fix tp get logps

[hjh0119]

No description provided.

[gemini-code-assist]

Summary of Changes

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This pull request addresses an issue with calculating log probabilities (logps) in a tensor-parallel Megatron-LM setup. It extends the list of recognized model weights and introduces specific handling for vocabulary-parallel log softmax, ensuring accurate computations in distributed training environments.

Highlights

• Megatron Model Weights: Added several projection weight names (.in_proj_qkv.weight, .in_proj_z.weight, .in_proj_a.weight, .in_proj_b.weight, .out_proj.weight) to the list of parameters in megatron.py. This likely ensures these weights are correctly handled during model operations, possibly for serialization or metric calculation.
• Vocab Parallel Log Softmax: Modified selective_log_softmax in torch_utils.py to conditionally use _vocab_parallel_selective_log_softmax when Megatron's tensor model parallelism is active. This ensures correct log probability calculation in distributed environments.

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[gemini-code-assist]

Code Review

This pull request introduces a fix for calculating log probabilities in a tensor-parallel setup by leveraging a specialized Megatron function. It also extends LoRA support to additional layer types. The core logic appears correct, but I've suggested an improvement to make the exception handling more specific and robust.