KV-cache for T5 model
# What does this PR do?
Improve the T5 generation related issues and T5 attention mask bugs. This PR should be used with https://github.com/NVIDIA/Megatron-LM/pull/1358

**Collection**: nlp T5

# Changelog 
- Add kv-cache mechanism for Megatron-core T5 model.
- Fix the attention mask bugs for Megatron-core local implementations (when mcore_t5 is true, and transformer_engine is False)
- Improve the generation of T5 to be better aligned with that in GPT

# Usage
* Implement kv-cache in generation of T5, improving its efficiency
* Fix local mcore t5 model attention mask bugs (not from transformer_engine)
* In original T5 decode method, you can only generate fix length sequence, even when the EOS token is generated, it will still generate tokens until the predefined number of tokens are reached, which is very inconvenience and inefficient. This pull request raise enables variable length generation.

```python
python examples/nlp/language_modeling/tuning/megatron_gpt_finetuning.py <datasets and checkpoints override>
```

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# Additional Information
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