Metadata-Version: 2.1
Name: dlex
Version: 0.0.5
Summary: Deep learning library for research experiments
Home-page: https://github.com/trungd/dlex
Author: Trung V. Dang
Author-email: trungv.dang@outlook.com
License: UNKNOWN
Description: [!] This code is under development and mainly for my personal use. This project is for fast prototyping of deep learning and machine learning model with minimal code. Some parts of the code may not be well-commented or lack of citation.
        
        dlex is an open source framework for machine learning scientific experiment. 
        
        # Features
        
        - [ ] Configuration-based experiment setup. Less code for more efficiency and reproducibility
        - [ ] Pytorch or Tensorflow 2.0 or scikit-learn as backend with similar training flow
        - [ ] Convenient "environment" for training similar models or tuning hyperparameter
        
        ![anim](anim.gif)
        
        # Install
        
        To install the current release
        
        ```
        pip install dlex
        ```
        
        Try your first dlex program
        
        ```python
        from dlex import yaml_configs, Configs
        from dlex.torch import PytorchBackend
        
        
        @yaml_configs("""backend: pytorch
        model:
            name: dlex.torch.models.DNN
            layers: [200, 100]
        dataset:
            name: dlex.datasets.MNIST
            num_train: 100
            num_test: 10
            num_classes: 5
        train:
            num_epochs: 10
            batch_size: 128
            optimizer:
                name: adam
                lr: 0.01
        test:
            metrics: [acc]""")
        def train(configs: Configs):
            params = configs.get_default_params()
            report = PytorchBackend(params).run_train()
            print(report.results)
        
        
        if __name__ == "__main__":
            train()
        ```
        
        # Resources
        
        - [Documentation](https://trungd.github.io/dlex/)
        - [Getting Started](https://trungd.github.io/dlex/getting_started.html)
        - [Various model implementations](dlex_impl/README.md)
        - [Implementations of machine learning algorithms for graph](https://github.com/trungd/ml-graph/)
        
        # License
        
        # Contributing
        
        Contributions are more than welcome! Please get in touch if you would like to help out.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=2.6
Description-Content-Type: text/markdown
