utils/gluon/score.py [26:47]:
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def parse_args():
    parser = argparse.ArgumentParser(description='Train a model for image classification.')
    parser.add_argument('--data-dir', type=str, default='~/.mxnet/datasets/imagenet',
                        help='training and validation pictures to use.')
    parser.add_argument('--rec-train', type=str, default='~/.mxnet/datasets/imagenet/rec/train.rec',
                        help='the training data')
    parser.add_argument('--rec-train-idx', type=str, default='~/.mxnet/datasets/imagenet/rec/train.idx',
                        help='the index of training data')
    parser.add_argument('--rec-val', type=str, default='~/.mxnet/datasets/imagenet/rec/val.rec',
                        help='the validation data')
    parser.add_argument('--rec-val-idx', type=str, default='~/.mxnet/datasets/imagenet/rec/val.idx',
                        help='the index of validation data')
    parser.add_argument('--use-rec', action='store_true',
                        help='use image record iter for data input. default is false.')
    parser.add_argument('--batch-size', type=int, default=32,
                        help='training batch size per device (CPU/GPU).')
    parser.add_argument('--dtype', type=str, default='float32',
                        help='data type for training. default is float32')
    parser.add_argument('--num-gpus', type=int, default=0,
                        help='number of gpus to use.')
    parser.add_argument('-j', '--num-data-workers', dest='num_workers', default=4, type=int,
                        help='number of preprocessing workers')
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utils/gluon/train_imagenet.py [26:47]:
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def parse_args():
    parser = argparse.ArgumentParser(description='Train a model for image classification.')
    parser.add_argument('--data-dir', type=str, default='~/.mxnet/datasets/imagenet',
                        help='training and validation pictures to use.')
    parser.add_argument('--rec-train', type=str, default='~/.mxnet/datasets/imagenet/rec/train.rec',
                        help='the training data')
    parser.add_argument('--rec-train-idx', type=str, default='~/.mxnet/datasets/imagenet/rec/train.idx',
                        help='the index of training data')
    parser.add_argument('--rec-val', type=str, default='~/.mxnet/datasets/imagenet/rec/val.rec',
                        help='the validation data')
    parser.add_argument('--rec-val-idx', type=str, default='~/.mxnet/datasets/imagenet/rec/val.idx',
                        help='the index of validation data')
    parser.add_argument('--use-rec', action='store_true',
                        help='use image record iter for data input. default is false.')
    parser.add_argument('--batch-size', type=int, default=32,
                        help='training batch size per device (CPU/GPU).')
    parser.add_argument('--dtype', type=str, default='float32',
                        help='data type for training. default is float32')
    parser.add_argument('--num-gpus', type=int, default=0,
                        help='number of gpus to use.')
    parser.add_argument('-j', '--num-data-workers', dest='num_workers', default=4, type=int,
                        help='number of preprocessing workers')
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