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import os, sys |
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currentdir = os.path.dirname(os.path.realpath(__file__)) |
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parentdir = os.path.dirname(currentdir) |
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sys.path.append(parentdir) |
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import argparse |
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from configparser import ConfigParser |
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from shutil import copy2 |
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import os |
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from datetime import datetime |
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TRAIN_DATASET = '/mnt/EncryptedData1/Users/javier/ext_datasets/COMET_dataset/OSLO_COMET_CT/Formatted_128x128x128/train' |
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err = list() |
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if __name__ == '__main__': |
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parser = argparse.ArgumentParser() |
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parser.add_argument('--ini', help='Configuration file') |
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args = parser.parse_args() |
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configFile = ConfigParser() |
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configFile.read(args.ini) |
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print('Loaded configuration file: ' + args.ini) |
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print({section: dict(configFile[section]) for section in configFile.sections()}) |
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print('\n\n') |
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trainConfig = configFile['TRAIN'] |
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lossesConfig = configFile['LOSSES'] |
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datasetConfig = configFile['DATASETS'] |
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othersConfig = configFile['OTHERS'] |
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print('TRAIN MODEL IN' + trainConfig['model']) |
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simil = lossesConfig['similarity'].split(',') |
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segm = lossesConfig['segmentation'].split(',') |
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if trainConfig['name'].lower() == 'uw': |
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from COMET.COMET_train_UW import launch_train |
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output_folder = os.path.join(othersConfig['outputFolder'], '{}_Lsim_{}__Lseg_{}'.format(trainConfig['name'], '_'.join(simil), '_'.join(segm))) |
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else: |
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from COMET.COMET_train import launch_train |
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simil = simil[0] |
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segm = segm[0] |
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output_folder = os.path.join(othersConfig['outputFolder'], '{}_Lsim_{}__Lseg_{}'.format(trainConfig['name'], simil, segm)) |
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output_folder = output_folder + '_' + datetime.now().strftime("%H%M%S-%d%m%Y") |
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try: |
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froozen_layers = eval(trainConfig['freeze']) |
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except NameError as err: |
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froozen_layers = [trainConfig['freeze'].upper()] |
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if froozen_layers is not None: |
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assert all(s in ['INPUT', 'OUTPUT', 'ENCODER', 'DECODER', 'TOP', 'BOTTOM'] for s in froozen_layers),\ |
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'Invalid option for "freeze". Expected one or several of: INPUT, OUTPUT, ENCODER, DECODER, TOP, BOTTOM' |
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froozen_layers = list(set(froozen_layers)) |
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os.makedirs(output_folder, exist_ok=True) |
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copy2(args.ini, os.path.join(output_folder, os.path.split(args.ini)[-1])) |
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launch_train(dataset_folder=datasetConfig['train'], |
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validation_folder=datasetConfig['validation'], |
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output_folder=output_folder, |
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gpu_num=eval(trainConfig['gpu']), |
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lr=eval(trainConfig['learningRate']), |
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rw=eval(trainConfig['regularizationWeight']), |
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simil=simil, |
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segm=segm, |
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max_epochs=eval(trainConfig['epochs']), |
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model_file=trainConfig['model'], |
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freeze_layers=froozen_layers, |
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acc_gradients=eval(trainConfig['accumulativeGradients']), |
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batch_size=eval(trainConfig['batchSize'])) |
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