src/similarity/siamese.py [23:36]:
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logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
logger.addHandler(logging.StreamHandler(sys.stdout))
    
parser = argparse.ArgumentParser(description='PyTorch CNN Siamese Network')

# Hyperparameters sent by the client are passed as command-line arguments to the script.
parser.add_argument('--batch-size', type=int, default=64, help='mini batch size')
parser.add_argument('--epochs', type=int, default=10, help='number of epochs')
parser.add_argument('--learning-rate', type=float, default=1e-4, help='learning rate')
parser.add_argument('--similarity-dims', type=int, default=64, 
                    help='the number of dimensions of the image vectors used for calculating similarity')
parser.add_argument('--similarity-margin', type=float, default=0.03, help='margin of error within labels to be considered correct')
parser.add_argument('--optimizer', type=str, default='Adam', help='optimizer to use for training')
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src/similarity/siamese2.py [25:38]:
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logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
logger.addHandler(logging.StreamHandler(sys.stdout))
    
parser = argparse.ArgumentParser(description='PyTorch CNN Siamese Network')

# Hyperparameters sent by the client are passed as command-line arguments to the script.
parser.add_argument('--batch-size', type=int, default=64, help='mini batch size')
parser.add_argument('--epochs', type=int, default=10, help='number of epochs')
parser.add_argument('--learning-rate', type=float, default=1e-4, help='learning rate')
parser.add_argument('--similarity-dims', type=int, default=64, 
                    help='the number of dimensions of the image vectors used for calculating similarity')
parser.add_argument('--similarity-margin', type=float, default=0.03, help='margin of error within labels to be considered correct')
parser.add_argument('--optimizer', type=str, default='Adam', help='optimizer to use for training')
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