[tests] fix mamba integration simple inference precision issue
Author: faaany
Pull request: yes

## What does this PR do?
This test fails both on CUDA and XPU. 

Root Cause:
The model's output sequence assertion can pass, but the logits assertion fails. This indicates that there might be some numerical precision issues during inference with torch.float16, since the model is loaded with `torch_dtype=torch.float16`. 

To verify my assumption, I changed the torch.float16 to torch.float32. And the tensor outputs on XPU and CUDA are equal to each other. 

For tasks requiring high precision, such as validation, testing or debugging, `torch.float32` should be used instead of `torch.float16`.

Fix: 
temporarily switch to `torch.float32` ensures that the test is not affected by these precision issues and focuses on validating the model's correctness.

After the fix, it works both on CUDA and XPU:

``
PASSED tests/models/mamba/test_modeling_mamba.py::MambaIntegrationTests::test_simple_generate_1_cpu
PASSED tests/models/mamba/test_modeling_mamba.py::MambaIntegrationTests::test_simple_generate_0_cuda
PASSED tests/models/mamba/test_modeling_mamba.py::MambaIntegrationTests::test_simple_generate_1_cpu
PASSED tests/models/mamba/test_modeling_mamba.py::MambaIntegrationTests::test_simple_generate_0_xpu
```



Comments:
The problem of using `torch.float32` is that we might get GPU OOM (which might be the main reason why we use torch.float16 when these tests are added to the library the first time). Our CI runner is mainly T4 GPU with 16G GPU memory.

I would like to invite @faaany to participate to the discussion in #37126 (as you are a consistently contribute to XPU related PRs), and once we achieve an agreement there, the solution there could be used to fix the issue here.

(I will check if torch.float32 would work on our runners however)

well, this PR pass all tests on T4 GPU. I am happy to merge as it is, after [this comment](https://github.com/huggingface/transformers/pull/37193#discussion_r2024662836) is addressed.

Thank youuu a lot! 

(but still, if you could join #37126, that wuld be great 🙏 but don't stress if not)

by the way, i see here branch name `issue176` and another PR `issue175`. Are these just coincidence or 🤔 ?

> by the way, i see here branch name `issue176` and another PR `issue175`. Are these just coincidence or 🤔 ?

it's not an coincidence, @ydshieh. We are systematically go through and fix XPU UT issues in Intel to align w/ CUDA, these issue numbers are the jira number we track internally. Thx.

> well, this PR pass all tests on T4 GPU. I am happy to merge as it is, after [this comment](https://github.com/huggingface/transformers/pull/37193#discussion_r2024662836) is addressed.
> 
> Thank youuu a lot!
> 
> (but still, if you could join #37126, that wuld be great 🙏 but don't stress if not)

just some background, @faaany is from my team, we are Intel HuggingFace engineering team to enable/optimize/upstream Intel platforms(CPU/XPU/HPU) 's developer experience and performance across Hugging Face ecosystem libraries, :). 

Thanks @ydshieh for the invitation! As Matrix said, we are one team. He represents my opinion. 😊

Thank a lot. XPU 🚀