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8 Commits
requiremen
...
reconfigur
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2
.github/workflows/nightly_tests.yml
vendored
2
.github/workflows/nightly_tests.yml
vendored
@@ -198,7 +198,7 @@ jobs:
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HF_TOKEN: ${{ secrets.DIFFUSERS_HF_HUB_READ_TOKEN }}
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RUN_COMPILE: yes
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run: |
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pytest -n 1 --max-worker-restart=0 --dist=loadfile -s -v -k "compile" --make-reports=tests_torch_compile_cuda tests/
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pytest -n 1 --max-worker-restart=0 --dist=loadfile -s -v -m "is_torch_compile" --make-reports=tests_torch_compile_cuda tests/
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- name: Failure short reports
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if: ${{ failure() }}
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run: cat reports/tests_torch_compile_cuda_failures_short.txt
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42
.github/workflows/push_tests.yml
vendored
42
.github/workflows/push_tests.yml
vendored
@@ -156,48 +156,6 @@ jobs:
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name: torch_cuda_test_reports_${{ matrix.module }}
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path: reports
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run_torch_compile_tests:
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name: PyTorch Compile CUDA tests
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runs-on:
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group: aws-g4dn-2xlarge
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container:
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image: diffusers/diffusers-pytorch-cuda
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options: --gpus all --shm-size "16gb" --ipc host
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steps:
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- name: Checkout diffusers
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uses: actions/checkout@v3
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with:
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fetch-depth: 2
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- name: NVIDIA-SMI
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run: |
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nvidia-smi
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- name: Install dependencies
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run: |
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uv pip install -e ".[quality,training]"
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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: Run example tests on GPU
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env:
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HF_TOKEN: ${{ secrets.DIFFUSERS_HF_HUB_READ_TOKEN }}
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RUN_COMPILE: yes
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run: |
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pytest -n 1 --max-worker-restart=0 --dist=loadfile -s -v -k "compile" --make-reports=tests_torch_compile_cuda tests/
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- name: Failure short reports
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if: ${{ failure() }}
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run: cat reports/tests_torch_compile_cuda_failures_short.txt
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- name: Test suite reports artifacts
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if: ${{ always() }}
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uses: actions/upload-artifact@v4
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with:
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name: torch_compile_test_reports
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path: reports
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run_xformers_tests:
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name: PyTorch xformers CUDA tests
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94
.github/workflows/push_tests_fast.yml
vendored
94
.github/workflows/push_tests_fast.yml
vendored
@@ -1,94 +0,0 @@
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name: Fast tests on main
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on:
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push:
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branches:
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- main
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paths:
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- "src/diffusers/**.py"
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- "examples/**.py"
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- "tests/**.py"
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concurrency:
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group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
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cancel-in-progress: true
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env:
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DIFFUSERS_IS_CI: yes
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HF_HOME: /mnt/cache
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OMP_NUM_THREADS: 8
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MKL_NUM_THREADS: 8
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HF_HUB_ENABLE_HF_TRANSFER: 1
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PYTEST_TIMEOUT: 600
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RUN_SLOW: no
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jobs:
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run_fast_tests:
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strategy:
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fail-fast: false
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matrix:
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config:
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- name: Fast PyTorch CPU tests on Ubuntu
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framework: pytorch
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runner: aws-general-8-plus
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image: diffusers/diffusers-pytorch-cpu
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report: torch_cpu
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- name: PyTorch Example CPU tests on Ubuntu
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framework: pytorch_examples
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runner: aws-general-8-plus
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image: diffusers/diffusers-pytorch-cpu
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report: torch_example_cpu
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name: ${{ matrix.config.name }}
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runs-on:
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group: ${{ matrix.config.runner }}
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container:
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image: ${{ matrix.config.image }}
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options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
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defaults:
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run:
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shell: bash
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steps:
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- name: Checkout diffusers
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uses: actions/checkout@v3
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with:
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fetch-depth: 2
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- name: Install dependencies
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run: |
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uv pip install -e ".[quality]"
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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: Run fast PyTorch CPU tests
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if: ${{ matrix.config.framework == 'pytorch' }}
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run: |
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pytest -n 4 --max-worker-restart=0 --dist=loadfile \
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-s -v -k "not Flax and not Onnx" \
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--make-reports=tests_${{ matrix.config.report }} \
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tests/
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- name: Run example PyTorch CPU tests
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if: ${{ matrix.config.framework == 'pytorch_examples' }}
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run: |
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uv pip install ".[training]"
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pytest -n 4 --max-worker-restart=0 --dist=loadfile \
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--make-reports=tests_${{ matrix.config.report }} \
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examples
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- name: Failure short reports
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if: ${{ failure() }}
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run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
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- name: Test suite reports artifacts
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if: ${{ always() }}
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uses: actions/upload-artifact@v4
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with:
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name: pr_${{ matrix.config.report }}_test_reports
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path: reports
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@@ -32,6 +32,7 @@ warnings.simplefilter(action="ignore", category=FutureWarning)
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def pytest_configure(config):
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config.addinivalue_line("markers", "big_accelerator: marks tests as requiring big accelerator resources")
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config.addinivalue_line("markers", "is_torch_compile: marks torch compilation tests")
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def pytest_addoption(parser):
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@@ -69,13 +69,12 @@ from ..testing_utils import (
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backend_synchronize,
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check_if_dicts_are_equal,
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get_python_version,
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is_torch_compile,
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numpy_cosine_similarity_distance,
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require_peft_backend,
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require_peft_version_greater,
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require_torch_2,
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require_torch_accelerator,
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require_torch_accelerator_with_training,
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require_torch_compile,
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require_torch_multi_accelerator,
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require_torch_version_greater,
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run_test_in_subprocess,
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@@ -783,7 +782,7 @@ class ModelTesterMixin:
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max_diff = (image - new_image).abs().max().item()
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self.assertLessEqual(max_diff, expected_max_diff, "Models give different forward passes")
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@is_torch_compile
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@require_torch_compile
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@require_torch_2
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@unittest.skipIf(
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get_python_version == (3, 12),
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@@ -2038,7 +2037,7 @@ class ModelPushToHubTester(unittest.TestCase):
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@require_torch_accelerator
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@require_torch_2
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@is_torch_compile
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@require_torch_compile
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@slow
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@require_torch_version_greater("2.7.1")
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class TorchCompileTesterMixin:
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@@ -2160,9 +2159,8 @@ class TorchCompileTesterMixin:
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@require_torch_2
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@require_torch_accelerator
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@require_peft_backend
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@require_peft_version_greater("0.14.0")
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@require_torch_version_greater("2.7.1")
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@is_torch_compile
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@require_torch_compile
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class LoraHotSwappingForModelTesterMixin:
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"""Test that hotswapping does not result in recompilation on the model directly.
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@@ -22,13 +22,13 @@ from ...testing_utils import (
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enable_full_determinism,
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torch_device,
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)
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from ..test_modeling_common import ModelTesterMixin, TorchCompileTesterMixin
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from ..test_modeling_common import ModelTesterMixin
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enable_full_determinism()
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class SkyReelsV2Transformer3DTests(ModelTesterMixin, TorchCompileTesterMixin, unittest.TestCase):
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class SkyReelsV2Transformer3DTests(ModelTesterMixin, unittest.TestCase):
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model_class = SkyReelsV2Transformer3DModel
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main_input_name = "hidden_states"
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uses_custom_attn_processor = True
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@@ -447,6 +447,25 @@ def require_big_accelerator(test_case):
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)(test_case)
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def require_torch_compile(test_case):
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"""
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Decorator marking compilation test.
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"""
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import pytest
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test_case = pytest.mark.is_torch_compile(test_case)
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if not is_torch_available():
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return unittest.skip("test requires PyTorch")(test_case)
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import torch
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if not (torch.cuda.is_available() or torch.xpu.is_available()):
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return unittest.skip("test requires PyTorch CUDA")(test_case)
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return unittest.skipUnless(_run_compile_tests, "test is torch compile")(test_case)
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def require_torch_accelerator_with_training(test_case):
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"""Decorator marking a test that requires an accelerator with support for training."""
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return unittest.skipUnless(
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