API layer built on tf-2.0 for high performance and easy training
- We support only tensorflow 2.x, not 1.x support
- Emphasis on speed of training, when we have to choose between speed and code complexity, we will favor speed.
- Emphasis to build a high level API like Fast.ai on tensorflow
- Self contained but extendable.
- Every function should have proper documentation
- Notebook based examples should be provided
- Enable Multiple Runs and logging for seeing history of experiments.
pip install --upgrade --upgrade-strategy only-if-needed https://github.com/faizanahemad/FastNet/tarball/master
or for developer mode:
pip install -e .
- setup unit test suite
- setup Site Page
- https://www.tensorflow.org/guide/performance/overview
- https://www.tensorflow.org/beta/guide/effective_tf2
- https://www.tensorflow.org/beta/guide/data_performance
- https://www.tensorflow.org/tutorials/load_data/tf_records
- https://github.com/kalaspuffar/tensorflow-data
- https://www.tensorflow.org/datasets/overview
- https://www.tensorflow.org/guide/performance/datasets
- https://www.tensorflow.org/beta/guide/keras/training_and_evaluation