Add tensor parallelism related mappings
Discussed in https://github.com/huggingface/transformers/issues/13690

In addition, I also created some helper functions. 
cc @RezaYazdaniAminabadi @lucasleesw 

## Reviewers
@stas00 @jaketae @siddk
_The documentation is not available anymore as the PR was closed or merged._<|||||>In my opinion, this mapping + module replacement is the easiest and the most extensible way to implement tensor parallelism now. That's why we need this mapping. However, I've found there were three models (ProphetNet, BigBird, SqueezeBert) that could not be applied in this way. see: https://github.com/tunib-ai/parallelformers/blob/main/FAQ.md#q-why-are-some-models-not-supported

The documentation also points out EncoderDecoderModel and RAG, but this is because it does not match the implementation of parallelformers. It has nothing to do with these mappings.<|||||>I think it's perfectly fine to design a way to automate most of the derivations if it works in most cases and leave the special cases to be that - special cases. Which can be taken care of later.

If you have ever used Perl, its motto: "make the easy things easy, and the hard things possible" and it lived up to that lofty goal. So if we can follow a similar principal here, then it'd be great! 

that's is let's not replicate data that doesn't need to be replicated if it can be derived automatically, and make it possible to overcome exceptions by providing additional data when it can't be auto-derived.

Does it make sense?<|||||>@stas00 Yes. That will be fine. Let's proceed by adding mappings for exception cases. For example, most models match well, but if a few models have exceptions, it is easiest to solve the problem by constructing an additional dictionary for only those exception cases. 

The `REVERSED PARAMS` and `FUSED ATTENTION` maps I wrote are examples. These cases are not difficult to define because there are only two of them across the transformers. @lucasleesw So, let's design it to support as many models as possible with as little effort as possible. That would be the best. <|||||>```python
ValueError: The following files have docstrings written in rst:
- src/transformers/utils/tensor_parallel_utils.py
To fix this run `doc-builder convert path_to_py_file` after installing `doc-builder`
(`pip install git+https://github.com/huggingface/doc-builder`)
make: *** [Makefile:40: repo-consistency] Error 1
```

@stas00 @jaketae @siddk Can you help me? I think it's about documentation.


```python
 hyunwoongko  ~/Github/transformers   master ±  doc-builder convert path_to_py_file
Traceback (most recent call last):
  File "/Library/Frameworks/Python.framework/Versions/3.7/bin/doc-builder", line 8, in <module>
    sys.exit(main())
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/doc_builder/commands/doc_builder_cli.py", line 39, in main
    args.func(args)
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/doc_builder/commands/convert_doc_file.py", line 114, in convert_command
    raise ValueError(f"This script only converts rst files. Got {source_file}.")
ValueError: This script only converts rst files. Got /Users/hyunwoongko/Github/transformers/path_to_py_file.
```

Do I have to create a new rst file?<|||||>> ```python
> ValueError: The following files have docstrings written in rst:
> - src/transformers/utils/tensor_parallel_utils.py
> To fix this run `doc-builder convert path_to_py_file` after installing `doc-builder`
> (`pip install git+https://github.com/huggingface/doc-builder`)
> make: *** [Makefile:40: repo-consistency] Error 1
> ```
> 
> @stas00 @jaketae @siddk Can you help me? I think it's about documentation.
> 
> ```python
>  hyunwoongko  ~/Github/transformers   master ±  doc-builder convert path_to_py_file
> Traceback (most recent call last):
>   File "/Library/Frameworks/Python.framework/Versions/3.7/bin/doc-builder", line 8, in <module>
>     sys.exit(main())
>   File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/doc_builder/commands/doc_builder_cli.py", line 39, in main
>     args.func(args)
>   File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/doc_builder/commands/convert_doc_file.py", line 114, in convert_command
>     raise ValueError(f"This script only converts rst files. Got {source_file}.")
> ValueError: This script only converts rst files. Got /Users/hyunwoongko/Github/transformers/path_to_py_file.
> ```
> 
> Do I have to create a new rst file?

we switched all docs from .rst and .md to .mdx some weeks back. Please See the updated docs tree in master. and README:
https://github.com/huggingface/transformers/tree/master/docs#readme<|||||>@stas00 @lucasleesw
I modified tensor parallel mapping. I am sure this is the best structure. 

In conclusion, the list of string is not a suitable structure to represent this mapping because various parameter states exist, such as fusion and reverse, and they have many combinations. (fusion means the fused QKV parameters like linear(3 * dim, dim), not the kernel fusion)

“col_no_fuse”, “col_no_fuse_no_reverse”, “col_no_replace_no_fuse”, … I think this is not we want.
For example, it may or may not be reversed while being fused. Therefore, it is better to represent them as objects, and if we set the default values of attributes to the most common value, we can reduce the time required to create a mapping.

And I added many utility functions to search these states like:

- `mapping.get_fusion_degree(model, parameter)`
- `mapping.is_reversed(model, parameter)`
- `mapping.is_fused(model, parameter)`
- `mapping.is_column_parallel(model, parameter)`
- `mapping.is_row_parallel(model, parameter)`
- `mapping.update_attributes(model)`
- ...<|||||>@hyunwoongko Apologies for the delayed review. I only have a few minor comments, and I can work on them if you'd like. Overall, I agree with the design choices you made. Thanks again for the PR!<|||||>Hello @stas00, this PR is ready for review. Could you kindly take a look when time permits?

For context, this PR provides a mapping between model names and parameters that will enable tensor parallelism. While this PR was introduced as part of efforts to integrate Oslo-enabled 3D parallelism to transformers, the map was constructed in a way that is framework agnostic, i.e., it could be used by Oslo, DeepSpeed, and the likes.

cc @LysandreJik @sgugger <|||||>@l-yohai If it works well after adding it to OSLO and testing it, let's continue to PR and add models here. I hope to support almost all models as soon as possible.<|||||>@sgugger Thanks for fixing code. I'll apply these suggestions to code.
 
@jaketae I'll apply some suggestions, Could you help me adding docstrings?<|||||>I think that any such new mappings should have an application and tests with it, so I don't think this is a good addition to transformers the way it's presented at the moment as it could lead to dead code. 

Typically any new features always come with application, tests and documentation. This PR has none of that.<|||||>Then, I think I will have to add this when I add OSLO.<|||||>closing the PR.<|||||>do you not want to first integrate the suggestions by Sylvain so that when added in the new PR it won't need to be done second time?<|||||>Hi all, apologies for causing confusion. In future PRs, I'll make sure to communicate with Stas before requesting a final round of review. 

On a separate note, I'll continue coordinating with Kevin to complete the remaining steps (i.e. docstrings, better documentation, reflecting feedback already received) to open a new PR.<|||||>@stas00 
> do you not want to first integrate the suggestions by Sylvain so that when added in the new PR it won't need to be done second time?

I will. 