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"""
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(c) 2019 Data Maker, hiplab.mc.vanderbilt.edu
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version 1.0.0
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This package serves as a proxy to the overall usage of the framework.
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This package is designed to generate synthetic data from a dataset from an original dataset using deep learning techniques
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@TODO:
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- Make configurable GPU, EPOCHS
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"""
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import pandas as pd
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import numpy as np
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}
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else:
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self.network_args = _args['network_args']
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self._encoder = None
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self._map = None
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self._df = _args['data'] if 'data' in _args else None
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self.logger.write(_args)
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if hasattr(caller,'_queue') :
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writer = transport.factory.instance(provider=transport.providers.FILE,context='write',path=os.sep.join([gTrain.out_dir,'map.json']))
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if os.path.exists(filename):
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return _df
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r = {}
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if _item['type'] in ['DATETIME','TIMESTAMP']:
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writer.write(_df,table=self.info['from'])
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_log = {'action':'io-data','input':{'candidates':1,'rows':int(self._df.shape[0])}}
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