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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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self._df = _args['data'] if 'data' in _args else None
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return [] #{'name':self._df.dtypes.index.tolist()[i],'type':self._df.dtypes.astype(str).tolist()[i]}for i in range(self._df.dtypes.shape[0])]
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super().__init__(**_args)
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# g.run()
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_date = datetime(year=year,month=month,day=day,minute=0,hour=0,second=0)
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if 'format' in self.info and name in self.info['format'] :
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return _df
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def __init__(self,**_args):
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