Question: I ' m working with the torchsurv library to implement a Convolutional Neural Network ( CNN ) for survival analysis, and I need assistance with

I'm working with the torchsurv library to implement a Convolutional Neural Network (CNN) for survival analysis, and I need assistance with calculating the C-index. I have already split my data into two scenarios: train-test and train-validation-test. My main challenges are:
C-Index Calculation:
How do I calculate the C-index for a CNN model in torchsurv when using a train-test split?
What adjustments are needed in the code to calculate the C-index when using a train-validation-test split?
Model Evaluation:
How should I structure my CNN model in torchsurv to ensure accurate C-index calculation?
What is the correct way to use torch.no_grad during evaluation to compute the C-index without affecting the model's gradients?
Any detailed guidance or example code snippets for these scenarios would be greatly appreciated. Thank you!

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