Fix missing strides validation in dpnp.tensor.usm_ndarray

[vlad-perevezentsev]

This PR proposes to fix #2881 issue.

The problem was that usm_ndarray constructor did not validate user-provided strides when allocating new memory.
This made it possible to create arrays with invalid stride patterns producing negative memory displacement or oversized memory footprints.

This PR adds validation for invalid stride configurations when allocating new memory and raises ValueError for unsupported strides.
It also adds a new test_ctor_invalid_strides in test_usm_ndarray_ctor.py to cover these cases

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[github-actions]

View rendered docs @ https://intelpython.github.io/dpnp/pull/2927/index.html

[github-actions]

Array API standard conformance tests for dpnp=0.21.0dev0=py313h509198e_44 ran successfully.
Passed: 1352
Failed: 8
Skipped: 16

[ndgrigorian]

Suggested change

	"strides={} result in a negative memory displacement "
	"and are not allowed when allocating new "
	"memory".format(strides))
	f"strides={strides} result in a negative memory displacement "
	"and are not allowed when allocating new "
	"memory"

[ndgrigorian]

Suggested change

	"strides={} is incompatible with shape={} when "
	"allocating new memory because the memory footprint "
	"exceeds the number of elements".format(strides, shape))
	f"strides={strides} is incompatible with shape={shape} when "
	"allocating new memory because the memory footprint "
	"exceeds the number of elements"