CUDA runtime error during benchmarking
Author: serkansulun
Pull request: no
Labels: name: wontfix

Running `transformers/examples/benchmarking/run_benchmark.py` with any type of model, with multi-processing gives the following error:

```
1 / 1
THCudaCheck FAIL file=/opt/conda/conda-bld/pytorch_1565272271120/work/aten/src/THC/THCGeneral.cpp line=54 error=3 : initialization error
cuda runtime error (3) : initialization error at /opt/conda/conda-bld/pytorch_1565272271120/work/aten/src/THC/THCGeneral.cpp:54
cuda runtime error (3) : initialization error at /opt/conda/conda-bld/pytorch_1565272271120/work/aten/src/THC/THCGeneral.cpp:54
Traceback (most recent call last):
  File "run_benchmark.py", line 47, in <module>
    main()
  File "run_benchmark.py", line 43, in main
    benchmark.run()
  File "/home/dock/.conda/envs/torch/lib/python3.7/site-packages/transformers/benchmark/benchmark_utils.py", line 709, in run
    memory, inference_summary = self.inference_memory(model_name, batch_size, sequence_length)
ValueError: too many values to unpack (expected 2)
```
It looks like `self.inference_memory` function is returning the string `N/A`. Everything works fine when `no_multi_processing` option is selected.

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 4.1.1
- Platform: Ubuntu 18.04.1 LTS
- Python version: 3.7.9
- PyTorch version (GPU?): 1.2.0 with GPU support
- Tensorflow version (GPU?): None
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: I guess so

### Who can help
@patrickvonplaten
<!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
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 albert, bert, GPT2, XLM: @LysandreJik 
 tokenizers: @mfuntowicz
 Trainer: @sgugger
 Speed and Memory Benchmarks: @patrickvonplaten
 Model Cards: @julien-c
 TextGeneration: @TevenLeScao 
 examples/distillation: @VictorSanh
 nlp datasets: [different repo](https://github.com/huggingface/nlp)
 rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)
 Text Generation: @patrickvonplaten @TevenLeScao
 Blenderbot: @patrickvonplaten
 Bart: @patrickvonplaten
 Marian: @patrickvonplaten
 Pegasus: @patrickvonplaten
 mBART: @patrickvonplaten
 T5: @patrickvonplaten
 Longformer/Reformer: @patrickvonplaten
 TransfoXL/XLNet: @TevenLeScao
 RAG: @patrickvonplaten, @lhoestq
 FSMT: @stas00
 examples/seq2seq: @patil-suraj
 examples/bert-loses-patience: @JetRunner
 tensorflow: @jplu
 examples/token-classification: @stefan-it
 documentation: @sgugger
 -->

## Information

Model I am using (Bert, XLNet ...): GPT2, DistilGPT2

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)



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