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.github/CONTRIBUTING.md

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Welcome to the PyTorch Lightning community! We're building the most advanced research platform on the planet to implement the latest, best practices
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and integrations that the amazing PyTorch team and other research organization rolls out!
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If you are new to open source, check out [this blog to get started with your first Open Source contribution](https://devblog.pytorchlightning.ai/quick-contribution-guide-86d977171b3a).
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If you are new to open source, check out [this blog to get started with your first Open Source contribution](https://medium.com/pytorch-lightning/quick-contribution-guide-86d977171b3a).
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## Main Core Value: One less thing to remember
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To set up a local development environment, we recommend using `uv`, which can be installed following their [instructions](https://docs.astral.sh/uv/getting-started/installation/).
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Once `uv` has been installed, begin by cloning the repository:
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Once `uv` has been installed, begin by cloning the forked repository:
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```bash
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git clone https://github.com/Lightning-AI/lightning.git
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cd lightning
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git clone https://github.com/{YOUR_GITHUB_USERNAME}/pytorch-lightning.git
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cd pytorch-lightning
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```
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Once in root level of the repository, create a new virtual environment and install the project dependencies.
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> If you're using [Lightning Studio](https://lightning.ai) or already have your `uv venv` activated, you can quickly set up the project by running:
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```bash
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make setup
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```
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This will:
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- Install all required dependencies.
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- Perform an editable install of the `pytorch-lightning` project.
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- Install and configure `pre-commit`.
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#### Manual Setup (Optional)
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If you prefer more fine-grained control over the dependencies, you can set up the environment manually:
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```bash
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uv venv

.github/checkgroup.yml

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- "build-pl (3.11, 2.4, 12.1.1)"
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- "build-pl (3.12, 2.5, 12.1.1)"
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- "build-pl (3.12, 2.6, 12.4.1)"
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- "build-pl (3.12, 2.7, 12.6.3, true)"
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- "build-pl (3.12, 2.7, 12.6.3)"
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- "build-pl (3.12, 2.8, 12.6.3, true)"
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# SECTION: lightning_fabric
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.github/workflows/call-clear-cache.yml

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jobs:
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cron-clear:
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if: github.event_name == 'schedule' || github.event_name == 'pull_request'
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uses: Lightning-AI/utilities/.github/workflows/cleanup-caches.yml@v0.14.3
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uses: Lightning-AI/utilities/.github/workflows/cleanup-caches.yml@v0.15.0
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with:
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scripts-ref: v0.14.3
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dry-run: ${{ github.event_name == 'pull_request' }}
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direct-clear:
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if: github.event_name == 'workflow_dispatch' || github.event_name == 'pull_request'
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uses: Lightning-AI/utilities/.github/workflows/cleanup-caches.yml@v0.14.3
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uses: Lightning-AI/utilities/.github/workflows/cleanup-caches.yml@v0.15.0
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with:
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scripts-ref: v0.14.3
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dry-run: ${{ github.event_name == 'pull_request' }}

.github/workflows/ci-schema.yml

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jobs:
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check:
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uses: Lightning-AI/utilities/.github/workflows/check-schema.yml@v0.14.3
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uses: Lightning-AI/utilities/.github/workflows/check-schema.yml@v0.15.0
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with:
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# skip azure due to the wrong schema file by MSFT
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# https://github.com/Lightning-AI/lightning-flash/pull/1455#issuecomment-1244793607

.github/workflows/docker-build.yml

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- { python_version: "3.11", pytorch_version: "2.4", cuda_version: "12.1.1" }
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- { python_version: "3.12", pytorch_version: "2.5", cuda_version: "12.1.1" }
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- { python_version: "3.12", pytorch_version: "2.6", cuda_version: "12.4.1" }
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- { python_version: "3.12", pytorch_version: "2.7", cuda_version: "12.6.3", latest: "true" }
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- { python_version: "3.12", pytorch_version: "2.7", cuda_version: "12.6.3" }
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- { python_version: "3.12", pytorch_version: "2.8", cuda_version: "12.6.3", latest: "true" }
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steps:
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- uses: actions/checkout@v4
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with:
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# adding dome more images as Thunder mainly using python 3.10,
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# and we need to support integrations as for example LitGPT
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python_version: ["3.10"]
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pytorch_version: ["2.6.0", "2.7.1"]
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pytorch_version: ["2.7.1", "2.8.0"]
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cuda_version: ["12.6.3"]
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include:
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# These are the base images for PL release docker images.
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- { python_version: "3.12", pytorch_version: "2.5.1", cuda_version: "12.1.1" }
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- { python_version: "3.12", pytorch_version: "2.6.0", cuda_version: "12.4.1" }
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- { python_version: "3.12", pytorch_version: "2.7.1", cuda_version: "12.6.3" }
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- { python_version: "3.12", pytorch_version: "2.8.0", cuda_version: "12.6.3" }
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steps:
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- uses: docker/setup-buildx-action@v3
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PYTHON_VERSION=${{ matrix.python_version }}
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CUDA_VERSION=${{ matrix.cuda_version }}
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MAKE_FLAGS="-j2"
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file: dockers/base-cuda/Dockerfile
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push: ${{ env.PUSH_NIGHTLY }}
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tags: "pytorchlightning/pytorch_lightning:base-cuda-py${{ matrix.python_version }}-torch${{ env.PT_VERSION }}-cuda${{ matrix.cuda_version }}"
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uses: docker/build-push-action@v6
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build-args: |
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PYTORCH_VERSION="25.04"
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file: dockers/nvidia/Dockerfile
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push: false
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timeout-minutes: 55

Makefile

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.PHONY: test clean docs
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.PHONY: test clean docs setup
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# to imitate SLURM set only single node
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export SLURM_LOCALID=0
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# install only Lightning Trainer packages
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export PACKAGE_NAME=pytorch
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setup:
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uv pip install -r requirements.txt \
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-r requirements/pytorch/base.txt \
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-r requirements/pytorch/test.txt \
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-r requirements/pytorch/extra.txt \
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-r requirements/pytorch/strategies.txt \
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-r requirements/fabric/base.txt \
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-r requirements/fabric/test.txt \
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-r requirements/fabric/strategies.txt \
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-r requirements/typing.txt \
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-e ".[all]" \
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pre-commit
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pre-commit install
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@echo "-----------------------------"
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@echo "✅ Environment setup complete. Ready to Contribute ⚡️!"
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clean:
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# clean all temp runs
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rm -rf $(shell find . -name "mlruns")

dockers/base-cuda/Dockerfile

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FROM nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
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ARG PYTORCH_VERSION=2.1
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ARG PYTORCH_VERSION=2.8
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ARG MAX_ALLOWED_NCCL=2.22.3
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ARG MAKE_FLAGS="-j$(nproc)"
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SHELL ["/bin/bash", "-c"]
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CUDA_TOOLKIT_ROOT_DIR="/usr/local/cuda" \
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# MAKEFLAGS="-j$(nproc)"
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MAKEFLAGS="-j2"
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MAKEFLAGS=${MAKE_FLAGS}
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RUN \
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CUDA_VERSION_MM=${CUDA_VERSION%.*} && \

dockers/nvidia/Dockerfile

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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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ARG PYTORCH_VERSION=22.09
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ARG PYTORCH_VERSION=24.05
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# https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes
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FROM nvcr.io/nvidia/pytorch:${PYTORCH_VERSION}-py3

dockers/release/Dockerfile

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# limitations under the License.
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ARG PYTORCH_VERSION=2.0
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ARG CUDA_VERSION=11.8.0
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ARG PYTORCH_VERSION=2.8
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ARG CUDA_VERSION=12.6.3
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FROM pytorchlightning/pytorch_lightning:base-cuda-py${PYTHON_VERSION}-torch${PYTORCH_VERSION}-cuda${CUDA_VERSION}
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docs/source-fabric/advanced/model_parallel/tp_fsdp.rst

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.. raw:: html
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<a target="_blank" href="https://lightning.ai/lightning-ai/studios/tensor-parallelism-supercharging-large-model-training-with-lightning-fabric">
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<a target="_blank" href="https://lightning.ai/lightning-ai/studios/pretrain-an-llm-with-pytorch-lightning">
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<img src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/studio-badge.svg" alt="Open In Studio" style="width: auto; max-width: none;"/>
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</a>
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