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Also use contig kernel if simplified iter is 1d and has unit strides
Example where it helps:
```
In [1]: import dpctl, dpctl.tensor as dpt
In [2]: x = dpt.arange(1234*7873, dtype=dpt.int32)
In [3]: xx = dpt.permute_dims(dpt.reshape(x, (2, 617, 7873)), (1,2,0))
In [4]: yy = dpt.permute_dims(dpt.reshape(dpt.empty_like(x, dtype="f4"), (2, 617, 7873)), (1,2,0))
In [5]: %timeit yy[...] = xx
1.07 ms ± 93.8 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)
```
in master the time is about 2.8 ms on Iris Xe.
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