|
|
@ -197,17 +197,17 @@ def generate(**_args):
|
|
|
|
f = open(os.sep.join([_args['logs'],'output',_args['context'],'map.json']))
|
|
|
|
f = open(os.sep.join([_args['logs'],'output',_args['context'],'map.json']))
|
|
|
|
_map = json.loads(f.read())
|
|
|
|
_map = json.loads(f.read())
|
|
|
|
f.close()
|
|
|
|
f.close()
|
|
|
|
if 'file' in _args :
|
|
|
|
# if 'file' in _args :
|
|
|
|
df = pd.read_csv(_args['file'])
|
|
|
|
# df = pd.read_csv(_args['file'])
|
|
|
|
else:
|
|
|
|
# else:
|
|
|
|
df = _args['data'] if not isinstance(_args['data'],str) else pd.read_csv(_args['data'])
|
|
|
|
# df = _args['data'] if not isinstance(_args['data'],str) else pd.read_csv(_args['data'])
|
|
|
|
args = {"context":_args['context'],"max_epochs":_args['max_epochs'],"candidates":_args['candidates']}
|
|
|
|
args = {"context":_args['context'],"max_epochs":_args['max_epochs'],"candidates":_args['candidates']}
|
|
|
|
args['logs'] = _args['logs'] if 'logs' in _args else 'logs'
|
|
|
|
args['logs'] = _args['logs'] if 'logs' in _args else 'logs'
|
|
|
|
args ['max_epochs'] = _args['max_epochs']
|
|
|
|
args ['max_epochs'] = _args['max_epochs']
|
|
|
|
# args['matrix_size'] = _matrix.shape[0]
|
|
|
|
# args['matrix_size'] = _matrix.shape[0]
|
|
|
|
args['batch_size'] = 2000
|
|
|
|
args['batch_size'] = 2000
|
|
|
|
args['partition'] = 0 if 'partition' not in _args else _args['partition']
|
|
|
|
args['partition'] = 0 if 'partition' not in _args else _args['partition']
|
|
|
|
args['row_count'] = df.shape[0]
|
|
|
|
args['row_count'] = _args['data'].shape[0]
|
|
|
|
#
|
|
|
|
#
|
|
|
|
# @TODO: perhaps get the space of values here ... (not sure it's a good idea)
|
|
|
|
# @TODO: perhaps get the space of values here ... (not sure it's a good idea)
|
|
|
|
#
|
|
|
|
#
|
|
|
|