-                self.assertTrue(
-                    check_if_lora_correctly_set(pipe.text_encoder), "Lora not correctly set in text encoder"
-                )
+            self.assertTrue(check_if_lora_correctly_set(pipe.text_encoder), "Lora not correctly set in text encoder")
 
         denoiser = pipe.transformer if self.unet_kwargs is None else pipe.unet
         denoiser.add_adapter(denoiser_lora_config, "adapter-1")

tests/lora/test_lora_layers_mochi.py

@@ -37,7 +37,6 @@ from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 class MochiLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = MochiPipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {

tests/lora/test_lora_layers_qwenimage.py

@@ -37,7 +37,6 @@ from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 class QwenImageLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = QwenImagePipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {

tests/lora/test_lora_layers_sana.py

@@ -31,9 +31,8 @@ from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 @require_peft_backend
 class SanaLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = SanaPipeline
-    scheduler_cls = FlowMatchEulerDiscreteScheduler(shift=7.0)
-    scheduler_kwargs = {}
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
+    scheduler_cls = FlowMatchEulerDiscreteScheduler
+    scheduler_kwargs = {"shift": 7.0}
     transformer_kwargs = {
         "patch_size": 1,
         "in_channels": 4,

tests/lora/test_lora_layers_sd3.py

@@ -55,7 +55,6 @@ class SD3LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = StableDiffusion3Pipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
     scheduler_kwargs = {}
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     transformer_kwargs = {
         "sample_size": 32,
         "patch_size": 1,

tests/lora/test_lora_layers_wan.py

@@ -42,7 +42,6 @@ from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 class WanLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = WanPipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {

tests/lora/test_lora_layers_wanvace.py

@@ -50,7 +50,6 @@ from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 class WanVACELoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = WanVACEPipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}
 
     transformer_kwargs = {
@@ -165,9 +164,8 @@ class WanVACELoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
 
     @require_peft_version_greater("0.13.2")
     def test_lora_exclude_modules_wanvace(self):
-        scheduler_cls = self.scheduler_classes[0]
         exclude_module_name = "vace_blocks.0.proj_out"
-        components, text_lora_config, denoiser_lora_config = self.get_dummy_components(scheduler_cls)
+        components, text_lora_config, denoiser_lora_config = self.get_dummy_components()
         pipe = self.pipeline_class(**components).to(torch_device)
         _, _, inputs = self.get_dummy_inputs(with_generator=False)