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- """Parser for arguments
-
- Put all arguments in one file and group similar arguments
- """
- import argparse
-
-
- class Parser():
-
- def __init__(self, description):
- '''
- arguments parser
- '''
- self.parser = argparse.ArgumentParser(description=description)
- self.args = None
- self._parse()
-
- def _parse(self):
- # dataset
- self.parser.add_argument(
- '--dataset', type=str, default="MUTAG",
- choices=['MUTAG', 'COLLAB', 'IMDBBINARY', 'IMDBMULTI'],
- help='name of dataset (default: MUTAG)')
- self.parser.add_argument(
- '--batch_size', type=int, default=32,
- help='batch size for training and validation (default: 32)')
- self.parser.add_argument(
- '--fold_idx', type=int, default=0,
- help='the index(<10) of fold in 10-fold validation.')
- self.parser.add_argument(
- '--filename', type=str, default="",
- help='output file')
-
- # device
- self.parser.add_argument(
- '--disable-cuda', action='store_true',
- help='Disable CUDA')
- self.parser.add_argument(
- '--device', type=int, default=0,
- help='which gpu device to use (default: 0)')
-
- # net
- self.parser.add_argument(
- '--num_layers', type=int, default=5,
- help='number of layers (default: 5)')
- self.parser.add_argument(
- '--num_mlp_layers', type=int, default=2,
- help='number of MLP layers(default: 2). 1 means linear model.')
- self.parser.add_argument(
- '--hidden_dim', type=int, default=64,
- help='number of hidden units (default: 64)')
-
- # graph
- self.parser.add_argument(
- '--graph_pooling_type', type=str,
- default="sum", choices=["sum", "mean", "max"],
- help='type of graph pooling: sum, mean or max')
- self.parser.add_argument(
- '--neighbor_pooling_type', type=str,
- default="sum", choices=["sum", "mean", "max"],
- help='type of neighboring pooling: sum, mean or max')
- self.parser.add_argument(
- '--learn_eps', action="store_true",
- help='learn the epsilon weighting')
-
- # learning
- self.parser.add_argument(
- '--seed', type=int, default=0,
- help='random seed (default: 0)')
- self.parser.add_argument(
- '--epochs', type=int, default=350,
- help='number of epochs to train (default: 350)')
- self.parser.add_argument(
- '--lr', type=float, default=0.01,
- help='learning rate (default: 0.01)')
- self.parser.add_argument(
- '--final_dropout', type=float, default=0.5,
- help='final layer dropout (default: 0.5)')
-
- # done
- self.args = self.parser.parse_args()
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