optimization (minor)
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@ -197,17 +197,17 @@ def generate(**_args):
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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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_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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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'] = _args['logs'] 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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args['partition'] = 0 if 'partition' not in _args else _args['partition']
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args['partition'] = 0 if 'partition' not in _args else _args['partition']
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args['row_count'] = df.shape[0]
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args['row_count'] = _args['data'].shape[0]
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#
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#
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# @TODO: perhaps get the space of values here ... (not sure it's a good idea)
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# @TODO: perhaps get the space of values here ... (not sure it's a good idea)
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#
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#
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