BLOOM - modifying slow tests
# What does this PR do?

- changed the non passing tests to fp32
- reduced sequence length
- remove padding test

All these matters have been discussed on Slack but mainly:

1- Generations tests were not passing because the linear layers does not give the same results between torch 1.11 and torch 1.12
2- batched generation can be flaky sometimes in half precision mode, this should be expected. Therefore we reduce the sequence length of the generated output
3- One should **always** use `padding_side=left` when doing batched generations

cc @ydshieh @patrickvonplaten

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_17963). All of your documentation changes will be reflected on that endpoint.<|||||>Hi, @younesbelkada 

Could you explain a bit more on ` One should always use padding_side=left when doing batched generations`?
And what are examples of test failures when using `padding=right` ? I couldn't find you mentioning this on Slack.

Thanks!
<|||||>Hi @ydshieh !
From the internal discussions here is a summary of why one should always use `padding_side=left` (cc @patrickvonplaten ):
- Imagine: `["hello my name is", "hey <pad> <pad> <pad>"]`
For the first input the correct token will be sampled from "is" - however for the second input, generate would incorrectly sample from `"<pad>"` where as it should sample from `"hey"`. Making sure everything is batched on the left circumvents this problem !<|||||>@younesbelkada - IMO we should not expect the generation to be flaky ever, why is this the case here?<|||||>Hi @younesbelkada : I have 3 questions 🙏 

- with fp16:
  - do we get stable results in a specific torch version (i.e. the same result across many runs)
- after changing to fp32 (without reducing the seq length)
  - do we get the same results across torch 1.11 and 1.12?
  - do we get stable results in a specific torch version (i.e. the same result across many runs)<|||||>Hi @ydshieh !
After merging this PR: https://github.com/huggingface/transformers/pull/17866 the slow tests are now passing. Our conclusion is that:
1- In half precision mode we might not get the same results across batched generation and it should be expected 
2- This behavior is observed ONLY on small models !<|||||>I'm still a bit confused by this PR - generations are not flaky for pretrained models normally and it's a bit weird to me that all this test does is modifying slow generation tests<|||||>Closing as it has been fixed by https://github.com/huggingface/transformers/pull/18344