Getting `TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.`
I am getting `TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.` when transcribing using a transducer model by setting `return_hypotheses=True` and `compute_timestamps=True` in decoding config. If I remove `compute_timestamps=True`, I don't get this error but the char and word level timestamp information won't be included.

**Steps/Code to reproduce bug**

```python
config = nemo_asr.models.ASRModel.restore_from(model_path, return_config=True)
decoding_config = config.decoding

decoding_config.strategy = "greedy_batch"

with open_dict(decoding_config):
    decoding_config.preserve_alignments = True
    decoding_config.fused_batch_size = -1  # temporarily stop fused batch during inference.
    decoding_config.compute_timestamps = True

model.change_decoding_strategy(decoding_config)

hypothesis = model.transcribe(audio=sample_audio, batch_size=1, return_hypotheses=True)[0][0]
```

**Error**
```bash
File [~/NeMo/nemo/collections/asr/parts/submodules/rnnt_decoding.py:851], in AbstractRNNTDecoding._compute_offsets(hypothesis, token_repetitions, rnnt_token)
    849 # Construct the start and end indices brackets
    850 end_indices = np.asarray(token_repetitions).cumsum()
--> 851 start_indices = np.concatenate(([start_index], end_indices[:-1]))
.
.
.
File [~/miniconda3/envs/base/lib/python3.11/site-packages/torch/_tensor.py:1062], in Tensor.__array__(self, dtype)
   1060     return handle_torch_function(Tensor.__array__, (self,), self, dtype=dtype)
   1061 if dtype is None:
-> 1062     return self.numpy()
   1063 else:
   1064     return self.numpy().astype(dtype, copy=False)

TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.
```

**Environment overview (please complete the following information)**

 - Environment location: AWS
 - Method of NeMo install: from source

**Environment details**
- OS version: Ubuntu 22.04
- PyTorch version: 2.2.1
- Python version: 3.11
