Run_tf_ner.py error on TPU 
## 🐛 Bug
run_tf_ner.py does not work with TPU. The first error is:
`File system scheme '[local]' not implemented `
When the script is changed and .tfrecord file is moved to gs:// address (and also hardcoded "/tmp/mylogs" is replaced with gs:/// dir)  there is an error with optimiser:
`AttributeError: 'device_map' not accessible within a TPU context.`

## To Reproduce

Steps to reproduce the behaviour:

python run_tf_ner.py.1 --tpu grpc://10.240.1.2:8470 --data_dir gs://nomentech/datadir --labels ./datasets/labels.txt --output_dir gs://nomentech/model1 --max_seq_length 40 --model_type bert --model_name_or_path bert-base-multilingual-cased --do_train --do_eval --cache_dir gs://nomentech/cachedir --num_train_epochs 5 --per_device_train_batch_size 96


## Environment

* OS: Ubuntu 18
* Python version: 3.7
* Tensorflow version: 2.1.0-dev20191222 (tf-nightly)
* PyTorch Transformers version (or branch): 2.3.0
* Distributed of parallel setup ? TPU

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
<|||||>I have the same issue on Colab TPU with tf-nightly 2.2.0. @dlauc did you solve the problem?<|||||>Hi @BOUALILILila, I've switched to the TF/Keras - it works well with TPU-s<|||||>Hi @dlauc. Could you elaborate how you fixed this? I am having the same problem. 