onnxruntime

Update tolerance of provider tests to fix flaky tests (#19792)

### Description

Check float/double/float16/bfloat16 tensors are close like
[numpy.isclose](https://numpy.org/doc/stable/reference/generated/numpy.isclose.html).
```
absolute(a - b) <= (atol + rtol * absolute(b))
```

The default tolerance thresholds:
- float: atol=1e-5 and rtol=1e-4
- float16: atol=0.0025 and rtol=0.001
- bfloat16: atol=0.02 and rtol=0.01

### Motivation and Context

Current pipeline has frequent failure due to using only relative
tolerance in https://github.com/microsoft/onnxruntime/pull/19608:

[ RUN      ] MatMulIntegerToFloat.NoZeroPoint_NoBias_test_U8S8
1: C:\a\_work\1\s\onnxruntime\test\providers\checkers.cc(272): error:
The difference between cur_expected[i] and cur_actual[i] is
1.3113021850585938e-06, which exceeds *(params.relative_error) *
std::abs(cur_expected[i]), where
1: cur_expected[i] evaluates to -1.3113021850585938e-06,
1: cur_actual[i] evaluates to 0, and
1: *(params.relative_error) * std::abs(cur_expected[i]) evaluates to
2.6226043559063328e-08.

It is not reasonable to use relative tolerance for a small value very
close to 0. Combining relative tolerance with a positive absolute
tolerance could avoid such issue.