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Thank you for the excellent work!
I am very interested in applying your model to a new dataset. In order to further enhance performance, I am attempting to fine-tune the existing large model using the training methods mentioned in your documentation. However, I encountered the following error:
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [8, 64, 266]] is at version 1; expected version 0 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck!
ERROR conda.cli.main_run:execute(124): conda run python /vol/home/xxx/code/scFoundation/RNA_pretraining.py failed. (See above for error)
I have utilized torch.autograd.set_detect_anomaly(True) to help identify the issue, and the error was pinpointed to the operation data_dash = torch.einsum('...id,...jd->...ij', (data_normalizer * data), projection).
Could you please offer some guidance or suggest possible solutions to resolve this error? Any advice would be greatly appreciated.
Thank you for your time and assistance.
The text was updated successfully, but these errors were encountered:
Thank you for the excellent work!
I am very interested in applying your model to a new dataset. In order to further enhance performance, I am attempting to fine-tune the existing large model using the training methods mentioned in your documentation. However, I encountered the following error:
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [8, 64, 266]] is at version 1; expected version 0 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck!
ERROR conda.cli.main_run:execute(124):
conda run python /vol/home/xxx/code/scFoundation/RNA_pretraining.py
failed. (See above for error)I have utilized torch.autograd.set_detect_anomaly(True) to help identify the issue, and the error was pinpointed to the operation data_dash = torch.einsum('...id,...jd->...ij', (data_normalizer * data), projection).
Could you please offer some guidance or suggest possible solutions to resolve this error? Any advice would be greatly appreciated.
Thank you for your time and assistance.
The text was updated successfully, but these errors were encountered: