83 lines
4.3 KiB
Python
83 lines
4.3 KiB
Python
# BSD 2-Clause License
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#
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# Copyright (c) 2021, Pl@ntNet
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# 1. Redistributions of source code must retain the above copyright notice, this
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# list of conditions and the following disclaimer.
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#
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# 2. Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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import torch
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def add_all_parsers(parser):
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_add_loss_parser(parser)
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_add_training_parser(parser)
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_add_model_parser(parser)
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_add_hardware_parser(parser)
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_add_misc_parser(parser)
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def _add_loss_parser(parser):
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group_loss = parser.add_argument_group('Loss parameters')
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group_loss.add_argument('--mu', type=float, default=0.0001, help='weight decay parameter')
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def _add_training_parser(parser):
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group_training = parser.add_argument_group('Training parameters')
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group_training.add_argument('--lr', type=float, help='learning rate to use')
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group_training.add_argument('--batch_size', type=int, default=32, help='default is 32')
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group_training.add_argument('--n_epochs', type=int)
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group_training.add_argument('--pretrained', action='store_true')
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group_training.add_argument('--image_size', type=int, default=256)
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group_training.add_argument('--crop_size', type=int, default=224)
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group_training.add_argument('--epoch_decay', nargs='+', type=int, default=[])
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group_training.add_argument('--k', nargs='+', help='value of k for computing the topk loss and computing topk accuracy',
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required=True, type=int)
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def _add_model_parser(parser):
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group_model = parser.add_argument_group('Model parameters')
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group_model.add_argument('--model', choices=['resnet18', 'resnet34', 'resnet50', 'resnet101', 'resnet152',
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'densenet121', 'densenet161', 'densenet169', 'densenet201',
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'mobilenet_v2', 'inception_v3', 'alexnet', 'squeezenet',
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'shufflenet', 'wide_resnet50_2', 'wide_resnet101_2',
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'vgg11', 'mobilenet_v3_large', 'mobilenet_v3_small',
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'inception_resnet_v2', 'inception_v4', 'efficientnet_b0',
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'efficientnet_b1', 'efficientnet_b2', 'efficientnet_b3',
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'efficientnet_b4', 'vit_base_patch16_224'],
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default='resnet50', help='choose the model you want to train on')
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def _add_hardware_parser(parser):
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group_hardware = parser.add_argument_group('Hardware parameters')
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group_hardware.add_argument('--use_gpu', type=int, choices=[0, 1], default=torch.cuda.is_available())
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def _add_misc_parser(parser):
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group_misc = parser.add_argument_group('Miscellaneous parameters')
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group_misc.add_argument('--seed', type=int, help='set the seed for reproductible experiments')
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group_misc.add_argument('--num_workers', type=int, default=4,
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help='number of workers for the data loader. Default is one. You can bring it up. '
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'If you have memory errors go back to one')
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group_misc.add_argument('--root', help='location of the train val and test directories')
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group_misc.add_argument('--save_name_xp', help='name of the saving file')
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