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.github/workflows/pr_style_bot.yml

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name: PR Style Bot
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on:
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issue_comment:
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types: [created]
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permissions:
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contents: write
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pull-requests: write
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jobs:
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run-style-bot:
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if: >
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contains(github.event.comment.body, '@bot /style') &&
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github.event.issue.pull_request != null
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runs-on: ubuntu-latest
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steps:
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- name: Extract PR details
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id: pr_info
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uses: actions/github-script@v6
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with:
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script: |
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const prNumber = context.payload.issue.number;
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const { data: pr } = await github.rest.pulls.get({
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owner: context.repo.owner,
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repo: context.repo.repo,
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pull_number: prNumber
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});
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// We capture both the branch ref and the "full_name" of the head repo
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// so that we can check out the correct repository & branch (including forks).
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core.setOutput("prNumber", prNumber);
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core.setOutput("headRef", pr.head.ref);
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core.setOutput("headRepoFullName", pr.head.repo.full_name);
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- name: Check out PR branch
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uses: actions/checkout@v3
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env:
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HEADREPOFULLNAME: ${{ steps.pr_info.outputs.headRepoFullName }}
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HEADREF: ${{ steps.pr_info.outputs.headRef }}
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with:
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# Instead of checking out the base repo, use the contributor's repo name
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repository: ${{ env.HEADREPOFULLNAME }}
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ref: ${{ env.HEADREF }}
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# You may need fetch-depth: 0 for being able to push
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fetch-depth: 0
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token: ${{ secrets.GITHUB_TOKEN }}
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- name: Debug
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env:
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HEADREPOFULLNAME: ${{ steps.pr_info.outputs.headRepoFullName }}
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HEADREF: ${{ steps.pr_info.outputs.headRef }}
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PRNUMBER: ${{ steps.pr_info.outputs.prNumber }}
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run: |
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echo "PR number: ${{ env.PRNUMBER }}"
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echo "Head Ref: ${{ env.HEADREF }}"
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echo "Head Repo Full Name: ${{ env.HEADREPOFULLNAME }}"
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- name: Set up Python
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uses: actions/setup-python@v4
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- name: Install dependencies
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run: |
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pip install .[quality]
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- name: Download Makefile from main branch
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run: |
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curl -o main_Makefile https://raw.githubusercontent.com/huggingface/diffusers/main/Makefile
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- name: Compare Makefiles
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run: |
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if ! diff -q main_Makefile Makefile; then
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echo "Error: The Makefile has changed. Please ensure it matches the main branch."
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exit 1
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fi
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echo "No changes in Makefile. Proceeding..."
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rm -rf main_Makefile
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- name: Run make style and make quality
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run: |
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make style && make quality
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- name: Commit and push changes
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id: commit_and_push
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env:
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HEADREPOFULLNAME: ${{ steps.pr_info.outputs.headRepoFullName }}
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HEADREF: ${{ steps.pr_info.outputs.headRef }}
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PRNUMBER: ${{ steps.pr_info.outputs.prNumber }}
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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run: |
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echo "HEADREPOFULLNAME: ${{ env.HEADREPOFULLNAME }}, HEADREF: ${{ env.HEADREF }}"
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# Configure git with the Actions bot user
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git config user.name "github-actions[bot]"
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git config user.email "github-actions[bot]@users.noreply.github.com"
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# Make sure your 'origin' remote is set to the contributor's fork
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git remote set-url origin "https://x-access-token:${GITHUB_TOKEN}@github.com/${{ env.HEADREPOFULLNAME }}.git"
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# If there are changes after running style/quality, commit them
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if [ -n "$(git status --porcelain)" ]; then
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git add .
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git commit -m "Apply style fixes"
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# Push to the original contributor's forked branch
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git push origin HEAD:${{ env.HEADREF }}
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echo "changes_pushed=true" >> $GITHUB_OUTPUT
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else
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echo "No changes to commit."
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echo "changes_pushed=false" >> $GITHUB_OUTPUT
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fi
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- name: Comment on PR with workflow run link
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if: steps.commit_and_push.outputs.changes_pushed == 'true'
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uses: actions/github-script@v6
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with:
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script: |
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const prNumber = parseInt(process.env.prNumber, 10);
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const runUrl = `${process.env.GITHUB_SERVER_URL}/${process.env.GITHUB_REPOSITORY}/actions/runs/${process.env.GITHUB_RUN_ID}`
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await github.rest.issues.createComment({
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owner: context.repo.owner,
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repo: context.repo.repo,
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issue_number: prNumber,
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body: `Style fixes have been applied. [View the workflow run here](${runUrl}).`
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});
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env:
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prNumber: ${{ steps.pr_info.outputs.prNumber }}

.github/workflows/pr_tests.yml

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on:
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pull_request:
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branches:
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- main
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branches: [main]
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types: [synchronize]
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paths:
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- "src/diffusers/**.py"
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- "benchmarks/**.py"
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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() }}

docs/source/en/_toctree.yml

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title: ConsisIDTransformer3DModel
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- local: api/models/cogview3plus_transformer2d
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title: CogView3PlusTransformer2DModel
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- local: api/models/cogview4_transformer2d
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title: CogView4Transformer2DModel
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- local: api/models/dit_transformer2d
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title: DiTTransformer2DModel
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- local: api/models/flux_transformer
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title: CogVideoX
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- local: api/pipelines/cogview3
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title: CogView3
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- local: api/pipelines/cogview4
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title: CogView4
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- local: api/pipelines/consisid
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title: ConsisID
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- local: api/pipelines/consistency_models

docs/source/en/api/activations.md

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## ApproximateGELU
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[[autodoc]] models.activations.ApproximateGELU
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## SwiGLU
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[[autodoc]] models.activations.SwiGLU
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## FP32SiLU
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[[autodoc]] models.activations.FP32SiLU
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## LinearActivation
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[[autodoc]] models.activations.LinearActivation

docs/source/en/api/attnprocessor.md

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## XLAFlashAttnProcessor2_0
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[[autodoc]] models.attention_processor.XLAFlashAttnProcessor2_0
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## XFormersJointAttnProcessor
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[[autodoc]] models.attention_processor.XFormersJointAttnProcessor
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## IPAdapterXFormersAttnProcessor
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[[autodoc]] models.attention_processor.IPAdapterXFormersAttnProcessor
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## FluxIPAdapterJointAttnProcessor2_0
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[[autodoc]] models.attention_processor.FluxIPAdapterJointAttnProcessor2_0
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## XLAFluxFlashAttnProcessor2_0
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[[autodoc]] models.attention_processor.XLAFluxFlashAttnProcessor2_0

docs/source/en/api/loaders/lora.md

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- [`FluxLoraLoaderMixin`] provides similar functions for [Flux](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux).
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- [`CogVideoXLoraLoaderMixin`] provides similar functions for [CogVideoX](https://huggingface.co/docs/diffusers/main/en/api/pipelines/cogvideox).
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- [`Mochi1LoraLoaderMixin`] provides similar functions for [Mochi](https://huggingface.co/docs/diffusers/main/en/api/pipelines/mochi).
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- [`LTXVideoLoraLoaderMixin`] provides similar functions for [LTX-Video](https://huggingface.co/docs/diffusers/main/en/api/pipelines/ltx_video).
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- [`SanaLoraLoaderMixin`] provides similar functions for [Sana](https://huggingface.co/docs/diffusers/main/en/api/pipelines/sana).
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- [`HunyuanVideoLoraLoaderMixin`] provides similar functions for [HunyuanVideo](https://huggingface.co/docs/diffusers/main/en/api/pipelines/hunyuan_video).
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- [`Lumina2LoraLoaderMixin`] provides similar functions for [Lumina2](https://huggingface.co/docs/diffusers/main/en/api/pipelines/lumina2).
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- [`AmusedLoraLoaderMixin`] is for the [`AmusedPipeline`].
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- [`LoraBaseMixin`] provides a base class with several utility methods to fuse, unfuse, unload, LoRAs and more.
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[[autodoc]] loaders.lora_pipeline.Mochi1LoraLoaderMixin
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## LTXVideoLoraLoaderMixin
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[[autodoc]] loaders.lora_pipeline.LTXVideoLoraLoaderMixin
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## SanaLoraLoaderMixin
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[[autodoc]] loaders.lora_pipeline.SanaLoraLoaderMixin
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## HunyuanVideoLoraLoaderMixin
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[[autodoc]] loaders.lora_pipeline.HunyuanVideoLoraLoaderMixin
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## Lumina2LoraLoaderMixin
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[[autodoc]] loaders.lora_pipeline.Lumina2LoraLoaderMixin
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## AmusedLoraLoaderMixin
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[[autodoc]] loaders.lora_pipeline.AmusedLoraLoaderMixin
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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License. -->
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# CogView4Transformer2DModel
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A Diffusion Transformer model for 2D data from [CogView4]()
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The model can be loaded with the following code snippet.
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```python
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from diffusers import CogView4Transformer2DModel
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transformer = CogView4Transformer2DModel.from_pretrained("THUDM/CogView4-6B", subfolder="transformer", torch_dtype=torch.bfloat16).to("cuda")
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```
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## CogView4Transformer2DModel
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[[autodoc]] CogView4Transformer2DModel
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## Transformer2DModelOutput
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[[autodoc]] models.modeling_outputs.Transformer2DModelOutput

docs/source/en/api/normalization.md

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## AdaGroupNorm
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[[autodoc]] models.normalization.AdaGroupNorm
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## AdaLayerNormContinuous
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[[autodoc]] models.normalization.AdaLayerNormContinuous
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## RMSNorm
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[[autodoc]] models.normalization.RMSNorm
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## GlobalResponseNorm
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[[autodoc]] models.normalization.GlobalResponseNorm
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## LuminaLayerNormContinuous
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[[autodoc]] models.normalization.LuminaLayerNormContinuous
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## SD35AdaLayerNormZeroX
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[[autodoc]] models.normalization.SD35AdaLayerNormZeroX
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## AdaLayerNormZeroSingle
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[[autodoc]] models.normalization.AdaLayerNormZeroSingle
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## LuminaRMSNormZero
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[[autodoc]] models.normalization.LuminaRMSNormZero
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## LpNorm
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[[autodoc]] models.normalization.LpNorm
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## CogView3PlusAdaLayerNormZeroTextImage
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[[autodoc]] models.normalization.CogView3PlusAdaLayerNormZeroTextImage
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## CogVideoXLayerNormZero
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[[autodoc]] models.normalization.CogVideoXLayerNormZero
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## MochiRMSNormZero
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[[autodoc]] models.transformers.transformer_mochi.MochiRMSNormZero
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## MochiRMSNorm
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[[autodoc]] models.normalization.MochiRMSNorm
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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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-->
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# CogView4
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<Tip>
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Make sure to check out the Schedulers [guide](../../using-diffusers/schedulers) to learn how to explore the tradeoff between scheduler speed and quality, and see the [reuse components across pipelines](../../using-diffusers/loading#reuse-a-pipeline) section to learn how to efficiently load the same components into multiple pipelines.
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</Tip>
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This pipeline was contributed by [zRzRzRzRzRzRzR](https://github.com/zRzRzRzRzRzRzR). The original codebase can be found [here](https://huggingface.co/THUDM). The original weights can be found under [hf.co/THUDM](https://huggingface.co/THUDM).
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## CogView4Pipeline
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[[autodoc]] CogView4Pipeline
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- all
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- __call__
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## CogView4PipelineOutput
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[[autodoc]] pipelines.cogview4.pipeline_output.CogView4PipelineOutput

docs/source/en/api/utilities.md

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## apply_layerwise_casting
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[[autodoc]] hooks.layerwise_casting.apply_layerwise_casting
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## apply_group_offloading
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[[autodoc]] hooks.group_offloading.apply_group_offloading

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