t5 remove data dependency
# What does this PR do?

Prevents clamping logic from being skipped by torch.onnx tracer by moving data-dependent inf check into fp16-specific training code. Unclamped inf results in NaN being returned during loss calculation and eventually will crash with the following error:

```bash
Traceback (most recent call last):
  File "/home/prathikrao/optimum/examples/onnxruntime/training/translation/run_translation.py", line 680, in <module>
    main()
  File "/home/prathikrao/optimum/examples/onnxruntime/training/translation/run_translation.py", line 588, in main
    train_result = trainer.train(resume_from_checkpoint=checkpoint)
  File "/opt/conda/envs/ptca/lib/python3.8/site-packages/optimum/onnxruntime/trainer.py", line 373, in train
    return inner_training_loop(
  File "/opt/conda/envs/ptca/lib/python3.8/site-packages/optimum/onnxruntime/trainer.py", line 658, in _inner_training_loop
    self.deepspeed.step()
  File "/opt/conda/envs/ptca/lib/python3.8/site-packages/deepspeed/runtime/engine.py", line 2169, in step
    self._take_model_step(lr_kwargs)
  File "/opt/conda/envs/ptca/lib/python3.8/site-packages/deepspeed/runtime/engine.py", line 2071, in _take_model_step
    self.optimizer.step()
  File "/opt/conda/envs/ptca/lib/python3.8/site-packages/deepspeed/runtime/zero/stage_1_and_2.py", line 1759, in step
    self._update_scale(self.overflow)
  File "/opt/conda/envs/ptca/lib/python3.8/site-packages/deepspeed/runtime/zero/stage_1_and_2.py", line 2016, in _update_scale
    self.loss_scaler.update_scale(has_overflow)
  File "/opt/conda/envs/ptca/lib/python3.8/site-packages/deepspeed/runtime/fp16/loss_scaler.py", line 156, in update_scale
    raise Exception(
Exception: Current loss scale already at minimum - cannot decrease scale anymore. Exiting run.
```

## Who can review?

Models:
- text models: @ArthurZucker and @younesbelkada
_The documentation is not available anymore as the PR was closed or merged._<|||||>Cool! Thanks for this contribution! Pretty sure that this can also be applied to `SwitchTransformers` (as it implements the similar procedure) and ~`MT5`~ LongT5<|||||>Let's maybe address this in a follow up PR no? Btw this PR includes the changes for `mt5` (EDIT: you meant `LongT5`)<|||||>@prathikr Would you mind changing the two other models in this PR or would you prefer we followup in a separate PR?<|||||>@sgugger I think a separate PR would be best. Thank you