/gpfs/projects/LynchGroup/spacewhale/git_spacewhale/spacewhale/shell_scripts
/gpfs/projects/LynchGroup/spacewhale
Sat May  4 13:59:35 EDT 2019
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WELCOME TO SPACEWHALE!
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We will now train your model.. please be patient
Using resneXt Your trained model will be named resnext_test32
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<torch.utils.data.dataloader.DataLoader object at 0x2aaafcaebba8>
Your dataset size is: 12545
You have 2 classes in your dataset
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Labels for the dataset are:
water = 0
whale = 1
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Data loaded into gpu
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/gpfs/projects/LynchGroup/spacewhale/git_spacewhale/spacewhale
Epoch 0/23
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Traceback (most recent call last):
  File "training_tester_weighted.py", line 130, in <module>
    model_ft = s.train_model(opt, device, dataset_sizes, dataloaders, model_ft, criterion, optimizer_ft, exp_lr_scheduler, num_epochs=opt.epochs)
  File "/gpfs/projects/LynchGroup/spacewhale/git_spacewhale/spacewhale/m_util.py", line 120, in train_model
    outputs = model(inputs)
  File "/gpfs/projects/LynchGroup/spacewhale/space_env/lib/python3.7/site-packages/torch/nn/modules/module.py", line 477, in __call__
    result = self.forward(*input, **kwargs)
  File "/gpfs/projects/LynchGroup/spacewhale/space_env/lib/python3.7/site-packages/torch/nn/modules/container.py", line 91, in forward
    input = module(input)
  File "/gpfs/projects/LynchGroup/spacewhale/space_env/lib/python3.7/site-packages/torch/nn/modules/module.py", line 477, in __call__
    result = self.forward(*input, **kwargs)
  File "/gpfs/projects/LynchGroup/spacewhale/space_env/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 301, in forward
    self.padding, self.dilation, self.groups)
RuntimeError: sizes must be non-negative
Sat May  4 13:59:43 EDT 2019
