same survival probabilities from predict_surv_df

Hi Havard. I am facing a problem for a long time that I can not understand what could be the reason of problem. I used images as inputs to a net that is a kind of Encoder and connect it to fully connected layers. I get good training loss but when it comes to predict_surv_df I can understand for different patients I get same survival probabilities. It is really strange for me. For example I trained a model that I got 0.45 train loss but I got same survival times and same curves for different patients but when I saw your example I could understand you get very good c-index and curves with 1.6 train loss. I have to add before training model completely and for example just with 2 epochs I get different probabilities and different survival times. This problem made me crazy and I can not understand what is the problem.

Start with the predict_surv_df entry point and reproduce the report using the image-input model described in the issue. Compare predictions for different patients before and after training, recording the training setup and outputs. Done requires identifying a reproducible cause or a documented explanation; the issue currently names no files, tests, or minimal example.

Written by the indexing model from the issue text.