[refactor] LoRA tests

tests/lora/test_lora_layers_cogvideox.py

@@ -48,6 +48,7 @@ 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,
@@ -126,8 +127,7 @@ def get_dummy_inputs(self, with_generator=True):
 
     @skip_mps
     def test_lora_fuse_nan(self):
-        scheduler_classes = [CogVideoXDDIMScheduler, CogVideoXDPMScheduler]
-        for scheduler_cls in scheduler_classes:
+        for scheduler_cls in self.scheduler_classes:
             components, text_lora_config, denoiser_lora_config = self.get_dummy_components(scheduler_cls)
             pipe = self.pipeline_class(**components)
             pipe = pipe.to(torch_device)
@@ -156,10 +156,22 @@ def test_lora_fuse_nan(self):
             self.assertTrue(np.isnan(out).all())
 
     def test_simple_inference_with_text_lora_denoiser_fused_multi(self):
-        super().test_simple_inference_with_text_lora_denoiser_fused_multi(expected_atol=5e-3)
+        super().test_simple_inference_with_text_lora_denoiser_fused_multi(expected_atol=9e-3)
 
     def test_simple_inference_with_text_denoiser_lora_unfused(self):
-        super().test_simple_inference_with_text_denoiser_lora_unfused(expected_atol=5e-3)
+        super().test_simple_inference_with_text_denoiser_lora_unfused(expected_atol=9e-3)
+
+    @unittest.skip("Not supported in CogVideoX.")
+    def test_simple_inference_with_text_denoiser_block_scale(self):
+        pass
+
+    @unittest.skip("Not supported in CogVideoX.")
+    def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(self):
+        pass
+
+    @unittest.skip("Not supported in CogVideoX.")
+    def test_modify_padding_mode(self):
+        pass
 
     @unittest.skip("Text encoder LoRA is not supported in CogVideoX.")
     def test_simple_inference_with_partial_text_lora(self):

tests/lora/test_lora_layers_flux.py

@@ -47,7 +47,7 @@ class FluxLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = FluxPipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler()
     scheduler_kwargs = {}
-    uses_flow_matching = True
+    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     transformer_kwargs = {
         "patch_size": 1,
         "in_channels": 4,
@@ -154,6 +154,14 @@ def test_with_alpha_in_state_dict(self):
         )
         self.assertFalse(np.allclose(images_lora_with_alpha, images_lora, atol=1e-3, rtol=1e-3))
 
+    @unittest.skip("Not supported in Flux.")
+    def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(self):
+        pass
+
+    @unittest.skip("Not supported in Flux.")
+    def test_modify_padding_mode(self):
+        pass
+
 
 @slow
 @require_torch_gpu

tests/lora/test_lora_layers_sd3.py

@@ -34,7 +34,7 @@ class SD3LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
     pipeline_class = StableDiffusion3Pipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
     scheduler_kwargs = {}
-    uses_flow_matching = True
+    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     transformer_kwargs = {
         "sample_size": 32,
         "patch_size": 1,
@@ -92,3 +92,19 @@ def test_sd3_lora(self):
 
         lora_filename = "lora_peft_format.safetensors"
         pipe.load_lora_weights(lora_model_id, weight_name=lora_filename)
+
+    @unittest.skip("Not supported in SD3.")
+    def test_simple_inference_with_text_denoiser_block_scale(self):
+        pass
+
+    @unittest.skip("Not supported in SD3.")
+    def test_simple_inference_with_text_denoiser_multi_adapter_block_lora(self):
+        pass
+
+    @unittest.skip("Not supported in SD3.")
+    def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(self):
+        pass
+
+    @unittest.skip("Not supported in SD3.")
+    def test_modify_padding_mode(self):
+        pass