45 lines
2.7 KiB
Python
45 lines
2.7 KiB
Python
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class ParserClass(object):
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def __init__(self, parser):
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"""
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Parses arguments and saves them in the Parser Class
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:param parser: A parser to get input from
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"""
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parser.add_argument('--batch_size', nargs="?", type=int, default=64, help='batch_size for experiment')
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parser.add_argument('--epochs', type=int, nargs="?", default=100, help='Number of epochs to train for')
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parser.add_argument('--logs_path', type=str, nargs="?", default="classification_logs/",
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help='Experiment log path, '
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'where tensorboard is saved, '
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'along with .csv of results')
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parser.add_argument('--experiment_prefix', nargs="?", type=str, default="classification",
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help='Experiment name without hp details')
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parser.add_argument('--continue_epoch', nargs="?", type=int, default=-1, help="ID of epoch to continue from, "
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"-1 means from scratch")
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parser.add_argument('--tensorboard_use', nargs="?", type=str, default="False",
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help='Whether to use tensorboard')
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parser.add_argument('--dropout_rate', nargs="?", type=float, default=0.35, help="Dropout value")
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parser.add_argument('--batch_norm_use', nargs="?", type=str, default="False", help='Whether to use tensorboard')
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parser.add_argument('--strided_dim_reduction', nargs="?", type=str, default="False",
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help='Whether to use tensorboard')
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parser.add_argument('--seed', nargs="?", type=int, default=1122017, help='Whether to use tensorboard')
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self.args = parser.parse_args()
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def get_argument_variables(self):
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"""
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Processes the parsed arguments and produces variables of specific types needed for the experiments
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:return: Arguments needed for experiments
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"""
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batch_size = self.args.batch_size
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experiment_prefix = self.args.experiment_prefix
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strided_dim_reduction = True if self.args.strided_dim_reduction == "True" else False
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batch_norm = True if self.args.batch_norm_use == "True" else False
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seed = self.args.seed
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dropout_rate = self.args.dropout_rate
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tensorboard_enable = True if self.args.tensorboard_use == "True" else False
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continue_from_epoch = self.args.continue_epoch # use -1 to start from scratch
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epochs = self.args.epochs
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logs_path = self.args.logs_path
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return batch_size, seed, epochs, logs_path, continue_from_epoch, tensorboard_enable, batch_norm, \
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strided_dim_reduction, experiment_prefix, dropout_rate
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