3 dimensional arrays don't do dot product of sub-matrices correctly

3 dimensional arrays don't do dot product correctly (unless they have only one top-level element).
Reproducer:
```
import org.jetbrains.kotlinx.multik.api.linalg.dot
import org.jetbrains.kotlinx.multik.api.mk
import org.jetbrains.kotlinx.multik.api.ndarray
import org.jetbrains.kotlinx.multik.ndarray.data.get

fun main() {

val a = mk.ndarray(
mk[
mk[
mk[1.0],
mk[0.0],
],
],
)
val b = mk.ndarray(
mk[
mk[
mk[1.0],
mk[0.0],
],
mk[
mk[1.0],
mk[0.0],
],
],
)
println("a[0] dot a[0].T: (CORRECT)")
println(a[0] dot a[0].transpose())

println("\nb[0] dot b[0].T: (WRONG)")
println(b[0] dot b[0].transpose())

println("\nb[1] dot b[1].T: (WRONG)")
println(b[1] dot b[1].transpose())
}
```
prints
```
a[0] dot a[0].T: (CORRECT)
[[1.0, 0.0],
[0.0, 0.0]]

b[0] dot b[0].T: (WRONG)
[[0.0, 0.0],
[0.0, 0.0]]

b[1] dot b[1].T: (WRONG)
[[0.0, 0.0],
[0.0, 0.0]]
```

Start with the linalg.dot implementation used by org.jetbrains.kotlinx.multik.api.linalg.dot and inspect how ndarray slicing and transpose are handled for 3D inputs. Run the reproducer from the issue, compare the one-element and two-element cases, and confirm that each sub-matrix dot product returns the expected nonzero result.

Written by the indexing model from the issue text.