Metadata-Version: 2.1
Name: fandak
Version: 0.0.1a1.dev5
Summary: A Framework for Deep Learning Research in PyTorch.
Home-page: https://github.com/yassersouri/fandak
Author: Yasser Souri
Author-email: yassersouri@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Typing :: Typed
Description-Content-Type: text/markdown
Requires-Dist: torch (<2,>=1.0)
Requires-Dist: torchvision (<1,>=0.3)
Requires-Dist: tqdm (<5,>=4.32)
Requires-Dist: matplotlib (<4,>=3.1.1)
Requires-Dist: tensorboard (<2,>=1.14.0)
Requires-Dist: future (<1,>=0.17.1)

# Fandak: فندک

## Ideas

* Config files:
    - One idea is to have config files (python files) with a specific signature that implements a specific function.
    - These files should be able to be loaded dynamically.
    - These files should be able to be saved in snapshot directories for resuming.
    - But it is confusing for me how to manage the dependencies for these config files.
    - I think 3 config files are needed: Train Dataset, Model, Training
    - We can have one more config file for: Evaluation. 

