Metadata-Version: 2.1
Name: pytorch_nn_tools
Version: 0.3.7
Summary: Tools for NN creation with Pytorch
Home-page: https://github.com/serge-m/pytorch_nn_tools
Author: SergeM
Author-email: serge-m@users.noreply.github.com
License: MIT license
Description: ================
        pytorch-nn-tools
        ================
        
        
        .. image:: https://img.shields.io/pypi/v/pytorch-nn-tools.svg
                :target: https://pypi.python.org/pypi/pytorch-nn-tools
        
        .. image:: https://travis-ci.com/serge-m/pytorch-nn-tools.svg?branch=master
                :target: https://travis-ci.com/github/serge-m/pytorch-nn-tools/
        
        .. image:: https://readthedocs.org/projects/pytorch-nn-tools/badge/?version=latest
                :target: https://pytorch-nn-tools.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        
        
        
        Tools for NN creation with Pytorch. The project is greatly inspired by fast.ai library.
        The project brings the convenience functions from fast.ai to a usual pytorch user.
        
        
        Usage examples
        =============================================================
        
        CheckpointSaver
        -----------------------------------
        
        .. code-block:: python
        
            from pytorch_nn_tools.devices import to_device
            from pytorch_nn_tools.train.checkpoint import CheckpointSaver
        
            checkpoint_saver = CheckpointSaver(path_checkpoints, logger=DummyLogger())
        
            # create your model, optimizer, scheduler
            # train for several epochs
            for epoch in range(100):
                .....
                # at the end of each epoch we save the results
                checkpoint_saver.save(model, optimizer, scheduler, epoch)
        
        
        
            # later you can load the latest checkpoint and continue training
            last = checkpoint_saver.find_last(start_epoch, end_epoch)
            if last is not None:
                print(f"found pretrained results for epoch {last}. Loading...")
                self.checkpoint_saver.load(model, optimizer, scheduler, last)
            else:
                print(f"pretrained weights are not found")
        
        
        Misc
        =============================================================
        * Free software: MIT license
        * Documentation: https://pytorch-nn-tools.readthedocs.io.
        
        
Keywords: pytorch_nn_tools
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
