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16 Commits

Author SHA1 Message Date
Dhruv Nair
43f72b2940 update 2024-02-15 12:34:16 +00:00
Dhruv Nair
36e52ef801 Merge branch 'unet-refactor' of https://github.com/huggingface/diffusers into unet-refactor 2024-02-15 09:36:05 +00:00
Dhruv Nair
95fcd61904 update 2024-02-15 09:35:37 +00:00
Dhruv Nair
8f824bf0ab Merge branch 'main' into unet-refactor 2024-02-05 19:56:09 +05:30
Dhruv Nair
89bcec9a0d update 2024-02-05 13:38:33 +00:00
Dhruv Nair
f404b6926e update 2024-02-05 13:08:56 +00:00
Dhruv Nair
69f4b8ff5a update 2024-02-05 12:55:55 +00:00
Dhruv Nair
f0ec02350a update 2024-02-05 11:30:55 +00:00
Dhruv Nair
9fdd6de30f update 2024-02-05 10:47:02 +00:00
Dhruv Nair
aa3b85bdd6 Merge branch 'main' into unet-refactor 2024-02-05 08:17:41 +00:00
Dhruv Nair
0953fed52b update 2024-01-04 08:54:00 +00:00
Dhruv Nair
bd375a8034 update 2024-01-04 06:57:36 +00:00
Dhruv Nair
17105d973c update 2024-01-03 16:43:09 +00:00
Dhruv Nair
32e04da6cf update 2024-01-03 16:08:10 +00:00
Dhruv Nair
c1e812b8fd Merge branch 'main' into unet-refactor 2024-01-03 12:09:10 +00:00
Dhruv Nair
784f4e9646 update 2023-12-19 11:57:01 +00:00
891 changed files with 14681 additions and 25593 deletions

View File

@@ -66,32 +66,32 @@ body:
Questions on DiffusionPipeline (Saving, Loading, From pretrained, ...):
Questions on pipelines:
- Stable Diffusion @yiyixuxu @DN6 @sayakpaul
- Stable Diffusion XL @yiyixuxu @sayakpaul @DN6
- Kandinsky @yiyixuxu
- ControlNet @sayakpaul @yiyixuxu @DN6
- T2I Adapter @sayakpaul @yiyixuxu @DN6
- IF @DN6
- Text-to-Video / Video-to-Video @DN6 @sayakpaul
- Wuerstchen @DN6
- Stable Diffusion @yiyixuxu @DN6 @sayakpaul @patrickvonplaten
- Stable Diffusion XL @yiyixuxu @sayakpaul @DN6 @patrickvonplaten
- Kandinsky @yiyixuxu @patrickvonplaten
- ControlNet @sayakpaul @yiyixuxu @DN6 @patrickvonplaten
- T2I Adapter @sayakpaul @yiyixuxu @DN6 @patrickvonplaten
- IF @DN6 @patrickvonplaten
- Text-to-Video / Video-to-Video @DN6 @sayakpaul @patrickvonplaten
- Wuerstchen @DN6 @patrickvonplaten
- Other: @yiyixuxu @DN6
Questions on models:
- UNet @DN6 @yiyixuxu @sayakpaul
- VAE @sayakpaul @DN6 @yiyixuxu
- Transformers/Attention @DN6 @yiyixuxu @sayakpaul @DN6
- UNet @DN6 @yiyixuxu @sayakpaul @patrickvonplaten
- VAE @sayakpaul @DN6 @yiyixuxu @patrickvonplaten
- Transformers/Attention @DN6 @yiyixuxu @sayakpaul @DN6 @patrickvonplaten
Questions on Schedulers: @yiyixuxu
Questions on Schedulers: @yiyixuxu @patrickvonplaten
Questions on LoRA: @sayakpaul
Questions on LoRA: @sayakpaul @patrickvonplaten
Questions on Textual Inversion: @sayakpaul
Questions on Textual Inversion: @sayakpaul @patrickvonplaten
Questions on Training:
- DreamBooth @sayakpaul
- Text-to-Image Fine-tuning @sayakpaul
- Textual Inversion @sayakpaul
- ControlNet @sayakpaul
- DreamBooth @sayakpaul @patrickvonplaten
- Text-to-Image Fine-tuning @sayakpaul @patrickvonplaten
- Textual Inversion @sayakpaul @patrickvonplaten
- ControlNet @sayakpaul @patrickvonplaten
Questions on Tests: @DN6 @sayakpaul @yiyixuxu
@@ -99,7 +99,7 @@ body:
Questions on JAX- and MPS-related things: @pcuenca
Questions on audio pipelines: @DN6
Questions on audio pipelines: @DN6 @patrickvonplaten

View File

@@ -38,13 +38,13 @@ members/contributors who may be interested in your PR.
Core library:
- Schedulers: @yiyixuxu
- Pipelines: @sayakpaul @yiyixuxu @DN6
- Training examples: @sayakpaul
- Docs: @stevhliu and @sayakpaul
- Schedulers: @yiyixuxu and @patrickvonplaten
- Pipelines: @patrickvonplaten and @sayakpaul
- Training examples: @sayakpaul and @patrickvonplaten
- Docs: @stevhliu and @yiyixuxu
- JAX and MPS: @pcuenca
- Audio: @sanchit-gandhi
- General functionalities: @sayakpaul @yiyixuxu @DN6
- General functionalities: @patrickvonplaten and @sayakpaul
Integrations:

View File

@@ -1,7 +1,6 @@
name: Benchmarking tests
on:
workflow_dispatch:
schedule:
- cron: "30 1 1,15 * *" # every 2 weeks on the 1st and the 15th of every month at 1:30 AM
@@ -32,9 +31,8 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install pandas peft
python -m pip install -e .[quality,test]
python -m pip install pandas
- name: Environment
run: |
python utils/print_env.py

View File

@@ -1,58 +1,21 @@
name: Test, build, and push Docker images
name: Build Docker images (nightly)
on:
pull_request: # During PRs, we just check if the changes Dockerfiles can be successfully built
branches:
- main
paths:
- "docker/**"
workflow_dispatch:
schedule:
- cron: "0 0 * * *" # every day at midnight
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
group: docker-image-builds
cancel-in-progress: false
env:
REGISTRY: diffusers
CI_SLACK_CHANNEL: ${{ secrets.CI_DOCKER_CHANNEL }}
jobs:
test-build-docker-images:
build-docker-images:
runs-on: ubuntu-latest
if: github.event_name == 'pull_request'
steps:
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v1
- name: Check out code
uses: actions/checkout@v3
- name: Find Changed Dockerfiles
id: file_changes
uses: jitterbit/get-changed-files@v1
with:
format: 'space-delimited'
token: ${{ secrets.GITHUB_TOKEN }}
- name: Build Changed Docker Images
run: |
CHANGED_FILES="${{ steps.file_changes.outputs.all }}"
for FILE in $CHANGED_FILES; do
if [[ "$FILE" == docker/*Dockerfile ]]; then
DOCKER_PATH="${FILE%/Dockerfile}"
DOCKER_TAG=$(basename "$DOCKER_PATH")
echo "Building Docker image for $DOCKER_TAG"
docker build -t "$DOCKER_TAG" "$DOCKER_PATH"
fi
done
if: steps.file_changes.outputs.all != ''
build-and-push-docker-images:
runs-on: ubuntu-latest
if: github.event_name != 'pull_request'
permissions:
contents: read
packages: write
@@ -87,27 +50,3 @@ jobs:
context: ./docker/${{ matrix.image-name }}
push: true
tags: ${{ env.REGISTRY }}/${{ matrix.image-name }}:latest
- name: Post to a Slack channel
id: slack
uses: slackapi/slack-github-action@6c661ce58804a1a20f6dc5fbee7f0381b469e001
with:
# Slack channel id, channel name, or user id to post message.
# See also: https://api.slack.com/methods/chat.postMessage#channels
channel-id: ${{ env.CI_SLACK_CHANNEL }}
# For posting a rich message using Block Kit
payload: |
{
"text": "${{ matrix.image-name }} Docker Image build result: ${{ job.status }}\n${{ github.event.head_commit.url }}",
"blocks": [
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": "${{ matrix.image-name }} Docker Image build result: ${{ job.status }}\n${{ github.event.head_commit.url }}"
}
}
]
}
env:
SLACK_BOT_TOKEN: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}

View File

@@ -7,10 +7,6 @@ on:
- doc-builder*
- v*-release
- v*-patch
paths:
- "src/diffusers/**.py"
- "examples/**"
- "docs/**"
jobs:
build:

View File

@@ -2,10 +2,6 @@ name: Build PR Documentation
on:
pull_request:
paths:
- "src/diffusers/**.py"
- "examples/**"
- "docs/**"
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}

View File

@@ -60,10 +60,9 @@ jobs:
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install -U transformers@git+https://github.com/huggingface/transformers
python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate
python -m pip install -e .[quality,test]
python -m pip install -U git+https://github.com/huggingface/transformers
python -m pip install git+https://github.com/huggingface/accelerate
- name: Environment
run: |
@@ -74,7 +73,6 @@ jobs:
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx" \
--make-reports=tests_${{ matrix.config.report }} \
@@ -85,7 +83,6 @@ jobs:
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 0 \
-s -v -k "Flax" \
--make-reports=tests_${{ matrix.config.report }} \
@@ -96,7 +93,6 @@ jobs:
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
-s -v -k "Onnx" \
--make-reports=tests_${{ matrix.config.report }} \
@@ -136,10 +132,10 @@ jobs:
- name: Install dependencies
shell: arch -arch arm64 bash {0}
run: |
${CONDA_RUN} python -m pip install --upgrade pip uv
${CONDA_RUN} python -m uv pip install -e [quality,test]
${CONDA_RUN} python -m uv pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu
${CONDA_RUN} python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate
${CONDA_RUN} python -m pip install --upgrade pip
${CONDA_RUN} python -m pip install -e .[quality,test]
${CONDA_RUN} python -m pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu
${CONDA_RUN} python -m pip install git+https://github.com/huggingface/accelerate
- name: Environment
shell: arch -arch arm64 bash {0}

View File

@@ -4,8 +4,6 @@ on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
push:
branches:
- main
@@ -25,12 +23,10 @@ jobs:
python-version: "3.8"
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install --upgrade pip uv
python -m uv pip install -e .
python -m uv pip install pytest
python -m pip install --upgrade pip
pip install -e .
pip install pytest
- name: Check for soft dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
pytest tests/others/test_dependencies.py

View File

@@ -4,8 +4,6 @@ on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
push:
branches:
- main
@@ -25,14 +23,12 @@ jobs:
python-version: "3.8"
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install --upgrade pip uv
python -m uv pip install -e .
python -m uv pip install "jax[cpu]>=0.2.16,!=0.3.2"
python -m uv pip install "flax>=0.4.1"
python -m uv pip install "jaxlib>=0.1.65"
python -m uv pip install pytest
python -m pip install --upgrade pip
pip install -e .
pip install "jax[cpu]>=0.2.16,!=0.3.2"
pip install "flax>=0.4.1"
pip install "jaxlib>=0.1.65"
pip install pytest
- name: Check for soft dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
pytest tests/others/test_dependencies.py

49
.github/workflows/pr_quality.yml vendored Normal file
View File

@@ -0,0 +1,49 @@
name: Run code quality checks
on:
pull_request:
branches:
- main
push:
branches:
- main
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
check_code_quality:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
ruff check examples tests src utils scripts
ruff format examples tests src utils scripts --check
check_repository_consistency:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
python utils/check_copies.py
python utils/check_dummies.py
make deps_table_check_updated

View File

@@ -33,8 +33,7 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m pip install -e .[quality,test]
- name: Environment
run: |
python utils/print_env.py
@@ -90,18 +89,15 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install -e [quality,test]
python -m pip install -e .[quality,test]
python -m pip install accelerate
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run all selected tests on CPU
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --dist=loadfile -v --make-reports=${{ matrix.modules }}_tests_cpu ${{ fromJson(needs.setup_pr_tests.outputs.test_map)[matrix.modules] }}
- name: Failure short reports
@@ -148,18 +144,15 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install -e [quality,test]
python -m pip install -e .[quality,test]
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run Hub tests for models, schedulers, and pipelines on a staging env
if: ${{ matrix.config.framework == 'hub_tests_pytorch' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
HUGGINGFACE_CO_STAGING=true python -m pytest \
-m "is_staging_test" \
--make-reports=tests_${{ matrix.config.report }} \

View File

@@ -4,9 +4,6 @@ on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
- "tests/**.py"
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
@@ -19,44 +16,7 @@ env:
PYTEST_TIMEOUT: 60
jobs:
check_code_quality:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
ruff check examples tests src utils scripts
ruff format examples tests src utils scripts --check
check_repository_consistency:
needs: check_code_quality
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
python utils/check_copies.py
python utils/check_dummies.py
make deps_table_check_updated
run_fast_tests:
needs: [check_code_quality, check_repository_consistency]
strategy:
fail-fast: false
matrix:
@@ -84,24 +44,21 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m pip install -e .[quality,test]
if [ "${{ matrix.lib-versions }}" == "main" ]; then
python -m uv pip install -U peft@git+https://github.com/huggingface/peft.git
python -m uv pip install -U transformers@git+https://github.com/huggingface/transformers.git
python -m uv pip install -U accelerate@git+https://github.com/huggingface/accelerate.git
python -m pip install -U git+https://github.com/huggingface/peft.git
python -m pip install -U git+https://github.com/huggingface/transformers.git
python -m pip install -U git+https://github.com/huggingface/accelerate.git
else
python -m uv pip install -U peft transformers accelerate
python -m pip install -U peft transformers accelerate
fi
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run fast PyTorch LoRA CPU tests with PEFT backend
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
-s -v \
--make-reports=tests_${{ matrix.config.report }} \

View File

@@ -4,14 +4,6 @@ on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
- "benchmarks/**.py"
- "examples/**.py"
- "scripts/**.py"
- "tests/**.py"
- ".github/**.yml"
- "utils/**.py"
push:
branches:
- ci-*
@@ -27,44 +19,7 @@ env:
PYTEST_TIMEOUT: 60
jobs:
check_code_quality:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
ruff check examples tests src utils scripts
ruff format examples tests src utils scripts --check
check_repository_consistency:
needs: check_code_quality
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
python utils/check_copies.py
python utils/check_dummies.py
make deps_table_check_updated
run_fast_tests:
needs: [check_code_quality, check_repository_consistency]
strategy:
fail-fast: false
matrix:
@@ -79,6 +34,11 @@ jobs:
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_cpu_models_schedulers
- name: LoRA
framework: lora
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_cpu_lora
- name: Fast Flax CPU tests
framework: flax
runner: docker-cpu
@@ -111,19 +71,16 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install accelerate
python -m pip install -e .[quality,test]
python -m pip install accelerate
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run fast PyTorch Pipeline CPU tests
if: ${{ matrix.config.framework == 'pytorch_pipelines' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx" \
--make-reports=tests_${{ matrix.config.report }} \
@@ -132,16 +89,22 @@ jobs:
- name: Run fast PyTorch Model Scheduler CPU tests
if: ${{ matrix.config.framework == 'pytorch_models' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx and not Dependency" \
--make-reports=tests_${{ matrix.config.report }} \
tests/models tests/schedulers tests/others
- name: Run fast PyTorch LoRA CPU tests
if: ${{ matrix.config.framework == 'lora' }}
run: |
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx and not Dependency" \
--make-reports=tests_${{ matrix.config.report }} \
tests/lora
- name: Run fast Flax TPU tests
if: ${{ matrix.config.framework == 'flax' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "Flax" \
--make-reports=tests_${{ matrix.config.report }} \
@@ -150,8 +113,7 @@ jobs:
- name: Run example PyTorch CPU tests
if: ${{ matrix.config.framework == 'pytorch_examples' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install peft
python -m pip install peft
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
--make-reports=tests_${{ matrix.config.report }} \
examples
@@ -168,7 +130,6 @@ jobs:
path: reports
run_staging_tests:
needs: [check_code_quality, check_repository_consistency]
strategy:
fail-fast: false
matrix:
@@ -200,18 +161,15 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m pip install -e .[quality,test]
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run Hub tests for models, schedulers, and pipelines on a staging env
if: ${{ matrix.config.framework == 'hub_tests_pytorch' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
HUGGINGFACE_CO_STAGING=true python -m pytest \
-m "is_staging_test" \
--make-reports=tests_${{ matrix.config.report }} \

View File

@@ -4,8 +4,6 @@ on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
push:
branches:
- main
@@ -25,12 +23,10 @@ jobs:
python-version: "3.8"
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install --upgrade pip uv
python -m uv pip install -e .
python -m uv pip install torch torchvision torchaudio
python -m uv pip install pytest
python -m pip install --upgrade pip
pip install -e .
pip install torch torchvision torchaudio
pip install pytest
- name: Check for soft dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
pytest tests/others/test_dependencies.py

View File

@@ -4,10 +4,7 @@ on:
push:
branches:
- main
paths:
- "src/diffusers/**.py"
- "examples/**.py"
- "tests/**.py"
env:
DIFFUSERS_IS_CI: yes
@@ -21,7 +18,7 @@ env:
jobs:
setup_torch_cuda_pipeline_matrix:
name: Setup Torch Pipelines CUDA Slow Tests Matrix
runs-on: [single-gpu, nvidia-gpu, t4, ci]
runs-on: docker-gpu
container:
image: diffusers/diffusers-pytorch-cpu # this is a CPU image, but we need it to fetch the matrix
options: --shm-size "16gb" --ipc host
@@ -35,9 +32,8 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
python -m pip install -e .[quality,test]
python -m pip install git+https://github.com/huggingface/accelerate.git
- name: Environment
run: |
@@ -62,9 +58,10 @@ jobs:
needs: setup_torch_cuda_pipeline_matrix
strategy:
fail-fast: false
max-parallel: 1
matrix:
module: ${{ fromJson(needs.setup_torch_cuda_pipeline_matrix.outputs.pipeline_test_matrix) }}
runs-on: [single-gpu, nvidia-gpu, t4, ci]
runs-on: docker-gpu
container:
image: diffusers/diffusers-pytorch-cuda
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/ --gpus 0
@@ -79,9 +76,8 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
python -m pip install -e .[quality,test]
python -m pip install git+https://github.com/huggingface/accelerate.git
- name: Environment
run: |
python utils/print_env.py
@@ -129,9 +125,8 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
python -m pip install -e .[quality,test]
python -m pip install git+https://github.com/huggingface/accelerate.git
- name: Environment
run: |
@@ -179,10 +174,9 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
python -m uv pip install peft@git+https://github.com/huggingface/peft.git
python -m pip install -e .[quality,test]
python -m pip install git+https://github.com/huggingface/accelerate.git
python -m pip install git+https://github.com/huggingface/peft.git
- name: Environment
run: |
@@ -230,9 +224,8 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
python -m pip install -e .[quality,test]
python -m pip install git+https://github.com/huggingface/accelerate.git
- name: Environment
run: |
@@ -278,9 +271,8 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
python -m pip install -e .[quality,test]
python -m pip install git+https://github.com/huggingface/accelerate.git
- name: Environment
run: |
@@ -328,8 +320,7 @@ jobs:
nvidia-smi
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test,training]
python -m pip install -e .[quality,test,training]
- name: Environment
run: |
python utils/print_env.py
@@ -369,8 +360,7 @@ jobs:
nvidia-smi
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test,training]
python -m pip install -e .[quality,test,training]
- name: Environment
run: |
python utils/print_env.py
@@ -411,19 +401,16 @@ jobs:
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test,training]
python -m pip install -e .[quality,test,training]
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run example tests on GPU
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile -s -v --make-reports=examples_torch_cuda examples/
- name: Failure short reports

View File

@@ -4,10 +4,6 @@ on:
push:
branches:
- main
paths:
- "src/diffusers/**.py"
- "examples/**.py"
- "tests/**.py"
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
@@ -69,18 +65,15 @@ jobs:
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m pip install -e .[quality,test]
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run fast PyTorch CPU tests
if: ${{ matrix.config.framework == 'pytorch' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx" \
--make-reports=tests_${{ matrix.config.report }} \
@@ -89,7 +82,6 @@ jobs:
- name: Run fast Flax TPU tests
if: ${{ matrix.config.framework == 'flax' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "Flax" \
--make-reports=tests_${{ matrix.config.report }} \
@@ -98,7 +90,6 @@ jobs:
- name: Run fast ONNXRuntime CPU tests
if: ${{ matrix.config.framework == 'onnxruntime' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "Onnx" \
--make-reports=tests_${{ matrix.config.report }} \
@@ -107,8 +98,7 @@ jobs:
- name: Run example PyTorch CPU tests
if: ${{ matrix.config.framework == 'pytorch_examples' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install peft
python -m pip install peft
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
--make-reports=tests_${{ matrix.config.report }} \
examples

View File

@@ -4,9 +4,6 @@ on:
push:
branches:
- main
paths:
- "src/diffusers/**.py"
- "tests/**.py"
env:
DIFFUSERS_IS_CI: yes
@@ -44,11 +41,11 @@ jobs:
- name: Install dependencies
shell: arch -arch arm64 bash {0}
run: |
${CONDA_RUN} python -m pip install --upgrade pip uv
${CONDA_RUN} python -m uv pip install -e [quality,test]
${CONDA_RUN} python -m uv pip install torch torchvision torchaudio
${CONDA_RUN} python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
${CONDA_RUN} python -m uv pip install transformers --upgrade
${CONDA_RUN} python -m pip install --upgrade pip
${CONDA_RUN} python -m pip install -e .[quality,test]
${CONDA_RUN} python -m pip install torch torchvision torchaudio
${CONDA_RUN} python -m pip install git+https://github.com/huggingface/accelerate.git
${CONDA_RUN} python -m pip install transformers --upgrade
- name: Environment
shell: arch -arch arm64 bash {0}

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -141,7 +141,6 @@ class LCMLoRATextToImageBenchmark(TextToImageBenchmark):
super().__init__(args)
self.pipe.load_lora_weights(self.lora_id)
self.pipe.fuse_lora()
self.pipe.unload_lora_weights()
self.pipe.scheduler = LCMScheduler.from_config(self.pipe.scheduler.config)
def get_result_filepath(self, args):
@@ -236,35 +235,6 @@ class InpaintingBenchmark(ImageToImageBenchmark):
)
class IPAdapterTextToImageBenchmark(TextToImageBenchmark):
url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/load_neg_embed.png"
image = load_image(url)
def __init__(self, args):
pipe = self.pipeline_class.from_pretrained(args.ckpt, torch_dtype=torch.float16).to("cuda")
pipe.load_ip_adapter(
args.ip_adapter_id[0],
subfolder="models" if "sdxl" not in args.ip_adapter_id[1] else "sdxl_models",
weight_name=args.ip_adapter_id[1],
)
if args.run_compile:
pipe.unet.to(memory_format=torch.channels_last)
print("Run torch compile")
pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
pipe.set_progress_bar_config(disable=True)
self.pipe = pipe
def run_inference(self, pipe, args):
_ = pipe(
prompt=PROMPT,
ip_adapter_image=self.image,
num_inference_steps=args.num_inference_steps,
num_images_per_prompt=args.batch_size,
)
class ControlNetBenchmark(TextToImageBenchmark):
pipeline_class = StableDiffusionControlNetPipeline
aux_network_class = ControlNetModel

View File

@@ -1,32 +0,0 @@
import argparse
import sys
sys.path.append(".")
from base_classes import IPAdapterTextToImageBenchmark # noqa: E402
IP_ADAPTER_CKPTS = {
"runwayml/stable-diffusion-v1-5": ("h94/IP-Adapter", "ip-adapter_sd15.bin"),
"stabilityai/stable-diffusion-xl-base-1.0": ("h94/IP-Adapter", "ip-adapter_sdxl.bin"),
}
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--ckpt",
type=str,
default="runwayml/stable-diffusion-v1-5",
choices=list(IP_ADAPTER_CKPTS.keys()),
)
parser.add_argument("--batch_size", type=int, default=1)
parser.add_argument("--num_inference_steps", type=int, default=50)
parser.add_argument("--model_cpu_offload", action="store_true")
parser.add_argument("--run_compile", action="store_true")
args = parser.parse_args()
args.ip_adapter_id = IP_ADAPTER_CKPTS[args.ckpt]
benchmark_pipe = IPAdapterTextToImageBenchmark(args)
args.ckpt = f"{args.ckpt} (IP-Adapter)"
benchmark_pipe.benchmark(args)

View File

@@ -72,7 +72,7 @@ def main():
command += " --run_compile"
run_command(command.split())
elif file in ["benchmark_sd_inpainting.py", "benchmark_ip_adapters.py"]:
elif file == "benchmark_sd_inpainting.py":
sdxl_ckpt = "stabilityai/stable-diffusion-xl-base-1.0"
command = f"python {file} --ckpt {sdxl_ckpt}"
run_command(command.split())

View File

@@ -23,13 +23,13 @@ ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
# follow the instructions here: https://cloud.google.com/tpu/docs/run-in-container#train_a_jax_model_in_a_docker_container
RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
python3 -m uv pip install --upgrade --no-cache-dir \
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --upgrade --no-cache-dir \
clu \
"jax[cpu]>=0.2.16,!=0.3.2" \
"flax>=0.4.1" \
"jaxlib>=0.1.65" && \
python3 -m uv pip install --no-cache-dir \
python3 -m pip install --no-cache-dir \
accelerate \
datasets \
hf-doc-builder \

View File

@@ -23,15 +23,15 @@ ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
# follow the instructions here: https://cloud.google.com/tpu/docs/run-in-container#train_a_jax_model_in_a_docker_container
RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --no-cache-dir \
"jax[tpu]>=0.2.16,!=0.3.2" \
-f https://storage.googleapis.com/jax-releases/libtpu_releases.html && \
python3 -m uv pip install --upgrade --no-cache-dir \
python3 -m pip install --upgrade --no-cache-dir \
clu \
"flax>=0.4.1" \
"jaxlib>=0.1.65" && \
python3 -m uv pip install --no-cache-dir \
python3 -m pip install --no-cache-dir \
accelerate \
datasets \
hf-doc-builder \

View File

@@ -22,14 +22,14 @@ RUN python3 -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
python3 -m uv pip install --no-cache-dir \
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --no-cache-dir \
torch==2.1.2 \
torchvision==0.16.2 \
torchaudio==2.1.2 \
onnxruntime \
--extra-index-url https://download.pytorch.org/whl/cpu && \
python3 -m uv pip install --no-cache-dir \
python3 -m pip install --no-cache-dir \
accelerate \
datasets \
hf-doc-builder \

View File

@@ -1,4 +1,4 @@
FROM nvidia/cuda:12.1.0-runtime-ubuntu20.04
FROM nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04
LABEL maintainer="Hugging Face"
LABEL repository="diffusers"
@@ -22,14 +22,14 @@ RUN python3 -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
python3 -m uv pip install --no-cache-dir \
torch \
torchvision \
torchaudio \
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --no-cache-dir \
torch==2.1.2 \
torchvision==0.16.2 \
torchaudio==2.1.2 \
"onnxruntime-gpu>=1.13.1" \
--extra-index-url https://download.pytorch.org/whl/cu117 && \
python3 -m uv pip install --no-cache-dir \
python3 -m pip install --no-cache-dir \
accelerate \
datasets \
hf-doc-builder \

View File

@@ -24,11 +24,11 @@ RUN python3.9 -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
RUN python3.9 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
python3.9 -m uv pip install --no-cache-dir \
torch \
torchvision \
torchaudio \
RUN python3.9 -m pip install --no-cache-dir --upgrade pip && \
python3.9 -m pip install --no-cache-dir \
torch==2.1.2 \
torchvision==0.16.2 \
torchaudio==2.1.2 \
invisible_watermark && \
python3.9 -m pip install --no-cache-dir \
accelerate \

View File

@@ -23,14 +23,14 @@ RUN python3 -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
python3 -m uv pip install --no-cache-dir \
torch \
torchvision \
torchaudio \
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --no-cache-dir \
torch==2.1.2 \
torchvision==0.16.2 \
torchaudio==2.1.2 \
invisible_watermark \
--extra-index-url https://download.pytorch.org/whl/cpu && \
python3 -m uv pip install --no-cache-dir \
python3 -m pip install --no-cache-dir \
accelerate \
datasets \
hf-doc-builder \
@@ -40,6 +40,6 @@ RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
numpy \
scipy \
tensorboard \
transformers matplotlib
transformers
CMD ["/bin/bash"]

View File

@@ -23,11 +23,11 @@ RUN python3 -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
python3 -m uv pip install --no-cache-dir \
torch \
torchvision \
torchaudio \
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --no-cache-dir \
torch==2.1.2 \
torchvision==0.16.2 \
torchaudio==2.1.2 \
invisible_watermark && \
python3 -m pip install --no-cache-dir \
accelerate \

View File

@@ -23,13 +23,13 @@ RUN python3 -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --no-cache-dir \
torch \
torchvision \
torchaudio \
torch==2.1.2 \
torchvision==0.16.2 \
torchaudio==2.1.2 \
invisible_watermark && \
python3 -m uv pip install --no-cache-dir \
python3 -m pip install --no-cache-dir \
accelerate \
datasets \
hf-doc-builder \

View File

@@ -1,5 +1,5 @@
<!---
Copyright 2024- The HuggingFace Team. All rights reserved.
Copyright 2023- The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -18,7 +18,7 @@
- local: tutorials/basic_training
title: Train a diffusion model
- local: tutorials/using_peft_for_inference
title: Load LoRAs for inference
title: Inference with PEFT
- local: tutorials/fast_diffusion
title: Accelerate inference of text-to-image diffusion models
title: Tutorials
@@ -52,18 +52,12 @@
title: Image-to-image
- local: using-diffusers/inpaint
title: Inpainting
- local: using-diffusers/text-img2vid
title: Text or image-to-video
- local: using-diffusers/depth2img
title: Depth-to-image
title: Tasks
- sections:
- local: using-diffusers/textual_inversion_inference
title: Textual inversion
- local: using-diffusers/ip_adapter
title: IP-Adapter
- local: using-diffusers/merge_loras
title: Merge LoRAs
- local: training/distributed_inference
title: Distributed inference with multiple GPUs
- local: using-diffusers/reusing_seeds
@@ -320,8 +314,6 @@
title: Semantic Guidance
- local: api/pipelines/shap_e
title: Shap-E
- local: api/pipelines/stable_cascade
title: Stable Cascade
- sections:
- local: api/pipelines/stable_diffusion/overview
title: Overview
@@ -329,8 +321,6 @@
title: Text-to-image
- local: api/pipelines/stable_diffusion/img2img
title: Image-to-image
- local: api/pipelines/stable_diffusion/svd
title: Image-to-video
- local: api/pipelines/stable_diffusion/inpaint
title: Inpainting
- local: api/pipelines/stable_diffusion/depth2img
@@ -422,8 +412,6 @@
title: ScoreSdeVeScheduler
- local: api/schedulers/score_sde_vp
title: ScoreSdeVpScheduler
- local: api/schedulers/tcd
title: TCDScheduler
- local: api/schedulers/unipc
title: UniPCMultistepScheduler
- local: api/schedulers/vq_diffusion

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
@@ -20,14 +20,14 @@ An attention processor is a class for applying different types of attention mech
## AttnProcessor2_0
[[autodoc]] models.attention_processor.AttnProcessor2_0
## AttnAddedKVProcessor
[[autodoc]] models.attention_processor.AttnAddedKVProcessor
## FusedAttnProcessor2_0
[[autodoc]] models.attention_processor.FusedAttnProcessor2_0
## AttnAddedKVProcessor2_0
[[autodoc]] models.attention_processor.AttnAddedKVProcessor2_0
## LoRAAttnProcessor
[[autodoc]] models.attention_processor.LoRAAttnProcessor
## CrossFrameAttnProcessor
[[autodoc]] pipelines.text_to_video_synthesis.pipeline_text_to_video_zero.CrossFrameAttnProcessor
## LoRAAttnProcessor2_0
[[autodoc]] models.attention_processor.LoRAAttnProcessor2_0
## CustomDiffusionAttnProcessor
[[autodoc]] models.attention_processor.CustomDiffusionAttnProcessor
@@ -35,23 +35,26 @@ An attention processor is a class for applying different types of attention mech
## CustomDiffusionAttnProcessor2_0
[[autodoc]] models.attention_processor.CustomDiffusionAttnProcessor2_0
## CustomDiffusionXFormersAttnProcessor
[[autodoc]] models.attention_processor.CustomDiffusionXFormersAttnProcessor
## AttnAddedKVProcessor
[[autodoc]] models.attention_processor.AttnAddedKVProcessor
## FusedAttnProcessor2_0
[[autodoc]] models.attention_processor.FusedAttnProcessor2_0
## AttnAddedKVProcessor2_0
[[autodoc]] models.attention_processor.AttnAddedKVProcessor2_0
## LoRAAttnAddedKVProcessor
[[autodoc]] models.attention_processor.LoRAAttnAddedKVProcessor
## XFormersAttnProcessor
[[autodoc]] models.attention_processor.XFormersAttnProcessor
## LoRAXFormersAttnProcessor
[[autodoc]] models.attention_processor.LoRAXFormersAttnProcessor
## CustomDiffusionXFormersAttnProcessor
[[autodoc]] models.attention_processor.CustomDiffusionXFormersAttnProcessor
## SlicedAttnProcessor
[[autodoc]] models.attention_processor.SlicedAttnProcessor
## SlicedAttnAddedKVProcessor
[[autodoc]] models.attention_processor.SlicedAttnAddedKVProcessor
## XFormersAttnProcessor
[[autodoc]] models.attention_processor.XFormersAttnProcessor

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
@@ -12,18 +12,14 @@ specific language governing permissions and limitations under the License.
# IP-Adapter
[IP-Adapter](https://hf.co/papers/2308.06721) is a lightweight adapter that enables prompting a diffusion model with an image. This method decouples the cross-attention layers of the image and text features. The image features are generated from an image encoder.
[IP-Adapter](https://hf.co/papers/2308.06721) is a lightweight adapter that enables prompting a diffusion model with an image. This method decouples the cross-attention layers of the image and text features. The image features are generated from an image encoder. Files generated from IP-Adapter are only ~100MBs.
<Tip>
Learn how to load an IP-Adapter checkpoint and image in the IP-Adapter [loading](../../using-diffusers/loading_adapters#ip-adapter) guide, and you can see how to use it in the [usage](../../using-diffusers/ip_adapter) guide.
Learn how to load an IP-Adapter checkpoint and image in the [IP-Adapter](../../using-diffusers/loading_adapters#ip-adapter) loading guide.
</Tip>
## IPAdapterMixin
[[autodoc]] loaders.ip_adapter.IPAdapterMixin
## IPAdapterMaskProcessor
[[autodoc]] image_processor.IPAdapterMaskProcessor

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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,18 +1,6 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->
# Consistency Decoder
Consistency decoder can be used to decode the latents from the denoising UNet in the [`StableDiffusionPipeline`]. This decoder was introduced in the [DALL-E 3 technical report](https://openai.com/dall-e-3).
Consistency decoder can be used to decode the latents from the denoising UNet in the [`StableDiffusionPipeline`]. This decoder was introduced in the [DALL-E 3 technical report](https://openai.com/dall-e-3).
The original codebase can be found at [openai/consistencydecoder](https://github.com/openai/consistencydecoder).

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
@@ -408,91 +408,6 @@ Make sure to check out the Schedulers [guide](../../using-diffusers/schedulers)
</Tip>
## Using AnimateLCM
[AnimateLCM](https://animatelcm.github.io/) is a motion module checkpoint and an [LCM LoRA](https://huggingface.co/docs/diffusers/using-diffusers/inference_with_lcm_lora) that have been created using a consistency learning strategy that decouples the distillation of the image generation priors and the motion generation priors.
```python
import torch
from diffusers import AnimateDiffPipeline, LCMScheduler, MotionAdapter
from diffusers.utils import export_to_gif
adapter = MotionAdapter.from_pretrained("wangfuyun/AnimateLCM")
pipe = AnimateDiffPipeline.from_pretrained("emilianJR/epiCRealism", motion_adapter=adapter)
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config, beta_schedule="linear")
pipe.load_lora_weights("wangfuyun/AnimateLCM", weight_name="sd15_lora_beta.safetensors", adapter_name="lcm-lora")
pipe.enable_vae_slicing()
pipe.enable_model_cpu_offload()
output = pipe(
prompt="A space rocket with trails of smoke behind it launching into space from the desert, 4k, high resolution",
negative_prompt="bad quality, worse quality, low resolution",
num_frames=16,
guidance_scale=1.5,
num_inference_steps=6,
generator=torch.Generator("cpu").manual_seed(0),
)
frames = output.frames[0]
export_to_gif(frames, "animatelcm.gif")
```
<table>
<tr>
<td><center>
A space rocket, 4K.
<br>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatelcm-output.gif"
alt="A space rocket, 4K"
style="width: 300px;" />
</center></td>
</tr>
</table>
AnimateLCM is also compatible with existing [Motion LoRAs](https://huggingface.co/collections/dn6/animatediff-motion-loras-654cb8ad732b9e3cf4d3c17e).
```python
import torch
from diffusers import AnimateDiffPipeline, LCMScheduler, MotionAdapter
from diffusers.utils import export_to_gif
adapter = MotionAdapter.from_pretrained("wangfuyun/AnimateLCM")
pipe = AnimateDiffPipeline.from_pretrained("emilianJR/epiCRealism", motion_adapter=adapter)
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config, beta_schedule="linear")
pipe.load_lora_weights("wangfuyun/AnimateLCM", weight_name="sd15_lora_beta.safetensors", adapter_name="lcm-lora")
pipe.load_lora_weights("guoyww/animatediff-motion-lora-tilt-up", adapter_name="tilt-up")
pipe.set_adapters(["lcm-lora", "tilt-up"], [1.0, 0.8])
pipe.enable_vae_slicing()
pipe.enable_model_cpu_offload()
output = pipe(
prompt="A space rocket with trails of smoke behind it launching into space from the desert, 4k, high resolution",
negative_prompt="bad quality, worse quality, low resolution",
num_frames=16,
guidance_scale=1.5,
num_inference_steps=6,
generator=torch.Generator("cpu").manual_seed(0),
)
frames = output.frames[0]
export_to_gif(frames, "animatelcm-motion-lora.gif")
```
<table>
<tr>
<td><center>
A space rocket, 4K.
<br>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatelcm-motion-lora.gif"
alt="A space rocket, 4K"
style="width: 300px;" />
</center></td>
</tr>
</table>
## AnimateDiffPipeline
[[autodoc]] AnimateDiffPipeline

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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

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@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0

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@@ -1,229 +0,0 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->
# Stable Cascade
This model is built upon the [Würstchen](https://openreview.net/forum?id=gU58d5QeGv) architecture and its main
difference to other models like Stable Diffusion is that it is working at a much smaller latent space. Why is this
important? The smaller the latent space, the **faster** you can run inference and the **cheaper** the training becomes.
How small is the latent space? Stable Diffusion uses a compression factor of 8, resulting in a 1024x1024 image being
encoded to 128x128. Stable Cascade achieves a compression factor of 42, meaning that it is possible to encode a
1024x1024 image to 24x24, while maintaining crisp reconstructions. The text-conditional model is then trained in the
highly compressed latent space. Previous versions of this architecture, achieved a 16x cost reduction over Stable
Diffusion 1.5.
Therefore, this kind of model is well suited for usages where efficiency is important. Furthermore, all known extensions
like finetuning, LoRA, ControlNet, IP-Adapter, LCM etc. are possible with this method as well.
The original codebase can be found at [Stability-AI/StableCascade](https://github.com/Stability-AI/StableCascade).
## Model Overview
Stable Cascade consists of three models: Stage A, Stage B and Stage C, representing a cascade to generate images,
hence the name "Stable Cascade".
Stage A & B are used to compress images, similar to what the job of the VAE is in Stable Diffusion.
However, with this setup, a much higher compression of images can be achieved. While the Stable Diffusion models use a
spatial compression factor of 8, encoding an image with resolution of 1024 x 1024 to 128 x 128, Stable Cascade achieves
a compression factor of 42. This encodes a 1024 x 1024 image to 24 x 24, while being able to accurately decode the
image. This comes with the great benefit of cheaper training and inference. Furthermore, Stage C is responsible
for generating the small 24 x 24 latents given a text prompt.
The Stage C model operates on the small 24 x 24 latents and denoises the latents conditioned on text prompts. The model is also the largest component in the Cascade pipeline and is meant to be used with the `StableCascadePriorPipeline`
The Stage B and Stage A models are used with the `StableCascadeDecoderPipeline` and are responsible for generating the final image given the small 24 x 24 latents.
<Tip warning={true}>
There are some restrictions on data types that can be used with the Stable Cascade models. The official checkpoints for the `StableCascadePriorPipeline` do not support the `torch.float16` data type. Please use `torch.bfloat16` instead.
In order to use the `torch.bfloat16` data type with the `StableCascadeDecoderPipeline` you need to have PyTorch 2.2.0 or higher installed. This also means that using the `StableCascadeCombinedPipeline` with `torch.bfloat16` requires PyTorch 2.2.0 or higher, since it calls the `StableCascadeDecoderPipeline` internally.
If it is not possible to install PyTorch 2.2.0 or higher in your environment, the `StableCascadeDecoderPipeline` can be used on its own with the `torch.float16` data type. You can download the full precision or `bf16` variant weights for the pipeline and cast the weights to `torch.float16`.
</Tip>
## Usage example
```python
import torch
from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
prompt = "an image of a shiba inu, donning a spacesuit and helmet"
negative_prompt = ""
prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", variant="bf16", torch_dtype=torch.bfloat16)
decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", variant="bf16", torch_dtype=torch.float16)
prior.enable_model_cpu_offload()
prior_output = prior(
prompt=prompt,
height=1024,
width=1024,
negative_prompt=negative_prompt,
guidance_scale=4.0,
num_images_per_prompt=1,
num_inference_steps=20
)
decoder.enable_model_cpu_offload()
decoder_output = decoder(
image_embeddings=prior_output.image_embeddings.to(torch.float16),
prompt=prompt,
negative_prompt=negative_prompt,
guidance_scale=0.0,
output_type="pil",
num_inference_steps=10
).images[0]
decoder_output.save("cascade.png")
```
## Using the Lite Versions of the Stage B and Stage C models
```python
import torch
from diffusers import (
StableCascadeDecoderPipeline,
StableCascadePriorPipeline,
StableCascadeUNet,
)
prompt = "an image of a shiba inu, donning a spacesuit and helmet"
negative_prompt = ""
prior_unet = StableCascadeUNet.from_pretrained("stabilityai/stable-cascade-prior", subfolder="prior_lite")
decoder_unet = StableCascadeUNet.from_pretrained("stabilityai/stable-cascade", subfolder="decoder_lite")
prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", prior=prior_unet)
decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", decoder=decoder_unet)
prior.enable_model_cpu_offload()
prior_output = prior(
prompt=prompt,
height=1024,
width=1024,
negative_prompt=negative_prompt,
guidance_scale=4.0,
num_images_per_prompt=1,
num_inference_steps=20
)
decoder.enable_model_cpu_offload()
decoder_output = decoder(
image_embeddings=prior_output.image_embeddings,
prompt=prompt,
negative_prompt=negative_prompt,
guidance_scale=0.0,
output_type="pil",
num_inference_steps=10
).images[0]
decoder_output.save("cascade.png")
```
## Loading original checkpoints with `from_single_file`
Loading the original format checkpoints is supported via `from_single_file` method in the StableCascadeUNet.
```python
import torch
from diffusers import (
StableCascadeDecoderPipeline,
StableCascadePriorPipeline,
StableCascadeUNet,
)
prompt = "an image of a shiba inu, donning a spacesuit and helmet"
negative_prompt = ""
prior_unet = StableCascadeUNet.from_single_file(
"https://huggingface.co/stabilityai/stable-cascade/resolve/main/stage_c_bf16.safetensors",
torch_dtype=torch.bfloat16
)
decoder_unet = StableCascadeUNet.from_single_file(
"https://huggingface.co/stabilityai/stable-cascade/blob/main/stage_b_bf16.safetensors",
torch_dtype=torch.bfloat16
)
prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", prior=prior_unet, torch_dtype=torch.bfloat16)
decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", decoder=decoder_unet, torch_dtype=torch.bfloat16)
prior.enable_model_cpu_offload()
prior_output = prior(
prompt=prompt,
height=1024,
width=1024,
negative_prompt=negative_prompt,
guidance_scale=4.0,
num_images_per_prompt=1,
num_inference_steps=20
)
decoder.enable_model_cpu_offload()
decoder_output = decoder(
image_embeddings=prior_output.image_embeddings,
prompt=prompt,
negative_prompt=negative_prompt,
guidance_scale=0.0,
output_type="pil",
num_inference_steps=10
).images[0]
decoder_output.save("cascade-single-file.png")
```
## Uses
### Direct Use
The model is intended for research purposes for now. Possible research areas and tasks include
- Research on generative models.
- Safe deployment of models which have the potential to generate harmful content.
- Probing and understanding the limitations and biases of generative models.
- Generation of artworks and use in design and other artistic processes.
- Applications in educational or creative tools.
Excluded uses are described below.
### Out-of-Scope Use
The model was not trained to be factual or true representations of people or events,
and therefore using the model to generate such content is out-of-scope for the abilities of this model.
The model should not be used in any way that violates Stability AI's [Acceptable Use Policy](https://stability.ai/use-policy).
## Limitations and Bias
### Limitations
- Faces and people in general may not be generated properly.
- The autoencoding part of the model is lossy.
## StableCascadeCombinedPipeline
[[autodoc]] StableCascadeCombinedPipeline
- all
- __call__
## StableCascadePriorPipeline
[[autodoc]] StableCascadePriorPipeline
- all
- __call__
## StableCascadePriorPipelineOutput
[[autodoc]] pipelines.stable_cascade.pipeline_stable_cascade_prior.StableCascadePriorPipelineOutput
## StableCascadeDecoderPipeline
[[autodoc]] StableCascadeDecoderPipeline
- all
- __call__

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