data-maker/data/maker/__init__.py

"""
(c) 2019 Data Maker, hiplab.mc.vanderbilt.edu
version 1.0.0

This package serves as a proxy to the overall usage of the framework.
This package is designed to generate synthetic data from a dataset from an original dataset using deep learning techniques

@TODO:
    - Make configurable GPU, EPOCHS
"""
import pandas as pd
import numpy as np

        self._df = _args['data'] if 'data' in _args else None
        beg = datetime.now() #.strftime('%Y-%m-%d %H:%M:%S')
        gTrain = gan.Train(**_args)
        gTrain.apply()
       
        writer = transport.factory.instance(provider='file',context='write',path=os.sep.join([gTrain.out_dir,'map.json']))
        writer.write(self._encoder._map,overwrite=True)
        writer.close()

        #
        # @TODO: At this point we need to generate another some other objects
        #
        _args = {"network_args":self.network_args,"store":self.store,"info":self.info,"candidates":self.candidates,"data":self._df}
        if self.gpu :
            _args['gpu'] = self.gpu
        g = Generator(**_args)
        # g.run() 
        if os.path.exists(filename):
            else:
        # print ([_name,FORMAT, _date.strftime(FORMAT)])
        _store['lock'] = True