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# -*- coding: utf-8 -*-
"""
Created on Sat Oct 29 14:56:09 2022
@author: Santiago Moreno
"""
import os
import argparse
from functions import json_to_txt, training_model, characterize_data, upsampling_data, str2bool, usage_cuda,copy_data
default_path = os.path.dirname(os.path.abspath(__file__))
os.chdir(default_path)
if __name__ == '__main__':
parser = argparse.ArgumentParser(add_help=True, usage='Train a new model with given data (GPU optional)')
parser.add_argument('-f','--fast', type=str2bool, nargs='?',const=True, default=False, help='Training fast option (Only for functioning test)', choices=(True, False), required=False)
parser.add_argument('-m','--model', type=str, nargs='?', help='New model name', required=True)
parser.add_argument('-s','--standard', type=str2bool, nargs='?',const=True, default=False, help='Standard CONLL input or not', choices=(True, False), required=False)
parser.add_argument('-id','--input_dir', type=str, nargs='?', help='Absolute path input directory', required=True)
parser.add_argument('-u','--up_sample_flag', type=str2bool, nargs='?',const=True, default=False , help='Boolean value to upsampling the data = True or not upsampling = False', required=False, choices=(True, False))
parser.add_argument('-cu','--cuda', type=str2bool, nargs='?', const=True, default=False, help='Boolean value for using cuda to Train the model (True). By defaul False.', choices=(True, False), required=False)
args = parser.parse_args()
if args.fast: epochs = 1
else: epochs = 20
if args.standard:
copy_data(args.input_dir)
not_error=True
else:
Error = json_to_txt(args.input_dir)
if type(Error)==int:
print('Error processing the input documents, code error {}'.format(Error))
not_error=False
else:
not_error=True
if not_error:
if args.up_sample_flag:
entities_dict=characterize_data()
entities = list(entities_dict.keys())
entities_to_upsample = [entities[i] for i,value in enumerate(entities_dict.values()) if value < 200]
upsampling_data(entities_to_upsample, 0.8, entities)
if args.cuda: cuda_info = usage_cuda(True)
else: cuda_info = usage_cuda(False)
print(cuda_info)
Error = training_model(args.model,epochs)
if type(Error)==int:
print('Error training the model, code error {}'.format(Error))
else:
print('Training complete')
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