[ROCM] GFX906 gpu dosent work when GFX900 gpu is also in the system
### System Info

System:
* ROCM 5.6
* torch-2.1.0.dev20230721+rocm5.6 
* GFX900 GPU (MI25) (HIP device 2)
* GFX906 GPU (MI50) (HIP device 1)
* GFX1030 GPU (rx6800xt) (HIP device 0)
* transformers @b257c46a075419c09e5ce5c5aa39bc346ecdb9a5
* Linux 6.4.3 with AMDGPU p2p activated

companion bug against rocm: https://github.com/RadeonOpenCompute/ROCm/issues/2328

### Who can help?

_No response_

### Information

- [X] The official example scripts
- [X] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

Have GFX900 and GFX906 gpu in system

run the following script:
```
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
import argparse

if __name__ == "__main__":

	parser = argparse.ArgumentParser("Transformers llm testing script")
	parser.add_argument('--tokenizer', '-t', help="tokenizer to use")
	parser.add_argument('--model', '-m', required=True, help="model to use")
	parser.add_argument('--device', '-d', default="cpu", help="device to use")
	parser.add_argument('--prompt', '-p', default="Today was a long day ", help="the promt to generate from")
	args = parser.parse_args()

	if args.device != 'cpu':
		dtype = torch.bfloat16
	else:
		dtype = torch.float32

	if args.tokenizer is None:
		tokenizer = AutoTokenizer.from_pretrained(args.model, padding_side='left')
	else:
		tokenizer = AutoTokenizer.from_pretrained(args.tokenizer, padding_side='left')

	model = AutoModelForCausalLM.from_pretrained(args.model, low_cpu_mem_usage=True, torch_dtype=dtype).to(args.device)
	model.eval()

	input_ids = tokenizer(args.prompt, return_tensors="pt").input_ids.to(args.device)
	attention_mask = torch.ones(input_ids.shape, device=args.device, requires_grad=False)
	outputs = model.generate(input_ids, attention_mask=attention_mask, do_sample=True, temperature=1)
	response_decoded = tokenizer.batch_decode(outputs, skip_special_tokens=True)
	response = response_decoded[0]
	print(response)

```

I used bloom-6b for the model, however this dosent matter. If device is set to the GFX1030 gpu everything works. If the deivce is set to the GFX900 GPU everything works, if the deivce is set to the GFX906 the script fails with:

```
Traceback (most recent call last):
  File "/home/philipp/machine-lerning/Transformersplayground/janachat/test-simple.py", line 29, in <module>
    outputs = model.generate(input_ids, attention_mask=attention_mask, do_sample=True, temperature=1)
  File "/home/philipp/machine-lerning/Transformersplayground/venv/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/philipp/machine-lerning/Transformersplayground/venv/lib/python3.9/site-packages/transformers/generation/utils.py", line 1563, in generate
    return self.sample(
  File "/home/philipp/machine-lerning/Transformersplayground/venv/lib/python3.9/site-packages/transformers/generation/utils.py", line 2665, in sample
    next_tokens.tile(eos_token_id_tensor.shape[0], 1).ne(eos_token_id_tensor.unsqueeze(1)).prod(dim=0)
RuntimeError: CUDA driver error: 303
```

running with export AMD_LOG_LEVEL=8 reveals that rocm appears to try to launch a GFX900 kernel on GFX906:

```
:1:devprogram.cpp           :1873: 1265234165 us: 21877: [tid:0x7f3bf549b740] Error: The program ISA amdgcn-amd-amdhsa--gfx900:xnack- is not compatible with the device ISA amdgcn-amd-amdhsa--gfx906:sramecc+:xnack-Error: create kernel metadata map using COMgr
Error: Cannot Find Global Var Sizes
Error: Cannot create kernels.
```

Indeed removeing the GFX900 gpu from the system makes the GFX906 work

### Expected behavior

GFX906 gpu should work in all instances
This seems more of an issue for PyTorch and AMD? We only use those libraries in Transformers.<|||||>this is correct, this issue has since been tracked down here https://github.com/ROCmSoftwarePlatform/rocBLAS/issues/1346#issuecomment-1646942417

i will keep the bug here open untill its resolved so that any one else expieranceing the same issue will be redirected the underlying issue.