Metadata-Version: 2.1
Name: thelper
Version: 0.2.1
Summary: Training framework & tools for PyTorch-based machine learning projects.
Home-page: https://github.com/plstcharles/thelper
Author: Pierre-Luc St-Charles
Author-email: stcharpl@crim.ca
License: Apache Software License 2.0
Description: ========
        Overview
        ========
        
        
        
        This package provides a training framework and CLI for PyTorch-based machine learning projects. This is free software distributed
        under the `Apache Software License version 2.0 <https://tldrlegal.com/license/apache-license-2.0-(apache-2.0)>`_ built by researchers
        and developers from the Centre de Recherche Informatique de Montréal / Computer Research Institute of Montreal (CRIM).
        
        For installation instructions, refer to the `installation guide <https://github.com/plstcharles/thelper/blob/master/INSTALL.rst>`_. For
        usage instructions, refer to the `user guide <https://github.com/plstcharles/thelper/blob/master/thelper_usage.txt>`_. Information about
        the auto-generated documentation is available `here <https://github.com/plstcharles/thelper/blob/master/DOCUMENTATION.rst>`_.
        
        
        Notes
        -----
        
        Development is still on-going --- expect the API and the internal classes to change rapidly.
        
        The project's structure was originally generated by `cookiecutter <https://github.com/audreyr/cookiecutter>`_ via `ionelmc's template <https://github.com/ionelmc/cookiecutter-pylibrary>`_.
        
        
        Changelog
        =========
        
        0.2.1 (2019/01/24)
        -------------------
        
        * Added typedef module & cleaned up parameter inspections
        * Cleaned up all drawing utils & added callback support to trainers
        * Added support for albumentation pipelines via wrapper
        * Updated all trainers/schedulers to rely on 0-based indexing
        * Updated travis/rtd configs for auto-deploy & 3.6 support
        
        0.2.0 (2019/01/15)
        -------------------
        
        * Added regression/segmentation tasks and trainers
        * Added interface for pascalvoc dataset
        * Refactored data loaders/parsers and cleaned up data package
        * Added lots of new utilities in base trainer implementation
        * Added new unit tests for transformations
        * Refactored transformations to use wrappers for augments/lists
        * Added new samplers with dataset scaling support
        * Added baseline implementation for FCN32s
        * Added mae/mse metrics implementations
        * Added trainer support for loss computation via external members
        * Added utils to download/verify/extract files
        
        
        0.1.1 (2019/01/14)
        -------------------
        
        * Minor fixups and updates for CCFB02 compatibility
        * Added RawPredictions metric to fetch data from trainers
        
        
        0.1.0 (2018/11/28)
        -------------------
        
        * Fixed readthedocs sphinx auto-build w/ mocking.
        * Refactored package structure to avoid env issues.
        * Rewrote seeding to allow 100% reproducible sessions.
        * Cleaned up config file parameter lists.
        * Cleaned up session output vars/logs/images.
        * Add support for eval-time augmentation.
        * Update transform wrappers for multi-channels & lists.
        * Add gui module w/ basic segmentation annotation tool.
        * Refactored task interfaces to allow merging.
        * Simplified model fine-tuning via checkpoints.
        
        
        0.0.2 (2018/10/18)
        -------------------
        
        * Completed first documentation pass.
        * Fixed travis/rtfd builds.
        * Fixed device mapping/loading issues.
        
        
        0.0.1 (2018/10/03)
        -------------------
        
        * Initial release (work in progress).
        
Keywords: pytorch,trainer,loader
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: ~=3.6
Provides-Extra: rst
