Metadata-Version: 2.1
Name: fc-pruning
Version: 0.1.0
Summary: FC Pruning
Home-page: https://github.com/AidaMehammed/fc-pruning
Author: Aida Mehammed
Author-email: aida.mehammed@studium.uni-hamburg.de
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/AidaMehammed/fc-pruning/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# [FeatureCloud Pruning](https://github.com/AidaMehammed/FC_Pruning_App)
### Model Compression with Pruning

The FC Pruning package offers a streamlined approach to model compression using advanced pruning techniques. With support for federated learning frameworks and integration with the [Torch-Pruning](https://github.com/VainF/Torch-Pruning/tree/master) library, this package enables efficient distributed training, suitable for a wide range of machine learning tasks.
1. Train Local Model


    
2. Configure Quantization:
    - Set up initial quantization settings.
      ```python
        self.configure_pruning(pruning_ratio, model, reference_model, imp,ex_input,
                               ignored_layers)        
      ```



 

3. Send Data to Coordinator and perform Pruning:
    - Send the prepared model data to the coordinator.
   ```python
    self.send_data_to_coordinator(model, use_pruning=True, use_smpc=False, use_dp=False)
   ```

