Remove global random seed used for testing

[mhucka]

PR #1056 modified the pytest configuration to set a global random number seed, to deal with flaky tests that failed sporadically because some numerical comparisons exceeded tolerances undpredictably. Setting a global seed is not good practice. The seeds for test scenarios should be revised:

• Avoid global seeds. It's generally better to avoid setting a global seed for all tests. Global seeds can cause unexpected behavior when different parts of the code rely on random numbers.

• Use numpy.random.default_rng. It's considered better to create a Generator instance with a seed at the beginning of each test or test suite. This ensures that each test has its own independent random state.

• Pass Generator objects. Pass the Generator object around as an argument. This makes the random number generation explicit and avoids relying on global state.

[matti-sarjala]

A safe way to split this might be to avoid removing the global seed in the first PR.

Possible incremental path:

1. Identify tests that currently rely on implicit global randomness.
2. Convert one small test module to use local numpy.random.default_rng(seed) instances.
3. Pass the Generator explicitly where helper functions need randomness.
4. Confirm that the converted module still passes when run repeatedly.
5. Only after enough modules are converted, remove the global pytest seed as a final cleanup PR.

This would reduce the risk of turning one global-seed cleanup into many unrelated flaky-test investigations.

A minimal first PR could target just one test file and follow the invariant:

“randomness used by a test should be local, explicit, and reproducible from the test itself.”

[fzlzjerry]

I'll take the first incremental slice in _multitensor_test.py: replace its uses of the legacy np.random global state with a fresh, deterministically seeded numpy.random.Generator fixture passed into each randomized test. I'll leave the global fixture in place so unrelated modules are not destabilized, and run this module repeatedly with varied pytest-randomly seeds.