Incorrectly saved checkpoints when ETP is enabled, replica_id is accidentally overwrites ETP shards when due to missing tp_rank in key

**Describe the bug**

When enabling expert tensor checkpoints, only the first rank of tensor parallelism of experts are saved due to a missing key in the replica_id for the GroupedLinear class

https://github.com/NVIDIA/Megatron-LM/pull/1770 closes this issue.

A clear and concise description of what the bug is.

**Steps/Code to reproduce bug**

* Train with ETP, try to load the checkpoint with high strictness, note the error. Also observe the checkpoints for training a large MOE like deepseek with ETP, they are half the size they should be with TP2, 1/4 with TP4, 1/8 with TP8 etc...

Please list *minimal* steps or code snippet for us to be able to reproduce the bug.

A helpful guide on on how to craft a minimal bug report http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports.

**Expected behavior**

* All weights are saved

A clear and concise description of what you expected to happen.

**Additional context**

Add any other context about the problem here.