torch_em.util.training

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 1import argparse
 2
 3
 4def parser_helper(description=None, default_iterations=int(1e5), default_batch_size=1, require_input=True):
 5    description = "Run torch_em training" if description is None else description
 6    parser = argparse.ArgumentParser(description)
 7    if require_input:
 8        parser.add_argument("-i", "--input", required=True,
 9                            help="Path to the input data, if not present an attempt will be made to download the data.")
10    parser.add_argument("-n", "--n_iterations", type=int, default=default_iterations,
11                        help="The number of training iterations.")
12    parser.add_argument("-b", "--batch_size", type=int, default=default_batch_size,
13                        help="The batch size")
14    parser.add_argument("--check", "-c", type=int, default=0, help="Check the data loader instead of running training.")
15    parser.add_argument("--from_checkpoint", type=int, default=0, help="Start training from existing checkpoint.")
16    parser.add_argument("--device", type=str, default=None)
17    return parser

def parser_helper( description=None, default_iterations=100000, default_batch_size=1, require_input=True): View Source

 5def parser_helper(description=None, default_iterations=int(1e5), default_batch_size=1, require_input=True):
 6    description = "Run torch_em training" if description is None else description
 7    parser = argparse.ArgumentParser(description)
 8    if require_input:
 9        parser.add_argument("-i", "--input", required=True,
10                            help="Path to the input data, if not present an attempt will be made to download the data.")
11    parser.add_argument("-n", "--n_iterations", type=int, default=default_iterations,
12                        help="The number of training iterations.")
13    parser.add_argument("-b", "--batch_size", type=int, default=default_batch_size,
14                        help="The batch size")
15    parser.add_argument("--check", "-c", type=int, default=0, help="Check the data loader instead of running training.")
16    parser.add_argument("--from_checkpoint", type=int, default=0, help="Start training from existing checkpoint.")
17    parser.add_argument("--device", type=str, default=None)
18    return parser