onnxruntime

Adds ATen fallback for scaled_dot_product_attention (#21107)

### Description
<!-- Describe your changes. -->

Introduces an ATen fallback for
`torch.nn.functional.scaled_dot_product_attention`. This operator was
introduced in torch 2.0 and, since then, has had many updates including
the implementation of memory efficient attention for V100 machines. The
current torchscript exporter exports a subgraph for attention which does
not provide the same memory savings that PyTorch's memory efficient
attention kernel provides. Allowing fallback to PyTorch ATen op for
attention helps mitigate memory spike issues for models leveraging
memory efficient attention.

### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->

Memory issues arose when integrating ONNX Runtime Training with AML
Stable Diffusion.

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Co-authored-by: root <prathikrao@microsoft.com>