image_classification/infer_imagenet.py [27:71]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 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') parser.add_argument('--num-epochs', type=int, default=3, help='number of training epochs.') parser.add_argument('--lr', type=float, default=0.1, help='learning rate. default is 0.1.') parser.add_argument('--momentum', type=float, default=0.9, help='momentum value for optimizer, default is 0.9.') parser.add_argument('--wd', type=float, default=0.0001, help='weight decay rate. default is 0.0001.') parser.add_argument('--lr-mode', type=str, default='step', help='learning rate scheduler mode. options are step, poly.') parser.add_argument('--lr-poly-power', type=int, default=2, help='if learning rate scheduler mode is poly, then power is used') parser.add_argument('--lr-decay', type=float, default=0.1, help='decay rate of learning rate. default is 0.1.') parser.add_argument('--lr-decay-epoch', type=str, default='40,60', help='epoches at which learning rate decays. default is 40,60.') parser.add_argument('--warmup-lr', type=float, default=0.0, help='starting warmup learning rate. default is 0.0.') parser.add_argument('--warmup-epochs', type=int, default=0, help='number of warmup epochs.') parser.add_argument('--last-gamma', action='store_true', help='whether to initialize the gamma of the last BN layer in each bottleneck to zero') parser.add_argument('--mode', type=str, help='mode in which to train the model. options are symbolic, imperative, hybrid') parser.add_argument('--model', type=str, required=True, help='type of model to use. see vision_model for options.') parser.add_argument('--use-pretrained', action='store_true', help='enable using pretrained model from gluon.') parser.add_argument('--use_se', action='store_true', help='use SE layers or not in resnext. default is false.') parser.add_argument('--batch-norm', action='store_true', help='enable batch normalization or not in vgg. default is false.') parser.add_argument('--log-interval', type=int, default=50, help='Number of batches to wait before logging.') parser.add_argument('--save-frequency', type=int, default=0, help='frequency of model saving.') parser.add_argument('--save-dir', type=str, default='params', help='directory of saved models') parser.add_argument('--logging-dir', type=str, default='logs', help='directory of training logs') parser.add_argument('--kvstore', type=str, default='nccl') parser.add_argument('--top-k', type=int, default=0, help='give 5 for top5 accuracy, if 0 only prints top1 accuracy') - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - image_classification/infer_imagenet_gpu.py [30:74]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 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') parser.add_argument('--num-epochs', type=int, default=3, help='number of training epochs.') parser.add_argument('--lr', type=float, default=0.1, help='learning rate. default is 0.1.') parser.add_argument('--momentum', type=float, default=0.9, help='momentum value for optimizer, default is 0.9.') parser.add_argument('--wd', type=float, default=0.0001, help='weight decay rate. default is 0.0001.') parser.add_argument('--lr-mode', type=str, default='step', help='learning rate scheduler mode. options are step, poly.') parser.add_argument('--lr-poly-power', type=int, default=2, help='if learning rate scheduler mode is poly, then power is used') parser.add_argument('--lr-decay', type=float, default=0.1, help='decay rate of learning rate. default is 0.1.') parser.add_argument('--lr-decay-epoch', type=str, default='40,60', help='epoches at which learning rate decays. default is 40,60.') parser.add_argument('--warmup-lr', type=float, default=0.0, help='starting warmup learning rate. default is 0.0.') parser.add_argument('--warmup-epochs', type=int, default=0, help='number of warmup epochs.') parser.add_argument('--last-gamma', action='store_true', help='whether to initialize the gamma of the last BN layer in each bottleneck to zero') parser.add_argument('--mode', type=str, help='mode in which to train the model. options are symbolic, imperative, hybrid') parser.add_argument('--model', type=str, required=True, help='type of model to use. see vision_model for options.') parser.add_argument('--use-pretrained', action='store_true', help='enable using pretrained model from gluon.') parser.add_argument('--use_se', action='store_true', help='use SE layers or not in resnext. default is false.') parser.add_argument('--batch-norm', action='store_true', help='enable batch normalization or not in vgg. default is false.') parser.add_argument('--log-interval', type=int, default=50, help='Number of batches to wait before logging.') parser.add_argument('--save-frequency', type=int, default=0, help='frequency of model saving.') parser.add_argument('--save-dir', type=str, default='params', help='directory of saved models') parser.add_argument('--logging-dir', type=str, default='logs', help='directory of training logs') parser.add_argument('--kvstore', type=str, default='nccl') parser.add_argument('--top-k', type=int, default=0, help='give 5 for top5 accuracy, if 0 only prints top1 accuracy') - 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