[WIP][Verl] Add entropy loss to cross_entropy_loss and fused_linear_cross_entropy_loss

[hongpeng-guo]

Summary

In RLHF workflows, such as verl, the actor forward function usually generates both losses of cross_entropy_loss (-log_probs) and entropy_loss, the later was used to encourage the policy to be not over-deterministic.

There is a real needs for a kernel that will generates both the two losses, with materializing the huge logits tensor. Liger-kernel's fused_linear_cross_entropy_loss already works well to generate the cross_entropy_loss, but only calculating the second part of the loss, i.e., the entropy loss.

This PR adds the entropy loss option to the existing FLCE loss, and work as one important step to support verl.

1. Adding the entropy calculation in the second pass of online softmax in cross_entropy.py::liger_cross_entropy_kernel, both the loss and its gradient subject to input are calculated and stored;
2. Propagate the changes to relevant modules in fused_linear_cross_entropy.py,
3. Propagate relavent changes to other functional modules in PyTorch interface.

Testing Done

Made existing unit tests working; Adding new unittest WIP.

• Hardware Type:
• run make test to ensure correctness
• run make checkstyle to ensure code style
• run make test-convergence to ensure convergence

[Tcc0403]

Please add a unit test with return_entropy_loss. You can write a new pytorch implementation like CrossEntropyWithZLoss, or return_entropy_loss functionality on top of it.