TF version of the trainer (#4017)

* First commit to add a TF version of the trainer.

* Make the TF trainer closer to what looks the PT trainer

* Refactoring common code between the PT and TF trainer into an util file.

* Some bugfix + better similarity with the PT trainer

* Add missing class in transformers init

* Bugfix over prediction + use classification report instead of simple metrics

* Fix name error

* Fix optimization tests + style

* Apply style

* Several bugfix for multi-gpu training

* Apply style

* Apply style

* Add glue example for the TF trainer

* Several bugix + address the reviews

* Fix on the TF training args file

* Add a debug mode

* Bugfix in utils_ner.py when segment_ids is None

* Apply style

* Apply style

* Add TPU strategy

* Fix selection strategy

src/transformers/__init__.py

@@ -145,7 +145,9 @@ from .tokenization_utils import PreTrainedTokenizer
 from .tokenization_xlm import XLMTokenizer
 from .tokenization_xlm_roberta import XLMRobertaTokenizer
 from .tokenization_xlnet import SPIECE_UNDERLINE, XLNetTokenizer
+from .trainer_utils import EvalPrediction
 from .training_args import TrainingArguments
+from .training_args_tf import TFTrainingArguments
 
 
 logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
@@ -502,6 +504,9 @@ if is_tf_available():
     # Optimization
     from .optimization_tf import WarmUp, create_optimizer, AdamWeightDecay, GradientAccumulator
 
+    # Trainer
+    from .trainer_tf import TFTrainer
+
 
 if not is_tf_available() and not is_torch_available():
     logger.warning(