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.github/workflows/benchmark.yml

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name: Benchmarking tests
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on:
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workflow_dispatch:
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schedule:
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- cron: "30 1 1,15 * *" # every 2 weeks on the 1st and the 15th of every month at 1:30 AM
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.github/workflows/build_docker_images.yml

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# For posting a rich message using Block Kit
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payload: |
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{
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"text": "${{ matrix.image-name }} Docker Image build result: ${{ job.status }}\n${{ github.event.pull_request.html_url || github.event.head_commit.url }}",
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"text": "${{ matrix.image-name }} Docker Image build result: ${{ job.status }}\n${{ github.event.head_commit.url }}",
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"blocks": [
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{
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"type": "section",
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"text": {
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"type": "mrkdwn",
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"text": "${{ matrix.image-name }} Docker Image build result: ${{ job.status }}\n${{ github.event.pull_request.html_url || github.event.head_commit.url }}"
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"text": "${{ matrix.image-name }} Docker Image build result: ${{ job.status }}\n${{ github.event.head_commit.url }}"
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}
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}
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]

.github/workflows/build_documentation.yml

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- v*-patch
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paths:
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- "src/diffusers/**.py"
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- "examples/"
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- "docs/"
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- "examples/**"
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- "docs/**"
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jobs:
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build:

.github/workflows/build_pr_documentation.yml

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pull_request:
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paths:
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- "src/diffusers/**.py"
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- "examples/"
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- "docs/"
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- "examples/**"
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- "docs/**"
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concurrency:
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group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}

.github/workflows/push_tests.yml

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jobs:
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setup_torch_cuda_pipeline_matrix:
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name: Setup Torch Pipelines CUDA Slow Tests Matrix
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runs-on: docker-gpu
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runs-on: [single-gpu, nvidia-gpu, t4, ci]
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container:
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image: diffusers/diffusers-pytorch-cpu # this is a CPU image, but we need it to fetch the matrix
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options: --shm-size "16gb" --ipc host
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needs: setup_torch_cuda_pipeline_matrix
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strategy:
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fail-fast: false
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max-parallel: 1
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matrix:
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module: ${{ fromJson(needs.setup_torch_cuda_pipeline_matrix.outputs.pipeline_test_matrix) }}
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runs-on: [single-gpu, nvidia-gpu, t4, ci]

benchmarks/base_classes.py

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super().__init__(args)
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self.pipe.load_lora_weights(self.lora_id)
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self.pipe.fuse_lora()
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self.pipe.unload_lora_weights()
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self.pipe.scheduler = LCMScheduler.from_config(self.pipe.scheduler.config)
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def get_result_filepath(self, args):

docker/diffusers-flax-cpu/Dockerfile

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# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
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# follow the instructions here: https://cloud.google.com/tpu/docs/run-in-container#train_a_jax_model_in_a_docker_container
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RUN python3 -m pip install --no-cache-dir --upgrade pip uv && \
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RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
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python3 -m uv pip install --upgrade --no-cache-dir \
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clu \
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"jax[cpu]>=0.2.16,!=0.3.2" \

docker/diffusers-flax-tpu/Dockerfile

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# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
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# follow the instructions here: https://cloud.google.com/tpu/docs/run-in-container#train_a_jax_model_in_a_docker_container
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RUN python3 -m pip install --no-cache-dir --upgrade pip uv && \
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RUN python3 -m pip install --no-cache-dir --upgrade pip uv==0.1.11 && \
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python3 -m pip install --no-cache-dir \
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"jax[tpu]>=0.2.16,!=0.3.2" \
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-f https://storage.googleapis.com/jax-releases/libtpu_releases.html && \

docker/diffusers-onnxruntime-cpu/Dockerfile

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

docker/diffusers-onnxruntime-cuda/Dockerfile

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

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