Training framework & tools for PyTorch-based machine learning projects.
Project description
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 built by researchers and developers from the Centre de Recherche Informatique de Montréal / Computer Research Institute of Montreal (CRIM).
To get a general idea of what this framework can be used for, visit the FAQ page. For installation instructions, refer to the installation guide. For usage instructions, refer to the user guide. The auto-generated documentation is available via readthedocs.io.
Notes
Development is still on-going — the API and internal classes may change in the future.
The project’s structure was originally generated by cookiecutter via ionelmc’s template.
Changelog
0.3.0 (2019/06/12)
Added dockerfile for containerized builds
Added object detection task & trainer implementations
Added CLI model/checkpoint export support
Added CLI dataset splitting/HDF5 support
Added baseline superresolution implementations
Added lots of new unit tests & docstrings
Cleaned up transform & display operations
0.2.8 (2019/03/17)
Cleaned up build tools & docstrings throughout api
Added user guide in documentation build
Update tasks to allow dataset interface override
Cleaned up trainer output logs
Added fully convolutional resnet implementation
Fixup various issues related to fine-tuning via ‘resume’
0.2.7 (2019/02/04)
Updated conda build recipe for python variants w/ auto upload
0.2.6 (2019/01/31)
Added framework checkpoint/configuration migration utilities
Fixed minor config parsing backward compatibility issues
Fixed minor bugs related to query & drawing utilities
0.2.2 - 0.2.5 (2019/01/29)
Fixed travis-ci matrix configuration
Added travis-ci deployment step for pypi
Fixed readthedocs documentation building
Updated readme shields & front page look
Cleaned up cli module entrypoint
Fixed openssl dependency issues for travis tox check jobs
Updated travis post-deploy to try to fix conda packaging (wip)
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).
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