Fixes an issue in text-classification where MNLI eval/test datasets are not being preprocessed.

[allenwang28]

What does this PR do?

In dfd16af for run_glue.py, {train|eval|test}_dataset was split out and preprocessed individually. However, this misses datasets["{validation|test}_mismatched"] which is appended to the {eval|test}_dataset only when MNLI is used.

When running evaluation on MNLI, that means we eventually hit an un-preprocessed dataset which leads to a stack trace like this:

Traceback (most recent call last):
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 329, in _mp_start_fn
    _start_fn(index, pf_cfg, fn, args)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 323, in _start_fn
    fn(gindex, *args)
  File "/transformers/examples/text-classification/run_glue.py", line 532, in _mp_fn
    main()
  File "/transformers/examples/text-classification/run_glue.py", line 493, in main
    metrics = trainer.evaluate(eval_dataset=eval_dataset)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/transformers/trainer.py", line 1657, in evaluate
    metric_key_prefix=metric_key_prefix,
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/transformers/trainer.py", line 1788, in prediction_loop
    loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/transformers/trainer.py", line 1899, in prediction_step
    loss, outputs = self.compute_loss(model, inputs, return_outputs=True)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/transformers/trainer.py", line 1458, in compute_loss
    outputs = model(**inputs)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/nn/modules/module.py", line 1015, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 625, in forward
    return_dict=return_dict,
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/nn/modules/module.py", line 1015, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 471, in forward
    raise ValueError("You have to specify either input_ids or inputs_embeds")
ValueError: You have to specify either input_ids or inputs_embeds

This commit resolves this by moving the dataset.map(preprocess...) to the beginning.

Fixes # 10620

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[sgugger]

Thanks for fixing!