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.github/ISSUE_TEMPLATE/bug-report.yml

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description: |
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Your issue will be replied to more quickly if you can figure out the right person to tag with @.
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If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
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All issues are read by one of the core maintainers, so if you don't know who to tag, just leave this blank and
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a core maintainer will ping the right person.
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Please tag a maximum of 2 people.
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Questions on DiffusionPipeline (Saving, Loading, From pretrained, ...):
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Questions on pipelines:
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- Stable Diffusion @yiyixuxu @DN6 @sayakpaul
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- Stable Diffusion XL @yiyixuxu @sayakpaul @DN6
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- Kandinsky @yiyixuxu
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- ControlNet @sayakpaul @yiyixuxu @DN6
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- T2I Adapter @sayakpaul @yiyixuxu @DN6
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- IF @DN6
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- Text-to-Video / Video-to-Video @DN6 @sayakpaul
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- Wuerstchen @DN6
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- Stable Diffusion @yiyixuxu @DN6 @sayakpaul
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- Stable Diffusion XL @yiyixuxu @sayakpaul @DN6
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- Kandinsky @yiyixuxu
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- ControlNet @sayakpaul @yiyixuxu @DN6
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- T2I Adapter @sayakpaul @yiyixuxu @DN6
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- IF @DN6
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- Text-to-Video / Video-to-Video @DN6 @sayakpaul
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- Wuerstchen @DN6
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- Other: @yiyixuxu @DN6
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Questions on models:
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- UNet @DN6 @yiyixuxu @sayakpaul
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- VAE @sayakpaul @DN6 @yiyixuxu
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- Transformers/Attention @DN6 @yiyixuxu @sayakpaul @DN6
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- UNet @DN6 @yiyixuxu @sayakpaul
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- VAE @sayakpaul @DN6 @yiyixuxu
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- Transformers/Attention @DN6 @yiyixuxu @sayakpaul @DN6
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Questions on Schedulers: @yiyixuxu
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Questions on Schedulers: @yiyixuxu
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Questions on LoRA: @sayakpaul
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Questions on LoRA: @sayakpaul
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Questions on Textual Inversion: @sayakpaul
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Questions on Textual Inversion: @sayakpaul
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Questions on Training:
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- DreamBooth @sayakpaul
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- Text-to-Image Fine-tuning @sayakpaul
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- Textual Inversion @sayakpaul
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- ControlNet @sayakpaul
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Questions on Training:
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- DreamBooth @sayakpaul
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- Text-to-Image Fine-tuning @sayakpaul
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- Textual Inversion @sayakpaul
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- ControlNet @sayakpaul
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Questions on Tests: @DN6 @sayakpaul @yiyixuxu
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Questions on Tests: @DN6 @sayakpaul @yiyixuxu
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Questions on Documentation: @stevhliu
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Questions on JAX- and MPS-related things: @pcuenca
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Questions on audio pipelines: @DN6
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Questions on audio pipelines: @DN6
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placeholder: "@Username ..."

.github/PULL_REQUEST_TEMPLATE.md

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Core library:
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- Schedulers: @yiyixuxu
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- Schedulers: @yiyixuxu
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- Pipelines: @sayakpaul @yiyixuxu @DN6
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- Training examples: @sayakpaul
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- Training examples: @sayakpaul
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- Docs: @stevhliu and @sayakpaul
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- JAX and MPS: @pcuenca
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- Audio: @sanchit-gandhi

.github/workflows/mirror_community_pipeline.yml

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# If ref is 'refs/heads/main' => set 'main'
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# Else it must be a tag => set {tag}
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- name: Set checkout_ref and path_in_repo
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run: |
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run: |
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if [ "${{ github.event_name }}" == "workflow_dispatch" ]; then
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if [ -z "${{ github.event.inputs.ref }}" ]; then
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echo "Error: Missing ref input"

.github/workflows/notify_slack_about_release.yml

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steps:
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- uses: actions/checkout@v3
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- name: Setup Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.8'
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- name: Notify Slack about the release
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env:
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SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL }}

.github/workflows/pr_dependency_test.yml

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run: |
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python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
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pytest tests/others/test_dependencies.py
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.github/workflows/pr_test_peft_backend.yml

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-s -v \
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--make-reports=tests_models_lora_${{ matrix.config.report }} \
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tests/models/ -k "lora"
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- name: Failure short reports
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if: ${{ failure() }}
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run: |
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cat reports/tests_${{ matrix.config.report }}_failures_short.txt
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cat reports/tests_models_lora_${{ matrix.config.report }}_failures_short.txt
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- name: Test suite reports artifacts
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uses: actions/upload-artifact@v2

.github/workflows/pypi_publish.yaml

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ref: ${{ needs.find-and-checkout-latest-branch.outputs.latest_branch }}
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- name: Setup Python
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- name: Install dependencies
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python -m pip install --upgrade pip
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pip install -U setuptools wheel twine
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pip install -U torch --index-url https://download.pytorch.org/whl/cpu
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pip install -U transformers
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- name: Build the dist files
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run: python setup.py bdist_wheel && python setup.py sdist
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- name: Publish to the test PyPI
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run: twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
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run: twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
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.github/workflows/run_tests_from_a_pr.yml

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test:
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- name: Install pytest
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CONTRIBUTING.md

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This is because of the same reasons put forward in [6. Contribute a community pipeline](#6-contribute-a-community-pipeline) for official pipelines vs. community pipelines: It is not feasible for the core maintainers to maintain all possible training methods for diffusion models.
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If the Diffusers core maintainers and the community consider a certain training paradigm to be too experimental or not popular enough, the corresponding training code should be put in the `research_projects` folder and maintained by the author.
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Both official training and research examples consist of a directory that contains one or more training scripts, a requirements.txt file, and a README.md file. In order for the user to make use of the
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Both official training and research examples consist of a directory that contains one or more training scripts, a `requirements.txt` file, and a `README.md` file. In order for the user to make use of the
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training examples, it is required to clone the repository:
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```bash
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cd diffusers
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pip install -r examples/<your-example-folder>/requirements.txt
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Therefore when adding an example, the `requirements.txt` file shall define all pip dependencies required for your training example so that once all those are installed, the user can run the example's training script. See, for example, the [DreamBooth `requirements.txt` file](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/requirements.txt).
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### Style guide
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For documentation strings, 🧨 Diffusers follows the [Google style](https://google.github.io/styleguide/pyguide.html).
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For documentation strings, 🧨 Diffusers follows the [Google style](https://google.github.io/styleguide/pyguide.html).

docs/source/en/api/models/pixart_transformer2d.md

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# PixArtTransformer2DModel
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A Transformer model for image-like data from [PixArt-Alpha](https://huggingface.co/papers/2310.00426) and [PixArt-Sigma](https://huggingface.co/papers/2403.04692).
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A Transformer model for image-like data from [PixArt-Alpha](https://huggingface.co/papers/2310.00426) and [PixArt-Sigma](https://huggingface.co/papers/2403.04692).
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## PixArtTransformer2DModel
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