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yiyixuxuDN6
yiyixuxu
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DN6
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[Modular] Fast Tests (#11937)
* rearrage the params to groups: default params /image params /batch params / callback params * make style * add names property to pipeline blocks * style * remove more unused func * prepare_latents_inpaint always return noise and image_latents * up * up * update * update * update * update * update * update * update * update --------- Co-authored-by: DN6 <[email protected]>
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‎.github/workflows/pr_modular_tests.yml

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name: Fast PR tests for Modular
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on:
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pull_request:
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branches: [main]
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paths:
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- "src/diffusers/modular_pipelines/**.py"
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- "src/diffusers/models/modeling_utils.py"
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- "src/diffusers/models/model_loading_utils.py"
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- "src/diffusers/pipelines/pipeline_utils.py"
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- "src/diffusers/pipeline_loading_utils.py"
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- "src/diffusers/loaders/lora_base.py"
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- "src/diffusers/loaders/lora_pipeline.py"
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- "src/diffusers/loaders/peft.py"
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- "tests/modular_pipelines/**.py"
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- ".github/**.yml"
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- "utils/**.py"
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- "setup.py"
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push:
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branches:
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- ci-*
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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_HUB_ENABLE_HF_TRANSFER: 1
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OMP_NUM_THREADS: 4
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MKL_NUM_THREADS: 4
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PYTEST_TIMEOUT: 60
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jobs:
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check_code_quality:
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runs-on: ubuntu-22.04
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: "3.10"
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install .[quality]
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- name: Check quality
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run: make quality
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- name: Check if failure
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if: ${{ failure() }}
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run: |
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echo "Quality check failed. Please ensure the right dependency versions are installed with 'pip install -e .[quality]' and run 'make style && make quality'" >> $GITHUB_STEP_SUMMARY
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check_repository_consistency:
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needs: check_code_quality
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runs-on: ubuntu-22.04
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: "3.10"
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install .[quality]
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- name: Check repo consistency
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run: |
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python utils/check_copies.py
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python utils/check_dummies.py
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python utils/check_support_list.py
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make deps_table_check_updated
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- name: Check if failure
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if: ${{ failure() }}
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run: |
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echo "Repo consistency check failed. Please ensure the right dependency versions are installed with 'pip install -e .[quality]' and run 'make fix-copies'" >> $GITHUB_STEP_SUMMARY
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run_fast_tests:
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needs: [check_code_quality, check_repository_consistency]
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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 Modular Pipeline CPU tests
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framework: pytorch_pipelines
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runner: aws-highmemory-32-plus
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image: diffusers/diffusers-pytorch-cpu
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report: torch_cpu_modular_pipelines
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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: ${{ matrix.config.image }}
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options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
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defaults:
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run:
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shell: bash
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steps:
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- name: Checkout diffusers
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uses: actions/checkout@v3
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with:
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fetch-depth: 2
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- name: Install dependencies
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run: |
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python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
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python -m uv pip install -e [quality,test]
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pip uninstall transformers -y && python -m uv pip install -U transformers@git+https://github.com/huggingface/transformers.git --no-deps
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pip uninstall accelerate -y && python -m uv pip install -U accelerate@git+https://github.com/huggingface/accelerate.git --no-deps
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- name: Environment
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run: |
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python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
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python utils/print_env.py
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- name: Run fast PyTorch Pipeline CPU tests
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if: ${{ matrix.config.framework == 'pytorch_pipelines' }}
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run: |
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python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
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python -m pytest -n 8 --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/modular_pipelines
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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.framework }}_${{ matrix.config.report }}_test_reports
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path: reports
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‎src/diffusers/modular_pipelines/modular_pipeline.py

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@@ -493,6 +493,22 @@ def combine_outputs(*named_output_lists: List[Tuple[str, List[OutputParam]]]) ->
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return list(combined_dict.values())
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@property
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def input_names(self) -> List[str]:
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return [input_param.name for input_param in self.inputs]
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@property
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def intermediate_input_names(self) -> List[str]:
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return [input_param.name for input_param in self.intermediate_inputs]
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@property
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def intermediate_output_names(self) -> List[str]:
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return [output_param.name for output_param in self.intermediate_outputs]
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@property
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def output_names(self) -> List[str]:
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return [output_param.name for output_param in self.outputs]
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class PipelineBlock(ModularPipelineBlocks):
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"""
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type_hint=type_hint,
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**spec_dict,
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)
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def set_progress_bar_config(self, **kwargs):
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for sub_block_name, sub_block in self.blocks.sub_blocks.items():
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if hasattr(sub_block, "set_progress_bar_config"):
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sub_block.set_progress_bar_config(**kwargs)

‎src/diffusers/modular_pipelines/stable_diffusion_xl/before_denoise.py

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timestep=None,
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is_strength_max=True,
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add_noise=True,
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return_noise=False,
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return_image_latents=False,
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):
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shape = (
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batch_size,
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if image.shape[1] == 4:
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image_latents = image.to(device=device, dtype=dtype)
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image_latents = image_latents.repeat(batch_size // image_latents.shape[0], 1, 1, 1)
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elif return_image_latents or (latents is None and not is_strength_max):
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elif latents is None and not is_strength_max:
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image = image.to(device=device, dtype=dtype)
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image_latents = self._encode_vae_image(components, image=image, generator=generator)
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image_latents = image_latents.repeat(batch_size // image_latents.shape[0], 1, 1, 1)
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noise = randn_tensor(shape, generator=generator, device=device, dtype=dtype)
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latents = image_latents.to(device)
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outputs = (latents,)
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if return_noise:
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outputs += (noise,)
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if return_image_latents:
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outputs += (image_latents,)
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outputs = (latents, noise, image_latents)
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return outputs
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block_state.height = block_state.image_latents.shape[-2] * components.vae_scale_factor
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block_state.width = block_state.image_latents.shape[-1] * components.vae_scale_factor
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block_state.latents, block_state.noise = self.prepare_latents_inpaint(
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block_state.latents, block_state.noise, block_state.image_latents = self.prepare_latents_inpaint(
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components,
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block_state.batch_size * block_state.num_images_per_prompt,
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components.num_channels_latents,
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timestep=block_state.latent_timestep,
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is_strength_max=block_state.is_strength_max,
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add_noise=block_state.add_noise,
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return_noise=True,
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return_image_latents=False,
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)
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# 7. Prepare mask latent variables

‎tests/modular_pipelines/__init__.py

Whitespace-only changes.

‎tests/modular_pipelines/stable_diffusion_xl/__init__.py

Whitespace-only changes.

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