Use Label-Looping algorithm for RNN-T decoding by default
Not ready yet jenkins > Late review with a few FYI comments. Do we test the cuda graphs implementation with stateless transducers yet?

Thanks for the comments, @galv! I will make fixes in next PRs. 
Cuda graphs implementation with stateless prediction network is not tested on CI for now (no production model), but I tested loop labels + cuda graphs locally with a custom model, and it works.

# What does this PR do ?

Enable Label-Looping algorithm introduced in #8286 and #7926 (`loop_labels=True`) by default for RNN-T greedy decoding.

**Collection**: [ASR]

# Changelog 
- Enable Label-Looping algorithm by default (`loop_labels=true`)
- fix Label Looping algorithm for RNN-T/TDT + Stateless network
- fix tests with custom RNNT Decoder
- parametrize tests for batched greedy decoding to test both algorithms (Frame-/Label-Looping)

# Usage

Label-Looping algorithm is used by default now for batched greedy decoding.

For Frame-Looping algorithm one can use:
```shell
python examples/asr/speech_to_text_eval.py  <...> \
 rnnt_decoding.greedy.loop_labels=false
```

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