Update `BridgeTowerModelTester`
Author: ydshieh
Pull request: yes

# What does this PR do?

Update `BridgeTowerModelTester` to use small values for config.



Comments:
_The documentation is not available anymore as the PR was closed or merged._

Remark: with lager model (but not too large), we get

```bash
FAILED tests/models/bridgetower/test_modeling_bridgetower.py::BridgeTowerModelTest::test_model_parallelism - RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cuda:1!
```

Better to check this separately.

---------------------

Here is the full log

```bash
>                   new_output = new_model(**inputs_dict_class)

tests/test_modeling_common.py:2616: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py:1501: in _call_impl
    return forward_call(*args, **kwargs)
/usr/local/lib/python3.8/dist-packages/accelerate/hooks.py:165: in new_forward
    output = old_forward(*args, **kwargs)
src/transformers/models/bridgetower/modeling_bridgetower.py:1423: in forward
    image_embeds = self.vision_model.visual.transformer.resblocks[i](image_embeds).type(
/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py:1501: in _call_impl
    return forward_call(*args, **kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = BridgeTowerResidualAttention(
  (attn): MultiheadAttention(
    (out_proj): NonDynamicallyQuantizableLinear(in_feature...ar(in_features=2048, out_features=512, bias=True)
  )
  (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
)
hidden_state = tensor([[[ 0.5531,  0.0555, -0.0248,  ...,  0.2110, -0.0403,  0.0487]],

        [[ 0.2963, -0.1709,  0.0074,  ...,  0...      [[ 0.3324, -0.0536, -0.0069,  ...,  0.0911, -0.0565, -0.2751]]],
       device='cuda:1', grad_fn=<ViewBackward0>)
attention_mask = None

    def forward(self, hidden_state: torch.Tensor, attention_mask: torch.Tensor = None):
        residual_state = hidden_state + self.attention(self.ln_1(hidden_state), attention_mask)
        hidden_state = self.ln_2(residual_state)
        for _, layer in self.mlp.items():
            hidden_state = layer(hidden_state)
>       hidden_state = residual_state + hidden_state
E       RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cuda:1!

src/transformers/models/bridgetower/modeling_bridgetower.py:237: RuntimeError
================================================================================================== warnings summary ==================================================================================================
../usr/local/lib/python3.8/dist-packages/detectron2/data/transforms/transform.py:46
  /usr/local/lib/python3.8/dist-packages/detectron2/data/transforms/transform.py:46: DeprecationWarning: LINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use BILINEAR or Resampling.BILINEAR instead.
    def __init__(self, src_rect, output_size, interp=Image.LINEAR, fill=0):

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
============================================================================================== short test summary info ===============================================================================================
FAILED tests/models/bridgetower/test_modeling_bridgetower.py::BridgeTowerModelTest::test_model_parallelism - RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cuda:1!
```