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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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#
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month = np.random.randint(1,13)
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FORMAT = '%Y-%m-%d'
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_type = np.int
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_schema = self.get_schema()
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_iocolumns = self.info['columns']
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elif _args['apply'] == 'generate' :
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