IntelPython / dpnp / 33077063400

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Wrap out-of-range float-to-integer astype casts to match NumPy (#3033)

Casting an out-of-range floating-point value to an integer type is
undefined behavior in C++. SYCL devices resolve it by saturating to the
destination's min/max, whereas NumPy emits a plain C cast that, for
narrow integer targets, truncates toward zero and wraps modulo the
destination width (e.g. `float32(128)` becomes `int8(-128)`).

`convert_impl` (used by `astype` and every copy-and-cast kernel) only
normalized this to NumPy's wrapping behavior for *unsigned*
destinations. Signed narrow integer targets fell through to a raw
`static_cast` and therefore *saturated* on device, diverging from NumPy.
The same inconsistency showed up within a single operation:
`dpnp.tensor.linalg.trace` with an `int8` output dtype produced
different results depending on whether the value went through the
element-wise `astype` path (saturated) or the reduction path (wrapped).

This PR generalizes the float-to-integer branch of `convert_impl` to
funnel every conversion through a wider signed integer, relying on the
well-defined integer narrowing to perform the modular wrap for both
signed and unsigned narrow integer targets. 64-bit destinations keep
their existing handling (unsigned routes negatives through `int64`;
signed casts directly).

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