Fix GreedyBatchedCTCInfer regression from GreedyCTCInfer.
~Fix not going to r2.0.0rc0?~

# What does this PR do ?

decoder_lengths is allowed to be on CPU even when decoder_output is on GPU. This matches the behavior of GreedyCTCInfer. Even though that behavior is unintentional, there is code depending on that behavior, including our jupyter notebooks.

# Testing

I tested in the following way. I ran:

```
pytest -k test_batched_decoding_ tests/collections/asr/decoding/test_ctc_decoding.py
CUDA_VISIBLE_DEVICES="" pytest -k test_batched_decoding_ tests/collections/asr/decoding/test_ctc_decoding.py
```

CUDA_VISIBLE_DEVICES="" ensures that the test runs when on CPU-only machines, as well as on machines with GPU. My previous PR related to this failed to test on GPU, which caused the crash we see today when we run with lengths on CPU but logprobs on GPU.

I also manually ran examples/notebooks/asr/ASR_with_Subword_Tokenization.ipynb and examples/notebooks/asr/ASR_with_NeMo.ipynb manually. These run to completion. I had to comment out the part that install NeMo from pypi, which would overwrite my local installation.

**Collection**: ASR

**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.

## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to NVBug 4647443 and 4647231
