bug fix ...
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6e45704252
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@ -144,20 +144,22 @@ def generate(**_args):
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"""
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"""
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partition = _args['partition'] if 'partition' in _args else None
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partition = _args['partition'] if 'partition' in _args else None
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if not partition :
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if not partition :
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LOG_DIR = os.sep.join([_args['logs'],'output',_args['context']])
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MAP_FLDER = os.sep.join([_args['logs'],'output',_args['context']])
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# f = open(os.sep.join([_args['logs'],'output',_args['context'],'map.json']))
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# f = open(os.sep.join([_args['logs'],'output',_args['context'],'map.json']))
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else:
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else:
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LOG_DIR = os.sep.join([_args['logs'],'output',_args['context'],str(partition)])
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MAP_FOLDER = os.sep.join([_args['logs'],'output',_args['context'],str(partition)])
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# f = open(os.sep.join([_args['logs'],'output',_args['context'],str(partition),'map.json']))
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# f = open(os.sep.join([_args['logs'],'output',_args['context'],str(partition),'map.json']))
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f = open(os.sep.join([LOG_DIR,'map.json']))
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f = open(os.sep.join([MAP_FOLDER,'map.json']))
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_map = json.loads(f.read())
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_map = json.loads(f.read())
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f.close()
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f.close()
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#
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#
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# if 'file' in _args :
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# if 'file' in _args :
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# df = pd.read_csv(_args['file'])
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# df = pd.read_csv(_args['file'])
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# else:
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# else:
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# df = _args['data'] if not isinstance(_args['data'],str) else pd.read_csv(_args['data'])
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# df = _args['data'] if not isinstance(_args['data'],str) else pd.read_csv(_args['data'])
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args = {"context":_args['context'],"max_epochs":_args['max_epochs'],"candidates":_args['candidates']}
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args = {"context":_args['context'],"max_epochs":_args['max_epochs'],"candidates":_args['candidates']}
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args['logs'] = LOG_DIR if 'logs' in _args else 'logs'
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args['logs'] = _args['logs'] if 'logs' in _args else 'logs'
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args ['max_epochs'] = _args['max_epochs']
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args ['max_epochs'] = _args['max_epochs']
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# args['matrix_size'] = _matrix.shape[0]
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# args['matrix_size'] = _matrix.shape[0]
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args['batch_size'] = 2000
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args['batch_size'] = 2000
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@ -177,7 +179,6 @@ def generate(**_args):
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lparams = {'columns':None}
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lparams = {'columns':None}
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if partition :
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if partition :
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lparams['partition'] = partition
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lparams['partition'] = partition
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handler.load_meta(**lparams)
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handler.load_meta(**lparams)
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#
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#
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# Let us now format the matrices by reverting them to a data-frame with values
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# Let us now format the matrices by reverting them to a data-frame with values
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@ -244,7 +244,7 @@ class Components :
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writer = factory.instance(**_args['store'])
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writer = factory.instance(**_args['store'])
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_df = _args['data']
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_df = _args['data']
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if _schema :
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if _schema :
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columns = _df.columns.tolist
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columns = []
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for _item in _schema :
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for _item in _schema :
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name = _item['name']
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name = _item['name']
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_type = str
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_type = str
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2
setup.py
2
setup.py
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@ -5,7 +5,7 @@ import sys
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def read(fname):
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def read(fname):
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return open(os.path.join(os.path.dirname(__file__), fname)).read()
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return open(os.path.join(os.path.dirname(__file__), fname)).read()
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args = {"name":"data-maker",
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args = {"name":"data-maker",
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"version":"1.4.7.3",
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"version":"1.4.7.4",
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"author":"Vanderbilt University Medical Center","author_email":"steve.l.nyemba@vanderbilt.edu","license":"MIT",
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"author":"Vanderbilt University Medical Center","author_email":"steve.l.nyemba@vanderbilt.edu","license":"MIT",
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"packages":find_packages(),"keywords":["healthcare","data","transport","protocol"]}
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"packages":find_packages(),"keywords":["healthcare","data","transport","protocol"]}
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args["install_requires"] = ['data-transport@git+https://dev.the-phi.com/git/steve/data-transport.git','tensorflow==1.15','pandas','pandas-gbq','pymongo']
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args["install_requires"] = ['data-transport@git+https://dev.the-phi.com/git/steve/data-transport.git','tensorflow==1.15','pandas','pandas-gbq','pymongo']
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