implement-simpo-loss-function

name	Implement SimPO Loss Function
description	Use when implementing the `simpo_loss` function in SimPOTrainer class. Extract loss computation logic from the paper and translate it to PyTorch code that accepts the expected tensor inputs.

1. Study the SimPO loss formula in the paper:

   • Read /root/SimPO/paper.pdf to understand the mathematical definition
   • Note the inputs expected (typically: logits for chosen/rejected, reference logits, or similar)
   • Identify any hyperparameters (temperature, beta, etc.)

2. Examine the function signature in SimPOTrainer:

   grep -A 10 "def simpo_loss" /root/SimPO/scripts/simpo_trainer.py
   

3. Check the unit test to understand expected inputs and outputs:

   cat /root/SimPO/unit_test/unit_test_1.py
   

   • Identify input tensor shapes and dtypes
   • Identify expected output shape and key name for .npz file

4. Implement the loss function:

   • Translate the mathematical formula to PyTorch operations
   • Handle batch dimensions correctly
   • Ensure numerical stability (use log-sum-exp tricks if needed)
   • Return losses as a 1D tensor matching batch size

5. Verify implementation:

   • Function accepts all required arguments from the test
   • Returns tensor with shape matching expected output
   • No undefined variables or missing imports