Fix unsafe copies in EXIR and permute transforms

[oscarandersson8218]

Replace deepcopy-based copies of shape lists with shallow container copies in paths that can carry torch.SymInt values from fake tensor metadata. This is safe as torch.Size is immutable, so creating a shallow list copy of it is safe: we can insert/delete elements in the new list without affecting the original shape.

This fixes symbolic-shape failures in exir.tensor.stride_from_dim_order() and in PostponePermuteOpBelowSqueezeOrUnsqueezeLikeView, where deepcopy() could crash while handling SymInt-backed shapes. The error that was produced: "RuntimeError: Cannot access data pointer of Tensor (e.g. FakeTensor, FunctionalTensor). If you're using torch.compile/export/fx, it is likely that we are erroneously tracing into a custom kernel. To fix this, please wrap the custom kernel into an opaque custom op. Please see the following for details:
https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html"

Add focused regression coverage for both cases: one test for stride computation with symbolic sizes, and one dynamic-shape edge-graph test for the permute/view transform pass.

cc @digantdesai @freddan80 @per @zingo @mansnils @Sebastian-Larsson @robell @rascani

[pytorch-bot]

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