Megatron conversion code converts some weights in fp16 to fp32(or uint8).
Author: hwijeen
Pull request: no

## 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: 4.9.2
Platform: Linux-4.18.0-25-generic-x86_64-with-glibc2.10
Python version: 3.8.5
PyTorch version (GPU?): 1.8.0a0+52ea372 (True)
Tensorflow version (GPU?): not installed (NA)
Flax version (CPU?/GPU?/TPU?): not installed (NA)
Jax version: not installed
JaxLib version: not installed
Using GPU in script?:
Using distributed or parallel set-up in script?: No



### Who can help
<!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @Rocketknight1

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

Model hub:

- for issues with a model report at https://discuss.huggingface.co/ and tag the model's creator.

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->
@novatig @jdemouth @LysandreJik

## Information

Model I am using (Bert, XLNet ...):

The problem arises when using:
* [ ] 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)

## To reproduce

1. Check the data type of original megatron checkpoint. It's all in fp16.
```bash
wget --content-disposition  https://api.ngc.nvidia.com/v2/models/nvidia/megatron_lm_345m/versions/v0.0/zip -O checkpoint.zip
unzip checkpoint.zip
python -c "import torch; from pprint import pprint as print; sd=torch.load('./release/mp_rank_00/model_optim_rng.pt'); d= {d.dtype: 1 for d in sd['model']['language_model']['transformer'].values()}; print(d.keys())"
# dict_keys([torch.float16])
```

2. But the [current conversion script](https://github.com/huggingface/transformers/blob/master/src/transformers/models/megatron_gpt2/convert_megatron_gpt2_checkpoint.py) converts some into [float32](https://github.com/huggingface/transformers/blob/91ff480e2693f36b11aaebc4e9cc79e4e3c049da/src/transformers/models/megatron_gpt2/convert_megatron_gpt2_checkpoint.py#L164) and [uint8](https://github.com/huggingface/transformers/blob/91ff480e2693f36b11aaebc4e9cc79e4e3c049da/src/transformers/models/megatron_gpt2/convert_megatron_gpt2_checkpoint.py#L160). This leads to a model with data type which is not faithful to the original model, and potentially a problem as discussed in #13076 
```
python3 /hf/transformers-master/src/transformers/models/megatron_bert/convert_megatron_gpt2_checkpoint.py checkpoint.zip
python -c "import torch; sd=torch.load('pytorch_model.bin');  d = {p.dtype:1 for p in sd.values() }; print(d.keys())"
# dict_keys([torch.float16, torch.float32, torch.uint8])
```

<!-- If you have code snippets, error messages, stack traces please provide them here as well.
     Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
     Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.-->

## Expected behavior
Converted checkpoint should have the same data type as the original one.
<!-- A clear and concise description of what you would expect to happen. -->

I will open a new PR to address this :)

Comments: