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Extend the BertForSequenceClassification docs to mention the special CLS token.

Fix tsv read error in Windows

Added a helpful error for users with single-document corpuses - fixes # 452

error for users whose corpus is just one giant document.

fix run_gpt2.py

Update README.md

Fix for

```> > > > 04/09/2019 21:39:38 - INFO - __main__ -   device: cuda n_gpu: 1, distributed training: False, 16-bits training: False
Traceback (most recent call last):
  File "/home/ubuntu/pytorch-pretrained-BERT/examples/lm_finetuning/simple_lm_finetuning.py", line 642, in <module>
    main()
  File "/home/ubuntu/pytorch-pretrained-BERT/examples/lm_finetuning/simple_lm_finetuning.py", line 502, in main
    raise ValueError("Training is currently the only implemented execution option. Please set `do_train`.")
ValueError: Training is currently the only implemented execution option. Please set `do_train`.
```

```while not args.unconditional:
   if not args.unconditional:
```
These lines have been updated

Fix Language Modeling Loss

fix sample_doc

Fix cosine schedule

Fix links in README

Fix typo in example code

Fixes to the TensorFlow conversion tool

Modify 'unambigiously' to 'unambiguously'

If the value of rand_end is returned from the randint function, the value of sampled_doc_index that matches current_idx is returned from searchsorted.

example:
cumsum_max = {int64} 30
doc_cumsum = {ndarray} [ 5  7 11 19 30]
doc_lengths = {list} <class 'list'>: [5, 2, 4, 8, 11]
if current_idx  = 1,
rand_start = 7
rand_end = 35
sentence_index = randint(7, 35) % cumsum_max
if randint return 35, sentence_index becomes 5.
if sentence_index is 5, np.searchsorted returns 1 equal to current_index.

Merge remote-tracking branch 'upstream/master'

fix lm_finetuning's link

The unconditional generation works now but if the seed is fixed, the sample is the same every time.
n_samples > 1 will give different samples though.
I am giving the start token as '<|endoftext|>' for the unconditional generation.

Added remaining GLUE tasks to 'run_classifier.py'

Remove padding_idx from position_embeddings and token_type_embeddings