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Merge branch 'master' into dependabot-pip-requirements-onnxscript-gte-0.1.0-and-lt-0.6.0
2 parents 7ea536c + 3bdf8ee commit 0c5881c

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‎.github/checkgroup.yml‎

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@@ -47,7 +47,7 @@ subprojects:
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- "!*.md"
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- "!**/*.md"
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checks:
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- "pytorch.yml / Lit Job (nvidia/cuda:12.1.1-runtime-ubuntu22.04, pytorch, 3.10, A100_X_2)"
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- "pytorch.yml / Lit Job (nvidia/cuda:12.1.1-runtime-ubuntu22.04, pytorch, 3.10, L4_X_2)"
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- "pytorch.yml / Lit Job (nvidia/cuda:12.6.3-runtime-ubuntu22.04, lightning, 3.12, L4_X_2)"
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- "pytorch.yml / Lit Job (nvidia/cuda:12.6.3-runtime-ubuntu22.04, pytorch, 3.12, L4_X_2)"
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@@ -148,7 +148,7 @@ subprojects:
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- "!*.md"
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- "!**/*.md"
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checks:
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- "fabric.yml / Lit Job (nvidia/cuda:12.1.1-runtime-ubuntu22.04, fabric, 3.10, A100_X_2)"
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- "fabric.yml / Lit Job (nvidia/cuda:12.1.1-runtime-ubuntu22.04, fabric, 3.10, L4_X_2)"
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- "fabric.yml / Lit Job (nvidia/cuda:12.6.3-runtime-ubuntu22.04, fabric, 3.12, L4_X_2)"
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- "fabric.yml / Lit Job (nvidia/cuda:12.6.3-runtime-ubuntu22.04, lightning, 3.12, L4_X_2)"
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‎.lightning/workflows/benchmark.yml‎

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@@ -22,12 +22,13 @@ env:
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RUN_ONLY_CUDA_TESTS: "1"
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run: |
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# Install Python and UV
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apt-get update -qq --fix-missing
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echo "Installing dependencies"
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apt-get update -qq --fix-missing -o=Dpkg::Use-Pty=0 &> /dev/null
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apt-get install -q -y software-properties-common curl
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# Add deadsnakes PPA for newer Python versions if needed
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echo "Add deadsnakes PPA for newer Python versions if needed"
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add-apt-repository ppa:deadsnakes/ppa -y
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apt-get update -qq --fix-missing
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apt-get update -qq --fix-missing -o=Dpkg::Use-Pty=0 &> /dev/null
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echo "Install Python ${python_version} and other dependencies"
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apt-get install -q -y --no-install-recommends --allow-downgrades --allow-change-held-packages \
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build-essential \
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pkg-config \
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libopenmpi-dev \
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openmpi-bin
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echo "Install Python ${python_version} and UV"
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apt-get install -y python${python_version} python${python_version}-venv python${python_version}-dev
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ln -sf /usr/bin/python${python_version} /usr/bin/python
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curl -LsSf https://astral.sh/uv/install.sh | sh
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# Source the environment and ensure UV is in PATH
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echo "Source the environment and ensure UV is in PATH"
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[ -f "$HOME/.local/bin/env" ] && . "$HOME/.local/bin/env"
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export PATH="$HOME/.local/bin:$PATH"
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source $HOME/.cargo/env 2>/dev/null || true
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export PATH="$HOME/.cargo/bin:$PATH"
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# Verify UV installation
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echo "Verify UV installation"
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command -v uv || (echo "UV not found in PATH" && exit 1)
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# Create and activate a local uv virtual environment
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uv venv .venv -p "/usr/bin/python${python_version}" || uv venv .venv -p "python${python_version}" || uv venv .venv
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. .venv/bin/activate
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hash -r
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echo "Show system information"
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whereis nvidia
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nvidia-smi
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python --version
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CUDA_VERSION_MM="${CUDA_VERSION_M_M//./}" # "126"
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export UV_TORCH_BACKEND=cu${CUDA_VERSION_MM}
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# Adjust tests
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echo "Adjust tests"
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uv pip install -q -r .actions/requirements.txt
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python .actions/assistant.py copy_replace_imports --source_dir="./tests" \
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--source_import="lightning.fabric,lightning.pytorch" \
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--target_import="lightning_fabric,pytorch_lightning"
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# Install package
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echo "Install package"
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uv pip install ".[dev]"
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# Env details
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python requirements/collect_env_details.py
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python -c "import torch ; mgpu = torch.cuda.device_count() ; assert mgpu >= 2, f'GPU: {mgpu}'"
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cd tests/
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# Testing: benchmarks
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echo "Testing: benchmarks"
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export PL_RUNNING_BENCHMARKS=1
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python -m pytest parity_${PACKAGE_NAME} -v --durations=0
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export PL_RUNNING_BENCHMARKS=0
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# Testing: fabric standalone tasks
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echo "Testing: fabric standalone tasks"
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export PL_RUN_STANDALONE_TESTS=1
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if [ "${PACKAGE_NAME}" == "fabric" ]; then
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cd parity_fabric/

‎.lightning/workflows/fabric.yml‎

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@@ -12,7 +12,7 @@ parametrize:
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- image: "nvidia/cuda:12.1.1-runtime-ubuntu22.04"
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PACKAGE_NAME: "fabric"
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python_version: "3.10"
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machine: "A100_X_2"
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machine: "L4_X_2"
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- image: "nvidia/cuda:12.6.3-runtime-ubuntu22.04"
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PACKAGE_NAME: "fabric"
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python_version: "3.12"
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RUN_ONLY_CUDA_TESTS: "1"
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run: |
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# Install Python and UV
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apt-get update -qq --fix-missing
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echo "Installing dependencies"
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apt-get update -qq --fix-missing -o=Dpkg::Use-Pty=0 &> /dev/null
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apt-get install -q -y software-properties-common curl
43-
# Add deadsnakes PPA for newer Python versions if needed
43+
echo "Add deadsnakes PPA for newer Python versions if needed"
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add-apt-repository ppa:deadsnakes/ppa -y
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apt-get update -qq --fix-missing
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apt-get update -qq --fix-missing -o=Dpkg::Use-Pty=0 &> /dev/null
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echo "Install Python ${python_version} and other dependencies"
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apt-get install -q -y --no-install-recommends --allow-downgrades --allow-change-held-packages \
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build-essential \
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pkg-config \
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libnccl2 \
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libnccl-dev
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echo "Install Python ${python_version} and UV"
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apt-get install -y python${python_version} python${python_version}-venv python${python_version}-dev
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ln -sf /usr/bin/python${python_version} /usr/bin/python
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curl -LsSf https://astral.sh/uv/install.sh | sh
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# Source the environment and ensure UV is in PATH
63+
echo "Source the environment and ensure UV is in PATH"
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[ -f "$HOME/.local/bin/env" ] && . "$HOME/.local/bin/env"
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export PATH="$HOME/.local/bin:$PATH"
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source $HOME/.cargo/env 2>/dev/null || true
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export PATH="$HOME/.cargo/bin:$PATH"
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# Verify UV installation
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echo "Verify UV installation"
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command -v uv || (echo "UV not found in PATH" && exit 1)
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# Create and activate a local uv virtual environment
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uv venv .venv -p "/usr/bin/python${python_version}" || uv venv .venv -p "python${python_version}" || uv venv .venv
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. .venv/bin/activate
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hash -r
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echo "Show system information"
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whereis nvidia
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nvidia-smi
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python --version
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uv pip install "cython<3.0" wheel # for compatibility
99102
fi
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# install the base so we can adjust other packages
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echo "Install the base so we can adjust other packages"
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uv pip install .
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echo "Adjust torch versions in requirements files"
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PYTORCH_VERSION=$(python -c "import torch; print(torch.__version__.split('+')[0])")
@@ -119,6 +122,7 @@ run: |
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--target_import="lightning_fabric"
120123
fi
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echo "Install package with [${PACKAGE_NAME}] extras"
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extra=$(python -c "print({'lightning': 'fabric-'}.get('$(PACKAGE_NAME)', ''))")
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uv pip install ".[${extra}dev]" --upgrade
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‎.lightning/workflows/pytorch.yml‎

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@@ -12,7 +12,7 @@ parametrize:
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- image: "nvidia/cuda:12.1.1-runtime-ubuntu22.04"
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PACKAGE_NAME: "pytorch"
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python_version: "3.10"
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machine: "A100_X_2"
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machine: "L4_X_2"
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- image: "nvidia/cuda:12.6.3-runtime-ubuntu22.04"
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PACKAGE_NAME: "pytorch"
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python_version: "3.12"
@@ -37,12 +37,13 @@ env:
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RUN_ONLY_CUDA_TESTS: "1"
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3939
run: |
40-
# Install Python and UV
41-
apt-get update -qq --fix-missing
40+
echo "Installing dependencies"
41+
apt-get update -qq --fix-missing -o=Dpkg::Use-Pty=0 &> /dev/null
4242
apt-get install -q -y software-properties-common curl
43-
# Add deadsnakes PPA for newer Python versions if needed
43+
echo "Add deadsnakes PPA for newer Python versions if needed"
4444
add-apt-repository ppa:deadsnakes/ppa -y
45-
apt-get update -qq --fix-missing
45+
apt-get update -qq --fix-missing -o=Dpkg::Use-Pty=0 &> /dev/null
46+
echo "Install Python ${python_version} and other dependencies"
4647
apt-get install -q -y --no-install-recommends --allow-downgrades --allow-change-held-packages \
4748
build-essential \
4849
pkg-config \
@@ -54,23 +55,25 @@ run: |
5455
libnccl2 \
5556
libnccl-dev
5657
58+
echo "Install Python ${python_version} and UV"
5759
apt-get install -y python${python_version} python${python_version}-venv python${python_version}-dev
5860
ln -sf /usr/bin/python${python_version} /usr/bin/python
5961
curl -LsSf https://astral.sh/uv/install.sh | sh
6062
61-
# Source the environment and ensure UV is in PATH
63+
echo "Source the environment and ensure UV is in PATH"
6264
[ -f "$HOME/.local/bin/env" ] && . "$HOME/.local/bin/env"
6365
export PATH="$HOME/.local/bin:$PATH"
6466
source $HOME/.cargo/env 2>/dev/null || true
6567
export PATH="$HOME/.cargo/bin:$PATH"
6668
67-
# Verify UV installation
69+
echo "Verify UV installation"
6870
command -v uv || (echo "UV not found in PATH" && exit 1)
6971
# Create and activate a local uv virtual environment
7072
uv venv .venv -p "/usr/bin/python${python_version}" || uv venv .venv -p "python${python_version}" || uv venv .venv
7173
. .venv/bin/activate
7274
hash -r
7375
76+
echo "Show system information"
7477
whereis nvidia
7578
nvidia-smi
7679
python --version
@@ -98,7 +101,7 @@ run: |
98101
uv pip install "cython<3.0" wheel # for compatibility
99102
fi
100103
101-
# install the base so we can adjust other packages
104+
echo "Install the base so we can adjust other packages"
102105
uv pip install .
103106
echo "Adjust torch versions in requirements files"
104107
PYTORCH_VERSION=$(python -c "import torch; print(torch.__version__.split('+')[0])")
@@ -119,9 +122,11 @@ run: |
119122
--target_import="lightning_fabric,pytorch_lightning"
120123
fi
121124
125+
echo "Install package"
122126
extra=$(python -c "print({'lightning': 'pytorch-'}.get('$(PACKAGE_NAME)', ''))")
123127
uv pip install -e ".[${extra}dev]" --upgrade
124128
129+
echo "Ensure only a single package is installed"
125130
if [ "${PACKAGE_NAME}" == "pytorch" ]; then
126131
echo "uninstall lightning to have just single package"
127132
uv pip uninstall lightning

‎docs/source-pytorch/common/checkpointing_basic.rst‎

Lines changed: 36 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -58,12 +58,45 @@ Lightning automatically saves a checkpoint for you in your current working direc
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# simply by using the Trainer you get automatic checkpointing
5959
trainer = Trainer()
6060
61-
To change the checkpoint path use the `default_root_dir` argument:
61+
62+
Checkpoint save location
63+
========================
64+
65+
The location where checkpoints are saved depends on whether you have configured a logger:
66+
67+
**Without a logger**, checkpoints are saved to the ``default_root_dir``:
68+
69+
.. code-block:: python
70+
71+
# saves checkpoints to 'some/path/checkpoints/'
72+
trainer = Trainer(default_root_dir="some/path/", logger=False)
73+
74+
**With a logger**, checkpoints are saved to the logger's directory, **not** to ``default_root_dir``:
6275

6376
.. code-block:: python
6477
65-
# saves checkpoints to 'some/path/' at every epoch end
66-
trainer = Trainer(default_root_dir="some/path/")
78+
from lightning.pytorch.loggers import CSVLogger
79+
80+
# checkpoints will be saved to 'logs/my_experiment/version_0/checkpoints/'
81+
# NOT to 'some/path/checkpoints/'
82+
trainer = Trainer(
83+
default_root_dir="some/path/", # This will be ignored for checkpoints!
84+
logger=CSVLogger("logs", "my_experiment")
85+
)
86+
87+
To explicitly control the checkpoint location when using a logger, use the
88+
:class:`~lightning.pytorch.callbacks.ModelCheckpoint` callback:
89+
90+
.. code-block:: python
91+
92+
from lightning.pytorch.callbacks import ModelCheckpoint
93+
94+
# explicitly set checkpoint directory
95+
checkpoint_callback = ModelCheckpoint(dirpath="my/custom/checkpoint/path/")
96+
trainer = Trainer(
97+
logger=CSVLogger("logs", "my_experiment"),
98+
callbacks=[checkpoint_callback]
99+
)
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----

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