Fix `load_balancing_loss_func` incompatible with `past_key_values`
Author: tkj666
Pull request: yes
Labels: name: Feature request


# What does this PR do?

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Changes the way `num_hidden_layers`, `batch_size` and `sequence_length` are calculated, and slices `attention_mask`, so that the shapes of `expert_attention_mask` and `expert_mask` match, thus making it compatible with inference with `past_key_values`
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Fixes #30731


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Comments:
**[For maintainers]** Suggested jobs to run (before merge)

run-slow: ernie4_5_moe, gpt_oss, minimax, mixtral, qwen3_moe, qwen3_next

> hey, sorry what's the motivation? Load balancing loss function is for training 😓

Multiple models that support `output_router_logits` would call `load_balancing_loss_func` if `output_router_logits == True` without checking whether it's training or not, e.g. https://github.com/huggingface/transformers/blob/32567739740da86ddf96c60a23cf2d0494ce4145/src/transformers/models/qwen3_moe/modular_qwen3_moe.py#L255C2-L262C5 and https://github.com/tkj666/transformers/blob/f8bdbaf5e3b907258e2154ea16797c057090430c/src/transformers/models/mixtral/modular_mixtral.py#L430C9-L436C14 

During inference, people may want to check the router logits, and currently due to the imcompatible shape of `attention_mask` and `all_router_logits` when `past_key_values` is enabled, it will raise an error. Since `aux_loss` does not depend on labels, it is also possible to check `aux_loss` in inference.