keras-models-factory

Factory generating keras models, with unit tests proving they work.

The repository includes integration tests showing that the networks perform well on certain datasets.

The tests include caching so that if a test is interrupted and re-launched, it resumes from where it had reached.

The idea is also available in the keras integration tests

LICENSE

Installation

pip3 install pew
pew new TEST_KERAS_MODELS_FACTORY
pip install git+https://github.com/shadiakiki1986/keras-models-factory.git

For GPU instances (e.g. AWS EC2 p2.xlarge): run init-gpu.sh

Usage

To test a keras model (copy one of the integration tests in tests)

To use a model from the factory:

from keras_models_factory import lstm

# stacked lstm
m1 = lstm.model_1(in_neurons=10, lstm_dim=[8,6], look_back=5)
m1.summary()
# ...

# single lstm followed by dense layers
m2 = lstm.model_2(in_neurons=10, lstm_dim=[8,6], look_back=5)
m2.summary()
# _________________________________________________________________
# Layer (type)                 Output Shape              Param #
# =================================================================
# lstm_1 (LSTM)                (None, 8)                 608
# _________________________________________________________________
# dense_1 (Dense)              (None, 6)                 54
# _________________________________________________________________
# dense_2 (Dense)              (None, 1)                 7
# =================================================================
# Total params: 669
# Trainable params: 669
# Non-trainable params: 0
# _________________________________________________________________

Testing

sudo apt-get install python3-tk

pip3 install pew
pew new KERAS_MODELS_FACTORY

# http://stackoverflow.com/questions/28509965/ddg#28842733
pip install -e .[dev]

# for GPU usage, check
# https://gist.github.com/shadiakiki1986/0c9ea999113691fb9a7ae64e3541fe29#file-init-gpu-sh

# run tests
nosetests --logging-level INFO --nocapture

# or run individual tests
# http://pythontesting.net/framework/specify-test-unittest-nosetests-pytest/
# https://nose.readthedocs.io/en/latest/plugins/logcapture.html
nosetests --logging-level INFO --nocapture -v tests/test_lstm_ds1.py:TestLstmDs1.test_fit_model_1
nosetests --logging-level INFO --nocapture -v tests/test_lstm_ds1.py:TestLstmDs1.test_fit_model_2

Note that ATM I moved some LSTM slow tests into

• tests/data/params_lstm_1_slow.yml
• and tests/data/params_lstm_2_slow.yml

To run tests in parallel

sudo apt-get install parallel
ls tests/test*py -1|pew in KERAS_MODELS_FACTORY parallel nosetests --logging-level INFO --nocapture -v {}

Note that the nosetests parameter --processes doesnt work and yields a CUDA_ERROR_NOT_INITIALIZED

Dev notes

In order for import keras_models_factor as kmf; help(kmf.datasets) to work, I use the keras_models_factory/__init__.py to have the imports. Ref: https://stackoverflow.com/a/46242108/4126114