def soft_pattern_arg_parser():
""" CLI args related to SoftPatternsClassifier """
p = ArgumentParser(add_help=False,
parents=[lstm_arg_parser(), mlp_arg_parser()])
p.add_argument("-u", "--use_rnn", help="Use an RNN underneath soft-patterns", action="store_true")
p.add_argument("-p", "--patterns",
help="Pattern lengths and numbers: an underscore separated list of length-number pairs",
default="5-50_4-50_3-50_2-50")
p.add_argument("--maxplus",
help="Use max-plus semiring instead of plus-times",
default=False, action='store_true')
p.add_argument("--maxtimes",
help="Use max-times semiring instead of plus-times",
default=False, action='store_true')
p.add_argument("--bias_scale_param",
help="Scale bias term by this parameter",
default=0.1, type=float)
p.add_argument("--eps_scale",
help="Scale epsilon by this parameter",
default=None, type=float)
p.add_argument("--self_loop_scale",
help="Scale self_loop by this parameter",
default=None, type=float)
p.add_argument("--no_eps", help="Don't use epsilon transitions", action='store_true')
p.add_argument("--no_sl", help="Don't use self loops", action='store_true')
p.add_argument("--shared_sl",
help="Share main path and self loop parameters, where self loops are discounted by a self_loop_parameter. "+
str(SHARED_SL_PARAM_PER_STATE_PER_PATTERN)+
": one parameter per state per pattern, "+str(SHARED_SL_SINGLE_PARAM)+
": a global parameter.", type=int, default=0)
return p
if model_save_dir is not None:
if not os.path.exists(model_save_dir):
os.makedirs(model_save_dir)
print("Training with", model_file_prefix)
train(train_data,
dev_data,
model,
num_classes,
model_save_dir,
args.num_iterations,
model_file_prefix,
args.learning_rate,
args.batch_size,
args.scheduler,
gpu=args.gpu,
clip=args.clip,
debug=args.debug,
dropout=dropout,
word_dropout=args.word_dropout,
patience=args.patience)
if __name__ == '__main__':
parser = \
argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
parents=[lstm_arg_parser(), mlp_arg_parser(), training_arg_parser(), general_arg_parser()])
main(parser.parse_args())