IntelPython / dpnp / 37211143718

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Commit Message

Fix `dpnp.median`/`dpnp.nanmedian` result shape for empty and size-1 kept dimensions (#3081)

This PR fixes two kept-dimension shape bugs in
`dpnp.median`/`dpnp.nanmedian`.

**Empty kept dimension.** `dpnp.median` and `dpnp.nanmedian` raised
`ValueError` when called with a tuple (or list) `axis` and one of the
kept, non-reduced dimensions has size 0, e.g.
```
dpnp.median(dpnp.empty((0, 3, 4)), axis=(1, 2))
```
The sequence-axis path flattens the reduced axes in
`_flatten_array_along_axes` with `a.reshape(kept_shape + (-1,))`. The
`-1` cannot be inferred once the array has size 0 and a kept axis is
also 0 (every merged length yields a size-0 array, so the dimension is
ambiguous), which makes `reshape` raise. The merged length is now
computed explicitly with `math.prod(...)`, so the tuple-axis path
returns the same empty result as the single-axis path.

**Size-1 kept dimension.** `dpnp.nanmedian` dropped kept dimensions of
size 1 and returned the wrong shape, e.g. a `(1, 5)` array reduced over
`axis=1` returned shape `()` instead of `(1,)`. `_calc_nanmedian` ended
with an unconditional `dpnp.squeeze(res)`, which also removed
non-reduced size-1 axes; it now squeezes only the reduced trailing axis
with `dpnp.squeeze(res, axis=-1)`.

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