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Merge branch 'main' into refactor/condition-embedders-submodule
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‎.ai/pipelines.md‎

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@@ -60,3 +60,7 @@ When adding a new pipeline (or reviewing one), skim `pipeline_flux.py`, `pipelin
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4. **Subclassing an existing pipeline for a variant.** Don't use an existing pipeline class (e.g. `FluxPipeline`) to override another (e.g. `FluxImg2ImgPipeline`) inside the core `src/` codebase. Each pipeline lives in its own file with its own class, even if it shares 90% of `__call__` with a sibling. Convention across diffusers — flux, sdxl, wan, qwenimage — is duplicated `__call__` between img2img / text2img / inpaint variants, not subclassing. Reuse private utilities (shared schedulers, prep functions) but not the pipeline class itself.
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5. **Copying a method from another pipeline without `# Copied from`.** When you reuse a method like `encode_prompt`, `prepare_latents`, `check_inputs`, or `_prepare_latent_image_ids` from another pipeline, add a `# Copied from` annotation so `make fix-copies` keeps the two in sync. Forgetting it means future refactors to the source drift away from your copy silently — and reviewers waste time spotting near-identical code that should have been linked. The annotation grammar (decorator placement, rename syntax with `with old->new`, etc.) is implemented in [`utils/check_copies.py`](../utils/check_copies.py) — read it for the exact rules.
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6. **Be deliberate about methods on the pipeline.** `__call__` is the user's mental model. The methods on the class are how they navigate it. Diffusers convention (flux, sdxl, wan, qwenimage) is a flat class body of public lifecycle methods (`__init__`, `check_inputs`, `encode_prompt`, `prepare_latents`, `__call__`). Two principles, not strict rules — use judgment:
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- **If a method is called from `__call__`, and it's a step in the pipeline lifecycle, make it public.** Each call from `__call__` should correspond to a step a user can identify: either a standard one (`encode_prompt`, `prepare_latents`, `set_timesteps`, …) or a pipeline-specific one (`prepare_src_latents`, `prepare_reference_audio_latents`, …). Don't gate these behind a `_`; they're part of the pipeline's API surface alongside their standard siblings.
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- **If a method is only used by another method, make it private (`_foo`) or lift it to a module-level function — and keep the count down.** Before adding one, see if the logic can be absorbed into its caller. Unless you expect the helper to be reused by another method (or another task pipeline), absorbing is usually the better call — especially when the body is small. Avoid a pipeline class littered with private helpers that bury the lifecycle..

‎.github/workflows/benchmark.yml‎

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uv pip install -r benchmarks/requirements.txt
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- name: Environment
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run: |
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python utils/print_env.py
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diffusers-cli env
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- name: Diffusers Benchmarking
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env:
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HF_TOKEN: ${{ secrets.DIFFUSERS_HF_HUB_READ_TOKEN }}

‎.github/workflows/claude_review.yml‎

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GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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PR_NUMBER: ${{ github.event.issue.number || github.event.pull_request.number }}
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COMMENT_USER: ${{ github.event.comment.user.login }}
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BASE_BRANCH: ${{ github.event.repository.default_branch }}
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run: |
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set -euo pipefail
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exit 0
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fi
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# For fork PRs, an earlier step redirected `origin` to a local bare
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# repo to sandbox claude-code-action. Undo that redirect so our push
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# reaches the real base repo. Safe: only Claude's edits within the
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# allowed paths are committed below — never the fork's other changes.
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git config --unset-all url."file:///tmp/local-origin.git".insteadOf 2>/dev/null || true
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PR_INFO=$(gh pr view "$PR_NUMBER" --json headRefName,isCrossRepository)
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PR_BRANCH=$(echo "$PR_INFO" | jq -r '.headRefName')
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IS_FORK=$(echo "$PR_INFO" | jq -r '.isCrossRepository')
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# COMMIT THIS isn't supported on fork PRs: we can't push to the
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# fork's branch, and falling back to main almost always conflicts
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# once the PR touches files that also moved on main. Bail early —
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# Claude's review comment with the suggested diff still stands.
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if [[ "$IS_FORK" == "true" ]]; then
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post_status "ℹ️ \`COMMIT THIS\` isn't supported on fork PRs. Apply Claude's suggestions manually, or open an issue to track them. See [workflow run]($RUN_URL)."
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exit 0
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fi
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git config user.name "claude[bot]"
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git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
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exit 1
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fi
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PR_BRANCH=$(gh pr view "$PR_NUMBER" --json headRefName --jq '.headRefName')
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if [[ "$PR_BRANCH" == claude/pr-* ]]; then
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# Source PR is already a Claude-opened PR — iterate in place by
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# committing and pushing straight to its head branch instead of
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exit 0
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fi
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# Otherwise: commit on the source PR's branch to get a clean SHA,
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# then cherry-pick onto a fresh branch cut from the default branch.
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# The follow-up PR's diff is therefore exactly Claude's edits vs. main.
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# Target the source PR's head branch. The follow-up then applies
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# cleanly regardless of how main has diverged, and merging it lands
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# Claude's edits onto the PR for the maintainer to fold in.
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BASE_BRANCH="$PR_BRANCH"
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# Commit on the source PR's branch to get a clean SHA, then
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# cherry-pick onto a fresh branch cut from BASE_BRANCH so the
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# follow-up PR's diff is exactly Claude's edits vs. BASE_BRANCH.
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NEW_BRANCH="claude/pr-${PR_NUMBER}-$(date -u +%Y%m%d-%H%M%S)"
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git commit -m "Apply changes from Claude (requested by @${COMMENT_USER} on #${PR_NUMBER})
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--title "Apply Claude's changes from #${PR_NUMBER}" \
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--body "Automated PR with edits Claude made in response to \`COMMIT THIS\` from @${COMMENT_USER} on [#${PR_NUMBER}](${GITHUB_SERVER_URL}/${GITHUB_REPOSITORY}/pull/${PR_NUMBER}).
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Targets \`${BASE_BRANCH}\` — independent of #${PR_NUMBER}. Further \`COMMIT THIS\` requests on *this* PR will commit directly to it.")
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Targets \`${BASE_BRANCH}\` (the head branch of #${PR_NUMBER}). Merging this brings Claude's edits into that PR.")
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post_status "✅ Opened follow-up PR (into \`${BASE_BRANCH}\`) with Claude's edits: ${NEW_PR_URL}"

‎.github/workflows/nightly_tests.yml‎

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uv pip install pytest-reportlog
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python utils/print_env.py
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diffusers-cli env
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uv pip uninstall accelerate && uv pip install -U accelerate@git+https://github.com/huggingface/accelerate.git
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uv pip install pytest-reportlog
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run: diffusers-cli env
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- name: Run nightly PyTorch CUDA tests for non-pipeline modules
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python utils/print_env.py
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diffusers-cli env
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- name: Run torch compile tests on GPU
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diffusers-cli env
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diffusers-cli env
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- name: Run PyTorch CUDA tests
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diffusers-cli env
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# ${CONDA_RUN} diffusers-cli env
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# ${CONDA_RUN} diffusers-cli env
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# env:

‎.github/workflows/pr_modular_tests.yml‎

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python utils/check_copies.py
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- name: Environment
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diffusers-cli env
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- name: Run fast PyTorch Pipeline CPU tests
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run: |

‎.github/workflows/pr_test_fetcher.yml‎

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- name: Environment
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python utils/print_env.py
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- name: Run all selected tests on CPU
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- name: Run Hub tests for models, schedulers, and pipelines on a staging env
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if: ${{ matrix.config.framework == 'hub_tests_pytorch' }}

‎.github/workflows/pr_tests.yml‎

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- name: Run fast PyTorch Pipeline CPU tests
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diffusers-cli env
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- name: Run Hub tests for models, schedulers, and pipelines on a staging env
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diffusers-cli env
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‎.github/workflows/pr_tests_gpu.yml‎

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diffusers-cli env
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- name: Run example tests on GPU
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‎.github/workflows/push_tests.yml‎

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python utils/print_env.py
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diffusers-cli env
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- name: Run PyTorch CUDA tests
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‎.github/workflows/push_tests_fast.yml‎

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- name: Run fast PyTorch CPU tests
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