|
|
|
|
"""
|
|
|
|
|
(c) 2019 Data Maker, hiplab.mc.vanderbilt.edu
|
|
|
|
|
version 1.0.0
|
|
|
|
|
|
|
|
|
|
This package serves as a proxy to the overall usage of the framework.
|
|
|
|
|
This package is designed to generate synthetic data from a dataset from an original dataset using deep learning techniques
|
|
|
|
|
|
|
|
|
|
@TODO:
|
|
|
|
|
- Make configurable GPU, EPOCHS
|
|
|
|
|
"""
|
|
|
|
|
import pandas as pd
|
|
|
|
|
import numpy as np
|
|
|
|
|
ROUND_UP = 2
|
|
|
|
|
# _BINARY= ContinuousToDiscrete.binary(X,BIN_SIZE)
|
|
|
|
|
#
|
|
|
|
|
if 'gpu' in _args :
|
|
|
|
|
# f = open(os.sep.join([_args['logs'],'output',_args['context'],'map.json']))
|
|
|
|
|
self.name = _args['name']
|
|
|
|
|
self.autopilot = _args['autopilot'] if 'autopilot' in _args else False
|
|
|
|
|
self.generate = None
|
|
|
|
|
self.candidates = int(_args['candidates']) if 'candidates' in _args else 1
|
|
|
|
|
def run(self):
|
|
|
|
|
self.initalize()
|
|
|
|
|
super().__init__(**_args)
|
|
|
|
|
x = []
|
|
|
|
|
for values in batches :
|
|
|
|
|
pass
|
|
|
|
|
:param candidates(default 1) number of candidates to generate
|
|
|
|
|
:param info {columns,sql,from}
|
|
|
|
|
:param autopilot will generate output automatically
|
|
|
|
|
:param batch (default 2k) size of the batch
|
|
|
|
|
"""
|
|
|
|
|
return Trainer(**_args)
|
