fix(asr): resolve CPU-GPU sync bottleneck in BLEU metric computation

[Sainava]

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What does this PR do ?

Resolves a documented TODO regarding excessive CPU-to-GPU operations by replacing an $O(N)$ sequential metric update loop with an $O(1)$ batched update, eliminating implicit host-to-device synchronizations per sample.

Collection: ASR

Changelog

• Aggregated hypotheses and references into batch lists rather than processing them sample-by-sample.
• Grouped texts by tokenizer type to preserve support for dynamic BLEU_TOKENIZER extraction via check_cuts.
• Replaced the iterative _bleu_score_update calls with a single group-level update, preventing the numerator, denominator, preds_len, and target_len state tensors from forcing sequential CPU-GPU blocking during evaluation.

Usage

• Internal performance optimization. No changes to the public API or user-facing usage are required.

# The BLEU metric is instantiated and used exactly as before, but evaluation throughput is significantly increased, especially at larger batch sizes.

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Additional Information

• Resolves the in-code # TODO: on line 190 of nemo/collections/asr/metrics/bleu.py regarding backend implementation speedups.

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[Sainava]

Hi , I noticed a TODO regarding the CPU-GPU sync bottleneck in the BLEU metric, so I batched the updates to eliminate the sequential host-to-device synchronizations. Please take a look whenever you have a moment!