fix(megatron-fsdp): reduce padding for grouped expert weights

[xuwchen]

• I, the PR author, have personally reviewed every line of this PR.

What does this PR do ?

MFSDP computes a chunk size factor (CSF) for each bucket as shape[1:].numel(), which flattens all dimensions except the first one.

For per-expert 2D expert weights:

• linear_fc1: (2 * moe_ffn_hidden_size, hidden_size)
• linear_fc2: (hidden_size, moe_ffn_hidden_size)

shape[1:].numel() is just the last dimension, so the CSF stays small.

For grouped 3D expert weights:

• linear_fc1: (num_local_experts, 2 * moe_ffn_hidden_size, hidden_size)
• linear_fc2: (num_local_experts, hidden_size, moe_ffn_hidden_size)

shape[1:].numel() becomes the full per-expert matrix size. This can make the CSF much larger than the equivalent per-expert 2D layout. When multiple expert weights share a bucket, MFSDP uses divisibility/LCM logic to choose a common CSF. The oversized CSF can force the bucket size to be padded to a much larger alignment unit, increasing AllGather traffic. In the reported configuration this matched the observed ~33% communication increase, corresponding to ~25% bucket padding.

This PR routes grouped expert weights with heterogeneous CSFs into separate buckets via a new _should_split_from_grouped_expert_bucket helper, while keeping the 2D / non-expert paths unchanged.

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[wujingyue]

I left my comments on #4980, a merge request to dev. Next time, I'll comment on only merge-to-main PRs.