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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.name = self.__class__.__name__
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_log = {'action':'data-prep','input':{'rows':self._df.shape[0],'cols':self._df.shape[1]} }
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_args['values'] = np.array(values)
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_args['row_count'] = self._df.shape[0]
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return _df
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:param store {source,target} if no target is provided console will be output
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:param epochs (default 2) number of epochs to train
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:param candidates(default 1) number of candidates to generate
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:param info {columns,sql,from}
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:param autopilot will generate output automatically
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:param batch (default 2k) size of the batch
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"""
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return Trainer(**_args)
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