Hi again, sorry for opening so many issues >.< When I try

Will do :) Old error is fixed, new one is this 😄: <div class="snippet-clipboa

Can you try pulling from <a href="https://github.com/sarthakpati/GaNDLF/tree/refactor"

You can try to reproduce the error from my fork: <a href="https://github.com/Karol-G/G

IndexError: list index out of range about gandlf HOT 7 CLOSED

mlcommons commented on August 25, 2024

IndexError: list index out of range

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Karol-G commented on August 25, 2024 1

Yes! It is working now 😁 Thanks!

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sarthakpati commented on August 25, 2024

No worries at all, this helps us with stress testing, so thank you! 😄

This could be due to the resampling. Could you try the following:

data_preprocessing:
  {
    # 'normalize',
    'normalize_nonZero', # this performs z-score normalization only on non-zero pixels
  }

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sarthakpati commented on August 25, 2024

I will also recommend to keep the configuration as light as possible for the toy examples (basically, let the defaults ride). Essentially, the configs in the testing module should be your starting point. 😄 🚀

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Karol-G commented on August 25, 2024

Will do :)
Old error is fixed, new one is this 😄:

This option has been superceded by 'model'
Number of channels :  3
Channel Keys :  ['subject_id', '1', '2', '3', 'label', 'path_to_metadata', 'value_0']



Initializing training at :  2021-03-28 13:12:04.708672
Found a pre-existing file for logging, now appending logs to that file!
Found a pre-existing file for logging, now appending logs to that file!
Device requested via CUDA_VISIBLE_DEVICES:  0
Total number of CUDA devices:  1
Device finally used:  0
Sending model to aforementioned device
Memory Total :  14.8 GB, Allocated:  0.1 GB, Cached:  0.1 GB
Device - Current: 0 Count: 1 Name: Tesla T4 Availability: True
Using device: cuda
********************
Starting Epoch :  0
Epoch start time :  2021-03-28 13:12:07.872670
/usr/local/lib/python3.7/dist-packages/torch/nn/modules/loss.py:528: UserWarning: Using a target size (torch.Size([1, 1])) that is different to the input size (torch.Size([1, 2])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.
  return F.mse_loss(input, target, reduction=self.reduction)
Epoch Average Train loss :  tensor(1.6588, device='cuda:0', grad_fn=<DivBackward0>)
Epoch Average Train mse :  tensor(1.6588, device='cuda:0', grad_fn=<DivBackward0>)
Epoch Average Train loss :  tensor(0.9822, device='cuda:0', grad_fn=<DivBackward0>)
Epoch Average Train mse :  tensor(0.9822, device='cuda:0', grad_fn=<DivBackward0>)
********************
Starting validation : 
********************
Traceback (most recent call last):
  File "gandlf_run", line 75, in <module>
    main()
  File "gandlf_run", line 70, in main
    TrainingManager(dataframe=data_full, headers = headers, outputDir=model_path, parameters=parameters, device=device, reset_prev = reset_prev)
  File "/content/GaNDLF-refactor/GANDLF/training_manager.py", line 146, in TrainingManager
    device=device, params=parameters, testing_data=testingData)
  File "/content/GaNDLF-refactor/GANDLF/training_loop.py", line 480, in training_loop
    model, val_dataloader, params
  File "/content/GaNDLF-refactor/GANDLF/training_loop.py", line 269, in validate_network
    output_prediction += output.cpu().data.item()# this probably needs customization for classification (majority voting or median, perhaps?)
ValueError: only one element tensors can be converted to Python scalars

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sarthakpati commented on August 25, 2024

Can you try pulling from my branch now and re-try?

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Karol-G commented on August 25, 2024

Sorry for replying so late! Was busy the last few days.
Sadly the error is still the same with the new refactor pull.

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Karol-G commented on August 25, 2024

You can try to reproduce the error from my fork: https://github.com/Karol-G/GaNDLF/tree/refactor
I added the experiment model.yaml, train.csv and the toy dataset.

You should be able to reproduce the error with the following command:
gandalf_run -config ./my_experiments/2d_classification/model_simple.yaml -data ./my_experiments/2d_classification/train.csv -output ./my_experiments/2d_classification/output_dir/ -train 1 -device -1 -reset_prev True

When debugging, I noticed that the model output is of size [1,2,1] which cannot be converted to a scalar with .item().

There is a comment there that "this probably needs customization for classification (majority voting or median, perhaps?)", so I guess that is probably the solution 😄

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IndexError: list index out of range about gandlf HOT 7 CLOSED

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