Enable build Intel backend in onemkl interfaces on CUDA

[vlad-perevezentsev]

This PR suggests to enable MKLGPU_BACKEND and MKLCPU_BACKEND builds in OneMKL Interfaces during build on CUDA with --target=cuda flag to ensure that all available devices can be used

ONEAPI_DEVICE_SELECTOR=cuda:gpu pytest dpnp/tests/
========= 67432 passed, 5625 skipped, 34 deselected, 2 xfailed in 442.92s (0:07:22) ======================


ONEAPI_DEVICE_SELECTOR=opencl:cpu pytest dpnp/tests/
========= 68332 passed, 4725 skipped, 34 deselected, 2 xfailed in 289.06s (0:04:49) ======================

Previous implementation only allowed array allocation on cuda::gpu device with ONEAPI_DEVICE_SEELCTOR=cuda:gpu env variable enabled and threw RuntimeError otherwise.

• Have you provided a meaningful PR description?
• Have you added a test, reproducer or referred to issue with a reproducer?
• Have you tested your changes locally for CPU and GPU devices?
• Have you made sure that new changes do not introduce compiler warnings?
• Have you checked performance impact of proposed changes?
• If this PR is a work in progress, are you filing the PR as a draft?

[github-actions]

View rendered docs @ https://intelpython.github.io/dpnp/pull/2229/index.html

[antonwolfy]

Thank you @vlad-perevezentsev

[coveralls]

coverage: 65.09%. remained the same
when pulling 50cc35a on enable_intel_backend_cuda
into d83ea3d on master.