Welcome to twodlearn’s documentation!¶
Contents:
Introduction¶
Twodlearn is a library designed to simplify the development of machine learning models.
A. Installation¶
1. Install the desired version of tensorflow (CPU or GPU)
pip install tensorflow # for CPU pip install tensorflow-gpu # for GPU
2. Clone the project
git clone git@github.com:danmar3/twodlearn.git twodlearn cd twodlearn
3. Install the project
pip install -e .
4. Install extras (optional)
pip install -e .[reinforce] pip install -e .[development]
B. Run the tests using pytest¶
install pytest pip install -U pytest
run the unit-tests using pytest:
cd twodlearn/tests/
pytest -ra # print a short test summary info at the end of the session
pytest -x --pdb # drop to PDB on first failure, then end test session
pytest --pdb --maxfail=3 # drop to PDB for first three failures
pytest --durations=10 # get the test execution time
pytest --lf # to only re-run the failures.
pytest --cache-clear # clear the cache of failed tests
Roadmap for v0.6¶
[x] migrate to TF 1.14
[ ] add documentation
[ ] add project to pypi
[ ] create LayerNamespace
[x] add a shortcut for required and optional input arguments
[x] add check_arguments method to Layer and TdlModel
[x] get_parameters now supports nested structures and nested SimpleNamespace
[ ] deprecate tuple initialization
[ ] deprecate optim
[ ] move feedforward to dense
[ ] cleanup common: clean deprecated descriptors and put them in separate file
[ ] remove redundant base classes, such as TdlObject
[ ] deprecate templates and design a format for estimators
[ ] deprecate options value
[ ] deprecate pyfmi and jmodelica