Set syncfree AdamW as the default optimizer for xla:gpu device in amp mode
This PR sets the syncfree AdamW ([#3294](https://github.com/pytorch/xla/pull/3294)) as the default optimizer for xla:gpu device in amp mode. The syncfree AdamW optimizer shows 20%+ throughput speedup in the run_mlm test case.

Tested with the following script:
```sh
GPU_NUM_DEVICES=1 python run_mlm.py \
    --model_name_or_path bert-base-uncased \
    --dataset_name wikitext \
    --dataset_config_name wikitext-2-raw-v1 \
    --overwrite_output_dir true \
    --output_dir /tmp/test-mlm \
    --per_device_train_batch_size 12 \
    --do_eval \
    --fp16 true \
    --do_train \
    --num_train_epochs 10
```
With normal AdamW:
```sh
***** train metrics *****
  epoch                    =       10.0
  train_loss               =     1.6235
  train_runtime            = 0:19:13.85
  train_samples            =       4627
  train_samples_per_second =       40.1
  train_steps_per_second   =      3.345
```
With syncfree AdamW:
```sh
***** train metrics *****
  epoch                    =       10.0
  train_loss               =     1.6166
  train_runtime            = 0:16:14.05
  train_samples            =       4627
  train_samples_per_second =     47.502
  train_steps_per_second   =      3.963
```

cc @sgugger
_The documentation is not available anymore as the PR was closed or merged._<|||||>Thanks a lot for your PR! I think it would be better to be less magical and offer the option of using this optimizer through a new choice (for instance named adamw_syncfree) in the `--optim` parameter instead of changing the default.

We did not even dare change the default from our implementation to the PyTorch ones for fear of braking changes :-)<|||||>@sgugger I added `adamw_torch_xla` as an optimizer option.