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

* update

* update

Author: DN6

.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 @@
 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 unittest
 
 import numpy as np
-import pytest
 import safetensors.torch
 import torch
 from parameterized import parameterized
@@ -813,7 +812,6 @@ def test_simple_inference_with_text_denoiser_multi_adapter_block_lora(self):
 @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 @@ def test_flux_xlabs_load_lora_with_single_blocks(self):
 @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 unittest
 
 import numpy as np
-import pytest
 import torch
 from transformers import CLIPTextModel, CLIPTokenizer, LlamaModel, LlamaTokenizerFast
 
@@ -198,7 +197,6 @@ def test_simple_inference_with_text_lora_save_load(self):
 @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 unittest
 
 import numpy as np
-import pytest
 import torch
 from transformers import AutoTokenizer, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel
 
@@ -139,7 +138,6 @@ def test_multiple_wrong_adapter_name_raises_error(self):
 @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 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 @@ def test_flux_image_output_shape(self):
 
 @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 @@
 from typing import Optional
 
 import numpy as np
-import pytest
 import torch
 from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel
 
@@ -221,7 +220,6 @@ def test_xformers_attention_forwardGenerator_pass(self):
 
 @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 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 @@ def test_flux_true_cfg(self):
 
 @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 @@ def test_flux_inference(self):
 
 @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 unittest
 
 import numpy as np
-import pytest
 import torch
 
 from diffusers import FluxPipeline, FluxPriorReduxPipeline
@@ -19,7 +18,6 @@
 
 @slow
 @require_big_accelerator
-@pytest.mark.big_accelerator
 class FluxReduxSlowTests(unittest.TestCase):
     pipeline_class = FluxPriorReduxPipeline
     repo_id = "black-forest-labs/FLUX.1-Redux-dev"