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[CI] Fix big GPU test marker #11786

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[CI] Fix big GPU test marker #11786

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DN6 Jun 24, 2025
e48cfea
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DN6 Jun 27, 2025
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2 changes: 1 addition & 1 deletion .github/workflows/nightly_tests.yml
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Expand Up @@ -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" \
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Should we not update the instances where the marker is actually present then? Example:
https://github.com/huggingface/diffusers/blob/7bc0a07b1947bcbe0e84bbe9ecf8ae2d234382c4/tests/lora/test_lora_layers_flux.py#L815C2-L815C25

I guess we should remove them?

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Oh whoops. Thought I removed them. Will push up the change.

--make-reports=tests_big_gpu_torch_cuda \
--report-log=tests_big_gpu_torch_cuda.log \
tests/
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4 changes: 4 additions & 0 deletions src/diffusers/utils/testing_utils.py
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Expand Up @@ -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)

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4 changes: 4 additions & 0 deletions tests/conftest.py
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Expand Up @@ -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

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3 changes: 0 additions & 3 deletions tests/lora/test_lora_layers_flux.py
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Expand Up @@ -20,7 +20,6 @@
import unittest

import numpy as np
import pytest
import safetensors.torch
import torch
from parameterized import parameterized
Expand Down Expand Up @@ -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.

Expand Down Expand Up @@ -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
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2 changes: 0 additions & 2 deletions tests/lora/test_lora_layers_hunyuanvideo.py
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Expand Up @@ -17,7 +17,6 @@
import unittest

import numpy as np
import pytest
import torch
from transformers import CLIPTextModel, CLIPTokenizer, LlamaModel, LlamaTokenizerFast

Expand Down Expand Up @@ -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.

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2 changes: 0 additions & 2 deletions tests/lora/test_lora_layers_sd3.py
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Expand Up @@ -17,7 +17,6 @@
import unittest

import numpy as np
import pytest
import torch
from transformers import AutoTokenizer, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel

Expand Down Expand Up @@ -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"
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2 changes: 0 additions & 2 deletions tests/pipelines/controlnet_flux/test_controlnet_flux.py
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Expand Up @@ -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
Expand Down Expand Up @@ -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

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2 changes: 0 additions & 2 deletions tests/pipelines/controlnet_sd3/test_controlnet_sd3.py
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Expand Up @@ -18,7 +18,6 @@
from typing import Optional

import numpy as np
import pytest
import torch
from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel

Expand Down Expand Up @@ -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

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3 changes: 0 additions & 3 deletions tests/pipelines/flux/test_pipeline_flux.py
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Expand Up @@ -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
Expand Down Expand Up @@ -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"
Expand Down Expand Up @@ -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"
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2 changes: 0 additions & 2 deletions tests/pipelines/flux/test_pipeline_flux_redux.py
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Expand Up @@ -2,7 +2,6 @@
import unittest

import numpy as np
import pytest
import torch

from diffusers import FluxPipeline, FluxPriorReduxPipeline
Expand All @@ -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"
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2 changes: 0 additions & 2 deletions tests/pipelines/mochi/test_mochi.py
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Expand Up @@ -17,7 +17,6 @@
import unittest

import numpy as np
import pytest
import torch
from transformers import AutoTokenizer, T5EncoderModel

Expand Down Expand Up @@ -268,7 +267,6 @@ def test_vae_tiling(self, expected_diff_max: float = 0.2):
@nightly
@require_torch_accelerator
@require_big_accelerator
@pytest.mark.big_accelerator
class MochiPipelineIntegrationTests(unittest.TestCase):
prompt = "A painting of a squirrel eating a burger."

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2 changes: 0 additions & 2 deletions tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3.py
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Expand Up @@ -2,7 +2,6 @@
import unittest

import numpy as np
import pytest
import torch
from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel

Expand Down Expand Up @@ -233,7 +232,6 @@ def test_skip_guidance_layers(self):

@slow
@require_big_accelerator
@pytest.mark.big_accelerator
class StableDiffusion3PipelineSlowTests(unittest.TestCase):
pipeline_class = StableDiffusion3Pipeline
repo_id = "stabilityai/stable-diffusion-3-medium-diffusers"
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2 changes: 0 additions & 2 deletions tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_img2img.py
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Expand Up @@ -3,7 +3,6 @@
import unittest

import numpy as np
import pytest
import torch
from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel

Expand Down Expand Up @@ -168,7 +167,6 @@ def test_multi_vae(self):

@slow
@require_big_accelerator
@pytest.mark.big_accelerator
class StableDiffusion3Img2ImgPipelineSlowTests(unittest.TestCase):
pipeline_class = StableDiffusion3Img2ImgPipeline
repo_id = "stabilityai/stable-diffusion-3-medium-diffusers"
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