Failure to export torch.nn.functional.pad with int32 tensor

Convert does not seem to support torch pad with int32 input type

`ValueError: In op, of type pad, named val, the named input `constant_val` must have the same data type as the named input `x`. However, constant_val has dtype fp32 whereas x has dtype int32.

venv/lib/python3.9/site-packages/coremltools/converters/mil/mil/input_type.py:137: ValueError`

```python
import coremltools as ct
import torch

class Example(torch.nn.Module):

def forward(self, x):
x = torch.nn.functional.pad(x, (0, 2), value=0)
return x

module = Example().eval()
traced = torch.jit.trace(module, (torch.IntTensor([[1, 2], [3, 4]]),))

coremlmodel = ct.convert(traced,
source='pytorch',
convert_to='mlprogram',
inputs=[ct.TensorType(name="x", dtype=ct.converters.mil.mil.types.int32, shape=(2, 2)),],
outputs=[ct.TensorType(name="y", dtype=ct.converters.mil.mil.types.int32)],
compute_units=ct.ComputeUnit.ALL,
compute_precision=ct.precision.FLOAT16,
)
```

## System environment (please complete the following information):
coremltools version: 6.2
mac os x Ventura
torch: 1.13.1
python 3.9

Start with the provided torch.nn.functional.pad reproducer and the traceback location in coremltools/converters/mil/mil/input_type.py:137. Trace how the pad operation handles constant_val and x dtypes, then verify that converting the int32 example succeeds and preserves the expected output dtype.

Written by the indexing model from the issue text.