[Quant Tool] Flaky test due to Pad reflect bug (#22798)
### Description
Fixes a unit test that would fail intermittently due to an existing bug
with Pad (reflect mode). When the number of padded values is >= the
inner dimension size, the ORT Pad implementation accesses invalid
memory. This PR makes the number of padding values less than the inner
dimension size to avoid triggering the bug.
### Motivation and Context
See related issues:
https://github.com/microsoft/onnxruntime/issues/8265
https://github.com/microsoft/onnxruntime/issues/11828
https://github.com/microsoft/onnxruntime/issues/20801
Here's a valgrind trace obtained on a Linux machine (with
`sess_options.enable_cpu_mem_arena = False`)
```
==864228== Invalid read of size 4
==864228== at 0x2716272A: void onnxruntime::PadInnermostAxis<unsigned int>(unsigned int*, unsigned int*, long, unsigned long) (pad.cc:370)
==864228== by 0x2715D213: onnxruntime::common::Status onnxruntime::PadImpl<unsigned int>(onnxruntime::OpKernelContext*, absl::lts_20240722::InlinedVector<long, 10ul, std::allocator<long> > const&, absl::lts_20240722::InlinedVector<long, 10ul, std::allocator<long> > const&, onnxruntime::Mode const&, unsigned int) (pad.cc:551)
==864228== by 0x2715B2BB: onnxruntime::Pad::Compute(onnxruntime::OpKernelContext*) const (pad.cc:725)
==864228== by 0x276FF6A7: onnxruntime::ExecuteKernel(onnxruntime::StreamExecutionContext&, unsigned long, unsigned long, bool const&, onnxruntime::SessionScope&) (sequential_executor.cc:484)
==864228== by 0x276F4A04: onnxruntime::LaunchKernelStep::Execute(onnxruntime::StreamExecutionContext&, unsigned long, onnxruntime::SessionScope&, bool const&, bool&) (execution_steps.cc:73)
...
```
The above is obtained with the basic Pad(reflect) example on the [ONNX
Pad operator spec
page](https://onnx.ai/onnx/operators/onnx__Pad.html#summary):
```python
data = [
[1.0, 1.2],
[2.3, 3.4],
[4.5, 5.7],
]
pads = [0, 2, 0, 0]
mode = 'reflect'
# Expected output by ONNX spec
expected_output = [
[1.0, 1.2, 1.0, 1.2],
[2.3, 3.4, 2.3, 3.4],
[4.5, 5.7, 4.5, 5.7],
]
# Bugged output from onnxruntime has invalid/uninitialized data for the first element in the inner dimension
# invalid data may be 0.0, inf, nan, etc.
ort_output = [
[inf, 1.2, 1.0, 1.2],
[inf, 3.4, 2.3, 3.4],
[inf, 5.7, 4.5, 5.7],
]
```
