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+/labml-0.4.162.tar.gz
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+%global _empty_manifest_terminate_build 0
+Name:		python-labml
+Version:	0.4.162
+Release:	1
+Summary:	Organize Machine Learning Experiments
+License:	MIT License
+URL:		https://github.com/labml.ai/labml
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/1f/1c/0749cce878d9ae6e976062d18aa139d2fbb8559eae1ad63cacff6bf98d31/labml-0.4.162.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-gitpython
+Requires:	python3-pyyaml
+Requires:	python3-numpy
+
+%description
+<div align="center" style="margin-bottom: 100px;">
+
+<h1>Monitor deep learning model training and hardware usage from mobile.</h1>
+
+[![PyPI - Python Version](https://badge.fury.io/py/labml.svg)](https://badge.fury.io/py/labml)
+[![PyPI Status](https://pepy.tech/badge/labml)](https://pepy.tech/project/labml)
+[![Docs](https://img.shields.io/badge/labml-docs-blue)](https://docs.labml.ai/)
+[![Twitter](https://img.shields.io/twitter/follow/labmlai?style=social)](https://twitter.com/labmlai?ref_src=twsrc%5Etfw)
+
+<img src="https://github.com/labmlai/labml/blob/master/images/cover-dark.png" alt=""/>
+</div>
+
+### 🔥 Features
+
+* Monitor running experiments from [mobile phone](https://github.com/labmlai/labml/tree/master/app) (or laptop)
+[![View Run](https://img.shields.io/badge/labml-experiment-brightgreen)](https://app.labml.ai/run/9e7f39e047e811ebbaff2b26e3148b3d)
+* Monitor [hardware usage on any computer](https://github.com/labmlai/labml/blob/master/guides/hardware_monitoring.md) with a single command
+* Integrate with just 2 lines of code (see examples below)
+* Keeps track of experiments including infomation like git commit, configurations and hyper-parameters
+* Keep Tensorboard logs organized
+* Save and load checkpoints
+* API for custom visualizations
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/labmlai/labml/blob/master/samples/stocks/analysis.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/vpj/poker/blob/master/kuhn_cfr/kuhn_cfr.ipynb)
+* Pretty logs of training progress
+* [Change hyper-parameters while the model is training](https://github.com/labmlai/labml/blob/master/guides/dynamic_hyperparameters.md)
+* Open source! we also have a small hosted server for the mobile web app
+
+
+### Installation
+
+You can install this package using PIP.
+
+```bash
+pip install labml
+```
+
+### PyTorch example
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Ldu5tr0oYN_XcYQORgOkIY_Ohsi152fz?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/monitoring-ml-model-training-on-your-mobile-phone)
+
+```python
+from labml import tracker, experiment
+
+with experiment.record(name='sample', exp_conf=conf):
+    for i in range(50):
+        loss, accuracy = train()
+        tracker.save(i, {'loss': loss, 'accuracy': accuracy})
+```
+
+### PyTorch Lightning example
+
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/15aSPDwbKihDu_c3aFHNPGG5POjVlM2KO?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/pytorch-lightning)
+
+```python
+from labml import experiment
+from labml.utils.lightening import LabMLLighteningLogger
+
+trainer = pl.Trainer(gpus=1, max_epochs=5, progress_bar_refresh_rate=20, logger=LabMLLighteningLogger())
+
+with experiment.record(name='sample', exp_conf=conf, disable_screen=True):
+        trainer.fit(model, data_loader)
+
+```
+
+
+### TensorFlow 2.X Keras example
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1lx1dUG3MGaIDnq47HVFlzJ2lytjSa9Zy?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/monitor-keras-model-training-on-your-mobile-phone)
+
+```python
+from labml import experiment
+from labml.utils.keras import LabMLKerasCallback
+
+with experiment.record(name='sample', exp_conf=conf):
+    for i in range(50):
+        model.fit(x_train, y_train, epochs=conf['epochs'], validation_data=(x_test, y_test),
+                  callbacks=[LabMLKerasCallback()], verbose=None)
+```
+
+### 📚 Documentation
+
+* [Python API Reference](https://docs.labml.ai)
+* [Samples](https://github.com/labmlai/labml/tree/master/samples)
+
+##### Guides
+
+* [API to create experiments](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/experiment.ipynb)
+* [Track training metrics](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/tracker.ipynb)
+* [Monitored training loop and other iterators](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/monitor.ipynb)
+* [API for custom visualizations](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/analytics.ipynb)
+* [Configurations management API](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/configs.ipynb)
+* [Logger for stylized logging](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/logger.ipynb)
+
+### 🖥 Screenshots
+
+#### Formatted training loop output
+
+<div align="center">
+    <img src="https://raw.githubusercontent.com/vpj/lab/master/images/logger_sample.png" alt="Sample Logs"/>
+</div>
+
+#### Custom visualizations based on Tensorboard logs
+
+<div align="center">
+    <img src="https://raw.githubusercontent.com/vpj/lab/master/images/analytics.png" alt="Analytics"/>
+</div>
+
+## Tools
+
+### [Hosting your own experiments server](https://docs.labml.ai/cli/labml.html#cmdoption-labml-arg-app-server)
+
+```sh
+# Install the package
+pip install labml-app -U
+
+# Start the server
+
+labml app-server
+```
+
+
+### [Training models on cloud](https://github.com/labmlai/labml/tree/master/remote)
+
+```bash
+# Install the package
+pip install labml_remote
+
+# Initialize the project
+labml_remote init
+
+# Add cloud server(s) to .remote/configs.yaml
+
+# Prepare the remote server(s)
+labml_remote prepare
+
+# Start a PyTorch distributed training job
+labml_remote helper-torch-launch --cmd 'train.py' --nproc-per-node 2 --env GLOO_SOCKET_IFNAME enp1s0
+```
+
+### [Monitoring hardware usage](https://github.com/labmlai/labml/blob/master/guides/hardware_monitoring.md)
+
+```sh
+# Install packages and dependencies
+pip install labml psutil py3nvml
+
+# Start monitoring
+labml monitor
+```
+
+## Other Guides
+
+#### [Setting up a local Ubuntu workstation for deep learning](https://github.com/labmlai/labml/blob/master/guides/local-ubuntu.md)
+
+#### [Setting up a cloud computer for deep learning](https://github.com/labmlai/labml/blob/master/guides/remote-python.md)
+
+## Citing
+
+If you use LabML for academic research, please cite the library using the following BibTeX entry.
+
+
+```bibtext
+@misc{labml,
+ author = {Varuna Jayasiri, Nipun Wijerathne},
+ title = {labml.ai: A library to organize machine learning experiments},
+ year = {2020},
+ url = {https://labml.ai/},
+}
+```
+
+
+
+
+%package -n python3-labml
+Summary:	Organize Machine Learning Experiments
+Provides:	python-labml
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-labml
+<div align="center" style="margin-bottom: 100px;">
+
+<h1>Monitor deep learning model training and hardware usage from mobile.</h1>
+
+[![PyPI - Python Version](https://badge.fury.io/py/labml.svg)](https://badge.fury.io/py/labml)
+[![PyPI Status](https://pepy.tech/badge/labml)](https://pepy.tech/project/labml)
+[![Docs](https://img.shields.io/badge/labml-docs-blue)](https://docs.labml.ai/)
+[![Twitter](https://img.shields.io/twitter/follow/labmlai?style=social)](https://twitter.com/labmlai?ref_src=twsrc%5Etfw)
+
+<img src="https://github.com/labmlai/labml/blob/master/images/cover-dark.png" alt=""/>
+</div>
+
+### 🔥 Features
+
+* Monitor running experiments from [mobile phone](https://github.com/labmlai/labml/tree/master/app) (or laptop)
+[![View Run](https://img.shields.io/badge/labml-experiment-brightgreen)](https://app.labml.ai/run/9e7f39e047e811ebbaff2b26e3148b3d)
+* Monitor [hardware usage on any computer](https://github.com/labmlai/labml/blob/master/guides/hardware_monitoring.md) with a single command
+* Integrate with just 2 lines of code (see examples below)
+* Keeps track of experiments including infomation like git commit, configurations and hyper-parameters
+* Keep Tensorboard logs organized
+* Save and load checkpoints
+* API for custom visualizations
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/labmlai/labml/blob/master/samples/stocks/analysis.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/vpj/poker/blob/master/kuhn_cfr/kuhn_cfr.ipynb)
+* Pretty logs of training progress
+* [Change hyper-parameters while the model is training](https://github.com/labmlai/labml/blob/master/guides/dynamic_hyperparameters.md)
+* Open source! we also have a small hosted server for the mobile web app
+
+
+### Installation
+
+You can install this package using PIP.
+
+```bash
+pip install labml
+```
+
+### PyTorch example
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Ldu5tr0oYN_XcYQORgOkIY_Ohsi152fz?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/monitoring-ml-model-training-on-your-mobile-phone)
+
+```python
+from labml import tracker, experiment
+
+with experiment.record(name='sample', exp_conf=conf):
+    for i in range(50):
+        loss, accuracy = train()
+        tracker.save(i, {'loss': loss, 'accuracy': accuracy})
+```
+
+### PyTorch Lightning example
+
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/15aSPDwbKihDu_c3aFHNPGG5POjVlM2KO?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/pytorch-lightning)
+
+```python
+from labml import experiment
+from labml.utils.lightening import LabMLLighteningLogger
+
+trainer = pl.Trainer(gpus=1, max_epochs=5, progress_bar_refresh_rate=20, logger=LabMLLighteningLogger())
+
+with experiment.record(name='sample', exp_conf=conf, disable_screen=True):
+        trainer.fit(model, data_loader)
+
+```
+
+
+### TensorFlow 2.X Keras example
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1lx1dUG3MGaIDnq47HVFlzJ2lytjSa9Zy?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/monitor-keras-model-training-on-your-mobile-phone)
+
+```python
+from labml import experiment
+from labml.utils.keras import LabMLKerasCallback
+
+with experiment.record(name='sample', exp_conf=conf):
+    for i in range(50):
+        model.fit(x_train, y_train, epochs=conf['epochs'], validation_data=(x_test, y_test),
+                  callbacks=[LabMLKerasCallback()], verbose=None)
+```
+
+### 📚 Documentation
+
+* [Python API Reference](https://docs.labml.ai)
+* [Samples](https://github.com/labmlai/labml/tree/master/samples)
+
+##### Guides
+
+* [API to create experiments](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/experiment.ipynb)
+* [Track training metrics](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/tracker.ipynb)
+* [Monitored training loop and other iterators](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/monitor.ipynb)
+* [API for custom visualizations](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/analytics.ipynb)
+* [Configurations management API](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/configs.ipynb)
+* [Logger for stylized logging](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/logger.ipynb)
+
+### 🖥 Screenshots
+
+#### Formatted training loop output
+
+<div align="center">
+    <img src="https://raw.githubusercontent.com/vpj/lab/master/images/logger_sample.png" alt="Sample Logs"/>
+</div>
+
+#### Custom visualizations based on Tensorboard logs
+
+<div align="center">
+    <img src="https://raw.githubusercontent.com/vpj/lab/master/images/analytics.png" alt="Analytics"/>
+</div>
+
+## Tools
+
+### [Hosting your own experiments server](https://docs.labml.ai/cli/labml.html#cmdoption-labml-arg-app-server)
+
+```sh
+# Install the package
+pip install labml-app -U
+
+# Start the server
+
+labml app-server
+```
+
+
+### [Training models on cloud](https://github.com/labmlai/labml/tree/master/remote)
+
+```bash
+# Install the package
+pip install labml_remote
+
+# Initialize the project
+labml_remote init
+
+# Add cloud server(s) to .remote/configs.yaml
+
+# Prepare the remote server(s)
+labml_remote prepare
+
+# Start a PyTorch distributed training job
+labml_remote helper-torch-launch --cmd 'train.py' --nproc-per-node 2 --env GLOO_SOCKET_IFNAME enp1s0
+```
+
+### [Monitoring hardware usage](https://github.com/labmlai/labml/blob/master/guides/hardware_monitoring.md)
+
+```sh
+# Install packages and dependencies
+pip install labml psutil py3nvml
+
+# Start monitoring
+labml monitor
+```
+
+## Other Guides
+
+#### [Setting up a local Ubuntu workstation for deep learning](https://github.com/labmlai/labml/blob/master/guides/local-ubuntu.md)
+
+#### [Setting up a cloud computer for deep learning](https://github.com/labmlai/labml/blob/master/guides/remote-python.md)
+
+## Citing
+
+If you use LabML for academic research, please cite the library using the following BibTeX entry.
+
+
+```bibtext
+@misc{labml,
+ author = {Varuna Jayasiri, Nipun Wijerathne},
+ title = {labml.ai: A library to organize machine learning experiments},
+ year = {2020},
+ url = {https://labml.ai/},
+}
+```
+
+
+
+
+%package help
+Summary:	Development documents and examples for labml
+Provides:	python3-labml-doc
+%description help
+<div align="center" style="margin-bottom: 100px;">
+
+<h1>Monitor deep learning model training and hardware usage from mobile.</h1>
+
+[![PyPI - Python Version](https://badge.fury.io/py/labml.svg)](https://badge.fury.io/py/labml)
+[![PyPI Status](https://pepy.tech/badge/labml)](https://pepy.tech/project/labml)
+[![Docs](https://img.shields.io/badge/labml-docs-blue)](https://docs.labml.ai/)
+[![Twitter](https://img.shields.io/twitter/follow/labmlai?style=social)](https://twitter.com/labmlai?ref_src=twsrc%5Etfw)
+
+<img src="https://github.com/labmlai/labml/blob/master/images/cover-dark.png" alt=""/>
+</div>
+
+### 🔥 Features
+
+* Monitor running experiments from [mobile phone](https://github.com/labmlai/labml/tree/master/app) (or laptop)
+[![View Run](https://img.shields.io/badge/labml-experiment-brightgreen)](https://app.labml.ai/run/9e7f39e047e811ebbaff2b26e3148b3d)
+* Monitor [hardware usage on any computer](https://github.com/labmlai/labml/blob/master/guides/hardware_monitoring.md) with a single command
+* Integrate with just 2 lines of code (see examples below)
+* Keeps track of experiments including infomation like git commit, configurations and hyper-parameters
+* Keep Tensorboard logs organized
+* Save and load checkpoints
+* API for custom visualizations
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/labmlai/labml/blob/master/samples/stocks/analysis.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/vpj/poker/blob/master/kuhn_cfr/kuhn_cfr.ipynb)
+* Pretty logs of training progress
+* [Change hyper-parameters while the model is training](https://github.com/labmlai/labml/blob/master/guides/dynamic_hyperparameters.md)
+* Open source! we also have a small hosted server for the mobile web app
+
+
+### Installation
+
+You can install this package using PIP.
+
+```bash
+pip install labml
+```
+
+### PyTorch example
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Ldu5tr0oYN_XcYQORgOkIY_Ohsi152fz?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/monitoring-ml-model-training-on-your-mobile-phone)
+
+```python
+from labml import tracker, experiment
+
+with experiment.record(name='sample', exp_conf=conf):
+    for i in range(50):
+        loss, accuracy = train()
+        tracker.save(i, {'loss': loss, 'accuracy': accuracy})
+```
+
+### PyTorch Lightning example
+
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/15aSPDwbKihDu_c3aFHNPGG5POjVlM2KO?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/pytorch-lightning)
+
+```python
+from labml import experiment
+from labml.utils.lightening import LabMLLighteningLogger
+
+trainer = pl.Trainer(gpus=1, max_epochs=5, progress_bar_refresh_rate=20, logger=LabMLLighteningLogger())
+
+with experiment.record(name='sample', exp_conf=conf, disable_screen=True):
+        trainer.fit(model, data_loader)
+
+```
+
+
+### TensorFlow 2.X Keras example
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1lx1dUG3MGaIDnq47HVFlzJ2lytjSa9Zy?usp=sharing) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/hnipun/monitor-keras-model-training-on-your-mobile-phone)
+
+```python
+from labml import experiment
+from labml.utils.keras import LabMLKerasCallback
+
+with experiment.record(name='sample', exp_conf=conf):
+    for i in range(50):
+        model.fit(x_train, y_train, epochs=conf['epochs'], validation_data=(x_test, y_test),
+                  callbacks=[LabMLKerasCallback()], verbose=None)
+```
+
+### 📚 Documentation
+
+* [Python API Reference](https://docs.labml.ai)
+* [Samples](https://github.com/labmlai/labml/tree/master/samples)
+
+##### Guides
+
+* [API to create experiments](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/experiment.ipynb)
+* [Track training metrics](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/tracker.ipynb)
+* [Monitored training loop and other iterators](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/monitor.ipynb)
+* [API for custom visualizations](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/analytics.ipynb)
+* [Configurations management API](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/configs.ipynb)
+* [Logger for stylized logging](https://colab.research.google.com/github/labmlai/labml/blob/master/guides/logger.ipynb)
+
+### 🖥 Screenshots
+
+#### Formatted training loop output
+
+<div align="center">
+    <img src="https://raw.githubusercontent.com/vpj/lab/master/images/logger_sample.png" alt="Sample Logs"/>
+</div>
+
+#### Custom visualizations based on Tensorboard logs
+
+<div align="center">
+    <img src="https://raw.githubusercontent.com/vpj/lab/master/images/analytics.png" alt="Analytics"/>
+</div>
+
+## Tools
+
+### [Hosting your own experiments server](https://docs.labml.ai/cli/labml.html#cmdoption-labml-arg-app-server)
+
+```sh
+# Install the package
+pip install labml-app -U
+
+# Start the server
+
+labml app-server
+```
+
+
+### [Training models on cloud](https://github.com/labmlai/labml/tree/master/remote)
+
+```bash
+# Install the package
+pip install labml_remote
+
+# Initialize the project
+labml_remote init
+
+# Add cloud server(s) to .remote/configs.yaml
+
+# Prepare the remote server(s)
+labml_remote prepare
+
+# Start a PyTorch distributed training job
+labml_remote helper-torch-launch --cmd 'train.py' --nproc-per-node 2 --env GLOO_SOCKET_IFNAME enp1s0
+```
+
+### [Monitoring hardware usage](https://github.com/labmlai/labml/blob/master/guides/hardware_monitoring.md)
+
+```sh
+# Install packages and dependencies
+pip install labml psutil py3nvml
+
+# Start monitoring
+labml monitor
+```
+
+## Other Guides
+
+#### [Setting up a local Ubuntu workstation for deep learning](https://github.com/labmlai/labml/blob/master/guides/local-ubuntu.md)
+
+#### [Setting up a cloud computer for deep learning](https://github.com/labmlai/labml/blob/master/guides/remote-python.md)
+
+## Citing
+
+If you use LabML for academic research, please cite the library using the following BibTeX entry.
+
+
+```bibtext
+@misc{labml,
+ author = {Varuna Jayasiri, Nipun Wijerathne},
+ title = {labml.ai: A library to organize machine learning experiments},
+ year = {2020},
+ url = {https://labml.ai/},
+}
+```
+
+
+
+
+%prep
+%autosetup -n labml-0.4.162
+
+%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-labml -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.162-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..ad171ca
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+9f2758afab9e9cdf01b311f480c63a67  labml-0.4.162.tar.gz