A library to develop machine learning models.

• 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]

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

• [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