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@@ -0,0 +1 @@ +/neptune_lightgbm-2.0.0.tar.gz diff --git a/python-neptune-lightgbm.spec b/python-neptune-lightgbm.spec new file mode 100644 index 0000000..f15b430 --- /dev/null +++ b/python-neptune-lightgbm.spec @@ -0,0 +1,327 @@ +%global _empty_manifest_terminate_build 0 +Name: python-neptune-lightgbm +Version: 2.0.0 +Release: 1 +Summary: Neptune.ai LightGBM integration library +License: Apache-2.0 +URL: https://neptune.ai/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/24/20/8e12db5d9b599986450a2155581dfd42241ecfd29d353adf6099968560ca/neptune_lightgbm-2.0.0.tar.gz +BuildArch: noarch + +Requires: python3-graphviz +Requires: python3-importlib-metadata +Requires: python3-lightgbm +Requires: python3-matplotlib +Requires: python3-neptune +Requires: python3-pre-commit +Requires: python3-pytest +Requires: python3-pytest-cov +Requires: python3-scikit-plot + +%description +# Neptune + LightGBM Integration + +Experiment tracking, model registry, data versioning, and live model monitoring for LightGBM trained models. + +## What will you get with this integration? + +* Log, display, organize, and compare ML experiments in a single place +* Version, store, manage, and query trained models, and model building metadata +* Record and monitor model training, evaluation, or production runs live + +## What will be logged to Neptune? + +* training and validation metrics, +* parameters, +* feature names, num_features, and num_rows for the train set, +* hardware consumption (CPU, GPU, memory), +* stdout and stderr logs, +* training code and Git commit information, +* [other metadata](https://docs.neptune.ai/logging/what_you_can_log) + + +*Example dashboard with train-valid metrics and selected parameters* + + +## Resources + +* [Documentation](https://docs.neptune.ai/integrations/lightgbm) +* [Code example on GitHub](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/lightgbm/scripts/Neptune_LightGBM_train_summary.py) +* [Example of a run logged in the Neptune app](https://app.neptune.ai/o/common/org/lightgbm-integration/e/LGBM-86/dashboard/train-cls-summary-6c07f9e0-36ca-4432-9530-7fd3457220b6) +* [Run example in Google Colab](https://colab.research.google.com/github/neptune-ai/examples/blob/main/integrations-and-supported-tools/lightgbm/notebooks/Neptune_LightGBM.ipynb) + +## Example + +``` +# On the command line: +pip install neptune-lightgbm +``` + +```python +# In Python: +import lightgbm as lgb +import neptune +from neptune.integrations.lightgbm import NeptuneCallback + +# Start a run +run = neptune.init_run( + project="common/lightgbm-integration", + api_token=neptune.ANONYMOUS_API_TOKEN, +) + +# Create a NeptuneCallback instance +neptune_callback = NeptuneCallback(run=run) + +# Prepare datasets +... +lgb_train = lgb.Dataset(X_train, y_train) + +# Define model parameters +params = { + "boosting_type": "gbdt", + "objective": "multiclass", + "num_class": 10, + ... +} + +# Train the model +gbm = lgb.train( + params, + lgb_train, + callbacks=[neptune_callback], +) +``` + +## Support + +If you got stuck or simply want to talk to us, here are your options: + +* Check our [FAQ page](https://docs.neptune.ai/getting-started/getting-help#frequently-asked-questions) +* You can submit bug reports, feature requests, or contributions directly to the repository. +* Chat! When in the Neptune application click on the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP), +* You can just shoot us an email at support@neptune.ai + + + +%package -n python3-neptune-lightgbm +Summary: Neptune.ai LightGBM integration library +Provides: python-neptune-lightgbm +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-neptune-lightgbm +# Neptune + LightGBM Integration + +Experiment tracking, model registry, data versioning, and live model monitoring for LightGBM trained models. + +## What will you get with this integration? + +* Log, display, organize, and compare ML experiments in a single place +* Version, store, manage, and query trained models, and model building metadata +* Record and monitor model training, evaluation, or production runs live + +## What will be logged to Neptune? + +* training and validation metrics, +* parameters, +* feature names, num_features, and num_rows for the train set, +* hardware consumption (CPU, GPU, memory), +* stdout and stderr logs, +* training code and Git commit information, +* [other metadata](https://docs.neptune.ai/logging/what_you_can_log) + + +*Example dashboard with train-valid metrics and selected parameters* + + +## Resources + +* [Documentation](https://docs.neptune.ai/integrations/lightgbm) +* [Code example on GitHub](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/lightgbm/scripts/Neptune_LightGBM_train_summary.py) +* [Example of a run logged in the Neptune app](https://app.neptune.ai/o/common/org/lightgbm-integration/e/LGBM-86/dashboard/train-cls-summary-6c07f9e0-36ca-4432-9530-7fd3457220b6) +* [Run example in Google Colab](https://colab.research.google.com/github/neptune-ai/examples/blob/main/integrations-and-supported-tools/lightgbm/notebooks/Neptune_LightGBM.ipynb) + +## Example + +``` +# On the command line: +pip install neptune-lightgbm +``` + +```python +# In Python: +import lightgbm as lgb +import neptune +from neptune.integrations.lightgbm import NeptuneCallback + +# Start a run +run = neptune.init_run( + project="common/lightgbm-integration", + api_token=neptune.ANONYMOUS_API_TOKEN, +) + +# Create a NeptuneCallback instance +neptune_callback = NeptuneCallback(run=run) + +# Prepare datasets +... +lgb_train = lgb.Dataset(X_train, y_train) + +# Define model parameters +params = { + "boosting_type": "gbdt", + "objective": "multiclass", + "num_class": 10, + ... +} + +# Train the model +gbm = lgb.train( + params, + lgb_train, + callbacks=[neptune_callback], +) +``` + +## Support + +If you got stuck or simply want to talk to us, here are your options: + +* Check our [FAQ page](https://docs.neptune.ai/getting-started/getting-help#frequently-asked-questions) +* You can submit bug reports, feature requests, or contributions directly to the repository. +* Chat! When in the Neptune application click on the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP), +* You can just shoot us an email at support@neptune.ai + + + +%package help +Summary: Development documents and examples for neptune-lightgbm +Provides: python3-neptune-lightgbm-doc +%description help +# Neptune + LightGBM Integration + +Experiment tracking, model registry, data versioning, and live model monitoring for LightGBM trained models. + +## What will you get with this integration? + +* Log, display, organize, and compare ML experiments in a single place +* Version, store, manage, and query trained models, and model building metadata +* Record and monitor model training, evaluation, or production runs live + +## What will be logged to Neptune? + +* training and validation metrics, +* parameters, +* feature names, num_features, and num_rows for the train set, +* hardware consumption (CPU, GPU, memory), +* stdout and stderr logs, +* training code and Git commit information, +* [other metadata](https://docs.neptune.ai/logging/what_you_can_log) + + +*Example dashboard with train-valid metrics and selected parameters* + + +## Resources + +* [Documentation](https://docs.neptune.ai/integrations/lightgbm) +* [Code example on GitHub](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/lightgbm/scripts/Neptune_LightGBM_train_summary.py) +* [Example of a run logged in the Neptune app](https://app.neptune.ai/o/common/org/lightgbm-integration/e/LGBM-86/dashboard/train-cls-summary-6c07f9e0-36ca-4432-9530-7fd3457220b6) +* [Run example in Google Colab](https://colab.research.google.com/github/neptune-ai/examples/blob/main/integrations-and-supported-tools/lightgbm/notebooks/Neptune_LightGBM.ipynb) + +## Example + +``` +# On the command line: +pip install neptune-lightgbm +``` + +```python +# In Python: +import lightgbm as lgb +import neptune +from neptune.integrations.lightgbm import NeptuneCallback + +# Start a run +run = neptune.init_run( + project="common/lightgbm-integration", + api_token=neptune.ANONYMOUS_API_TOKEN, +) + +# Create a NeptuneCallback instance +neptune_callback = NeptuneCallback(run=run) + +# Prepare datasets +... +lgb_train = lgb.Dataset(X_train, y_train) + +# Define model parameters +params = { + "boosting_type": "gbdt", + "objective": "multiclass", + "num_class": 10, + ... +} + +# Train the model +gbm = lgb.train( + params, + lgb_train, + callbacks=[neptune_callback], +) +``` + +## Support + +If you got stuck or simply want to talk to us, here are your options: + +* Check our [FAQ page](https://docs.neptune.ai/getting-started/getting-help#frequently-asked-questions) +* You can submit bug reports, feature requests, or contributions directly to the repository. +* Chat! When in the Neptune application click on the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP), +* You can just shoot us an email at support@neptune.ai + + + +%prep +%autosetup -n neptune-lightgbm-2.0.0 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-neptune-lightgbm -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.0-1 +- Package Spec generated @@ -0,0 +1 @@ +03ea92ff249e9c76aa7ca5a58578797c neptune_lightgbm-2.0.0.tar.gz |