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Some minor updates to the nightly and push workflows (#9759)
* move lora integration tests to nightly./ * remove slow marker in the workflow where not needed.
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.github/workflows/push_tests.yml

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@@ -81,7 +81,7 @@ jobs:
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- name: Environment
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run: |
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python utils/print_env.py
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- name: Slow PyTorch CUDA checkpoint tests on Ubuntu
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- name: PyTorch CUDA checkpoint tests on Ubuntu
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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# https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms
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run: |
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python utils/print_env.py
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- name: Run slow Flax TPU tests
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- name: Run Flax TPU tests
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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run: |
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run: |
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python utils/print_env.py
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- name: Run slow ONNXRuntime CUDA tests
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- name: Run ONNXRuntime CUDA tests
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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run: |

tests/lora/test_lora_layers_flux.py

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@@ -27,6 +27,7 @@
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from diffusers.utils.testing_utils import (
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floats_tensor,
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is_peft_available,
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nightly,
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numpy_cosine_similarity_distance,
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require_peft_backend,
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require_torch_gpu,
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@slow
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@nightly
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@require_torch_gpu
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@require_peft_backend
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# @unittest.skip("We cannot run inference on this model with the current CI hardware")
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@unittest.skip("We cannot run inference on this model with the current CI hardware")
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# TODO (DN6, sayakpaul): move these tests to a beefier GPU
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class FluxLoRAIntegrationTests(unittest.TestCase):
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"""internal note: The integration slices were obtained on audace.

tests/lora/test_lora_layers_sd.py

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from diffusers.utils.import_utils import is_accelerate_available
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from diffusers.utils.testing_utils import (
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load_image,
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nightly,
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numpy_cosine_similarity_distance,
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require_peft_backend,
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require_torch_gpu,
@@ -207,6 +208,7 @@ def test_integration_move_lora_dora_cpu(self):
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@slow
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@nightly
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@require_torch_gpu
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@require_peft_backend
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class LoraIntegrationTests(unittest.TestCase):

tests/lora/test_lora_layers_sdxl.py

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@slow
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@nightly
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@require_torch_gpu
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@require_peft_backend
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class LoraSDXLIntegrationTests(unittest.TestCase):

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