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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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if value >= item.left and value <= item.right :
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df = args['data'] if not isinstance(args['data'],str) else pd.read_csv(args['data'])
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trainer = gan.Train(**args)
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trainer.apply()
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def post(**args):
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"""
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This uploads the tensorflow checkpoint to a data-store (mongodb, biguqery, s3)
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"""
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pass
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# NO_VALUE = dict(args['no_value']) if type(args['no_value']) == dict else args['no_value']
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# print ([col,df[col].dtype,_df[col].tolist()])
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