[CI] Fix big GPU test marker (#11786)

* update

* update

.github/workflows/nightly_tests.yml

@@ -248,7 +248,7 @@ jobs:
           BIG_GPU_MEMORY: 40
         run: |
           python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
-            -m "big_gpu_with_torch_cuda" \
+            -m "big_accelerator" \
             --make-reports=tests_big_gpu_torch_cuda \
             --report-log=tests_big_gpu_torch_cuda.log \
             tests/

src/diffusers/utils/testing_utils.py

@@ -421,6 +421,10 @@ def require_big_accelerator(test_case):
     Decorator marking a test that requires a bigger hardware accelerator (24GB) for execution. Some example pipelines:
     Flux, SD3, Cog, etc.
     """
+    import pytest
+
+    test_case = pytest.mark.big_accelerator(test_case)
+
     if not is_torch_available():
         return unittest.skip("test requires PyTorch")(test_case)
 

tests/conftest.py

@@ -30,6 +30,10 @@ sys.path.insert(1, git_repo_path)
 warnings.simplefilter(action="ignore", category=FutureWarning)
 
 
+def pytest_configure(config):
+    config.addinivalue_line("markers", "big_accelerator: marks tests as requiring big accelerator resources")
+
+
 def pytest_addoption(parser):
     from diffusers.utils.testing_utils import pytest_addoption_shared
 

tests/lora/test_lora_layers_flux.py

@@ -20,7 +20,6 @@ import tempfile
 import unittest
 
 import numpy as np
-import pytest
 import safetensors.torch
 import torch
 from parameterized import parameterized
@@ -813,7 +812,6 @@ class FluxControlLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
 @require_torch_accelerator
 @require_peft_backend
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class FluxLoRAIntegrationTests(unittest.TestCase):
     """internal note: The integration slices were obtained on audace.
 
@@ -960,7 +958,6 @@ class FluxLoRAIntegrationTests(unittest.TestCase):
 @require_torch_accelerator
 @require_peft_backend
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class FluxControlLoRAIntegrationTests(unittest.TestCase):
     num_inference_steps = 10
     seed = 0

tests/lora/test_lora_layers_hunyuanvideo.py

@@ -17,7 +17,6 @@ import sys
 import unittest
 
 import numpy as np
-import pytest
 import torch
 from transformers import CLIPTextModel, CLIPTokenizer, LlamaModel, LlamaTokenizerFast
 
@@ -198,7 +197,6 @@ class HunyuanVideoLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
 @require_torch_accelerator
 @require_peft_backend
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class HunyuanVideoLoRAIntegrationTests(unittest.TestCase):
     """internal note: The integration slices were obtained on DGX.
 

tests/lora/test_lora_layers_sd3.py

@@ -17,7 +17,6 @@ import sys
 import unittest
 
 import numpy as np
-import pytest
 import torch
 from transformers import AutoTokenizer, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel
 
@@ -139,7 +138,6 @@ class SD3LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
 @require_torch_accelerator
 @require_peft_backend
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class SD3LoraIntegrationTests(unittest.TestCase):
     pipeline_class = StableDiffusion3Img2ImgPipeline
     repo_id = "stabilityai/stable-diffusion-3-medium-diffusers"

tests/pipelines/controlnet_flux/test_controlnet_flux.py

@@ -17,7 +17,6 @@ import gc
 import unittest
 
 import numpy as np
-import pytest
 import torch
 from huggingface_hub import hf_hub_download
 from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5TokenizerFast
@@ -211,7 +210,6 @@ class FluxControlNetPipelineFastTests(unittest.TestCase, PipelineTesterMixin, Fl
 
 @nightly
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class FluxControlNetPipelineSlowTests(unittest.TestCase):
     pipeline_class = FluxControlNetPipeline
 

tests/pipelines/controlnet_sd3/test_controlnet_sd3.py

@@ -18,7 +18,6 @@ import unittest
 from typing import Optional
 
 import numpy as np
-import pytest
 import torch
 from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel
 
@@ -221,7 +220,6 @@ class StableDiffusion3ControlNetPipelineFastTests(unittest.TestCase, PipelineTes
 
 @slow
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class StableDiffusion3ControlNetPipelineSlowTests(unittest.TestCase):
     pipeline_class = StableDiffusion3ControlNetPipeline
 

tests/pipelines/flux/test_pipeline_flux.py

@@ -2,7 +2,6 @@ import gc
 import unittest
 
 import numpy as np
-import pytest
 import torch
 from huggingface_hub import hf_hub_download
 from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel
@@ -224,7 +223,6 @@ class FluxPipelineFastTests(
 
 @nightly
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class FluxPipelineSlowTests(unittest.TestCase):
     pipeline_class = FluxPipeline
     repo_id = "black-forest-labs/FLUX.1-schnell"
@@ -312,7 +310,6 @@ class FluxPipelineSlowTests(unittest.TestCase):
 
 @slow
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class FluxIPAdapterPipelineSlowTests(unittest.TestCase):
     pipeline_class = FluxPipeline
     repo_id = "black-forest-labs/FLUX.1-dev"

tests/pipelines/flux/test_pipeline_flux_redux.py

@@ -2,7 +2,6 @@ import gc
 import unittest
 
 import numpy as np
-import pytest
 import torch
 
 from diffusers import FluxPipeline, FluxPriorReduxPipeline
@@ -19,7 +18,6 @@ from diffusers.utils.testing_utils import (
 
 @slow
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class FluxReduxSlowTests(unittest.TestCase):
     pipeline_class = FluxPriorReduxPipeline
     repo_id = "black-forest-labs/FLUX.1-Redux-dev"

tests/pipelines/mochi/test_mochi.py

@@ -17,7 +17,6 @@ import inspect
 import unittest
 
 import numpy as np
-import pytest
 import torch
 from transformers import AutoTokenizer, T5EncoderModel
 
@@ -268,7 +267,6 @@ class MochiPipelineFastTests(PipelineTesterMixin, FasterCacheTesterMixin, unitte
 @nightly
 @require_torch_accelerator
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class MochiPipelineIntegrationTests(unittest.TestCase):
     prompt = "A painting of a squirrel eating a burger."
 

tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3.py

@@ -2,7 +2,6 @@ import gc
 import unittest
 
 import numpy as np
-import pytest
 import torch
 from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel
 
@@ -233,7 +232,6 @@ class StableDiffusion3PipelineFastTests(unittest.TestCase, PipelineTesterMixin):
 
 @slow
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class StableDiffusion3PipelineSlowTests(unittest.TestCase):
     pipeline_class = StableDiffusion3Pipeline
     repo_id = "stabilityai/stable-diffusion-3-medium-diffusers"

tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_img2img.py

@@ -3,7 +3,6 @@ import random
 import unittest
 
 import numpy as np
-import pytest
 import torch
 from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel
 
@@ -168,7 +167,6 @@ class StableDiffusion3Img2ImgPipelineFastTests(PipelineLatentTesterMixin, unitte
 
 @slow
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class StableDiffusion3Img2ImgPipelineSlowTests(unittest.TestCase):
     pipeline_class = StableDiffusion3Img2ImgPipeline
     repo_id = "stabilityai/stable-diffusion-3-medium-diffusers"