[lslusarczyk]

A module without a strategy is now tuned with tt.default_strategy(device).
It measures every backend that runs on the device and keeps the fastest.

tt.default_strategy(device) is HighestThroughputStrategy over default_backends(device):

Device	Backends
XPU	XPU graph, Torch Inductor, OpenVINO, Torch Eager
CPU	Torch Inductor, OpenVINO, Torch Eager

TorchAO is left out because quantization changes the results.

The old default was one FirstWinsStrategy instance shared by every module.
FirstWins keeps the first backend that builds, not the fastest one.
The shared instance also carried state from one module to the next.
Each graph now gets its own strategy, built for the device it is tuned on.

FirstWinsStrategy and HighestThroughputStrategy without backends use the same default_backends(device).
FirstWinsStrategy keeps its order, XPU graph first.
HighestThroughputStrategy() now also measures OpenVINO.
On CPU neither strategy tries XPU graph.

On an Arc Pro B70 the default strategy was the fastest or close to it on five of six models.
OpenVINO wins on whole ViT and DistilBERT models and loses on small modules, so it is measured, not excluded.

Breaking:

• Default tuning takes longer, because it measures every backend.
• Without backends, tuning on a device other than XPU or CPU raises ValueError.