Skip to main content

Easy development of machine learning models

Project description

A library to develop 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 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

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

twodlearn-0.5.0.tar.gz (146.6 kB view hashes)

Uploaded source

Built Distribution

twodlearn-0.5.0-py3-none-any.whl (184.4 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page