Fix is_causal being a tensor
Author: IlyasMoutawwakil
Pull request: yes

# What does this PR do?

We encountered this issue when gpt2 is part of a [vision encoder decoder (add_cross_attention=True)](https://github.com/huggingface/optimum/actions/runs/12866793752/job/35870112430?pr=2158)
```
FAILED exporters/onnx/test_exporters_onnx_cli.py::OnnxCLIExportTestCase::test_exporters_cli_pytorch_cpu_639_vision_encoder_decoder_image_to_text_with_past_default_hf_internal_testing_tiny_random_VisionEncoderDecoderModel_vit_gpt2 - TypeError: scaled_dot_product_attention(): argument 'is_causal' must be bool, not Tensor
```
Usually `is_causal` is evaluated in `is_causal = attention_mask is None and query_states.shape[-2] > 1 and not is_cross_attention` by the fact that `attention_mask is None` is False, skipping the rest, but when attention mask is not None, `query_states.shape[-2] > 1` is evaluated and returns a tensor, resulting in sdpa failing because it's expecting a bool.

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Comments:
Yeah I was surprised at first and thought it might be a behavior change in torch but it's actually related to tracing:

```python
import torch


class model(torch.nn.Module):
    def __init__(self):
        super(model, self).__init__()
        self.fc = torch.nn.Linear(1, 1)

    def forward(self, x):
        print("shape > 1: ", x.shape[0] > 1)
        return self.fc(x)


model = model()
x = torch.randn(1, 1)

model(x)  # shape > 1:  False
torch.jit.trace(model, x, check_trace=False)  # shape > 1:  tensor(False)
torch.onnx.export(model, x, "model.onnx")  # shape > 1:  tensor(False)
```

This should've impacted the gpt2 onnx tests but I guess it wasn't caught because it's only tested as a pure decoder.

Got it, does the device synch not cause any issue for the exported model afterwards? 

> Got it, does the device synch not cause any issue for the exported model afterwards?

@ArthurZucker didn't see any issues in optimum onnx exported models, but I added a guard for jit tracing just in case.

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