Metadata-Version: 2.1
Name: torchfit
Version: 0.2.0
Summary: TorchFit is a simple, easy-to-use, and minimalistic training-helper for PyTorch
Home-page: https://github.com/amaiya/torchfit
Author: Arun S. Maiya
Author-email: arun@maiya.net
License: MIT
Description: # TorchFit
        
        `TorchFit` is a bare-bones, minimalistic *training-helper* for **PyTorch** that exposes an easy-to-use `fit` method in the style of **fastai** and **Keras**.  
        
        `TorchFit` is intended to be minimally-invasive with a tiny footprint and as little bloat as possible. It is well-suited to those that are new to training models in PyTorch. For more complex training scenarios (e.g., training GANs, multi-node GPU training), [PyTorch Lightning](https://github.com/PyTorchLightning/pytorch-lightning) is highly recommended.
        
        
        ## Usage
        
        ```python
        
        
        # normal PyTorch stuff
        train_loader = create_your_training_data_loader()
        val_loader = create_your_validation_data_loader()
        test_loader = create_your_test_data_loader()
        model = create_your_pytorch_model()
        
        # wrap model and data in Learner
        import torchfit
        learner = torchfit.Learner(model, train_loader, val_loader=val_loader)
        
        # estimate LR using Learning Rate Finder
        learner.find_lr()
        
        # train using 1cycle learning rate policy
        learner.fit_onecycle(1e-4, 3)
        
        # plot training vs. validation loss
        learner.plot('loss')
        
        # make predictions as easy as in Keras
        y_pred = learner.predict(test_loader)
        
        # save model and reload later
        learner.save('/tmp/mymodel')
        learer.load('/tmp/mymodel')
        ```
        
        ### For more information, see the [Tutorial Notebook](https://github.com/amaiya/torchfit/blob/master/examples/tutorial.ipynb).
        
        
        ## Installation
        
        After ensuring [PyTorch is installed](https://pytorch.org/get-started/locally/), install `TorchFit` with:
        
        ```
        pip3 install torchfit
        
        ```
        
        <!-- pip3 install pillow==6.2.2 torch==1.3.1+cu100 torchvision==0.4.2+cu100 -f https://download.pytorch.org/whl/torch_stable.html -->
        
Keywords: pytorch,deep learning,machine learning
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
