add eager mode check for NaN and Inf

Summary:
This diff includes some debug tool improvements
In IG_CTR MC proposal debug, we noted that some new snapshots generated NaN in results. We want to figure out the root cause.
With this diff, we can run with `--run-accuracy-check` which will run the generate merge + load merge through pybind. But it does not check eager mode run. In this diff, I added this feature. The random inputs are created the same way as we did in load merge.  Attach the results P1494263214
```
CUDA_VISIBLE_DEVICES=5 TORCH_COMPILE_DEBUG=1 TORCHINDUCTOR_MAX_AUTOTUNE=1 buck2 run mode/opt-split-dwarf   mode/inplace -c fbcode.platform010_cuda_version=12 -c fbcode.nvcc_arch=h100  caffe2/torch/fb/model_transform/experimental/benchmark:mts_gpu_benchmark -- --model-path=/data/local/models/581303767/85/gpu_lowering/input.predictor.disagg.gpu.merge  --lower-backend="AOT_INDUCTOR" --run-accuracy-check  --debug_operator_range="1397,1397" --generate_sample_inputs=False  --min_acc_module_size=0  --disable-multiple-batch-run  2>&1 | tee aot.log
```

If we want to enable the layer print, add "--dispatch-print" and it will print out each layer's output and check if NaN or INF is contained.

Reviewed By: hl475, chenyang78

Differential Revision: D60150435

fx2ait/fx2ait/ait_splitter.py

@@ -172,9 +172,7 @@ def __init__(
             settings = AITSplitterSettings()
         if not operator_support:
             if settings.debug_operator_range:
-                min_range, max_range = tuple(
-                    int(x) for x in settings.debug_operator_range.split(",")
-                )
+                min_range, max_range = settings.debug_operator_range
                 operator_support = _range_operator_support(
                     module=module,
                     start=min_range,