May some bug on custom layer...

## 🐞Describing the bug
- this bug is quite hard to represent...
- TLDR:
- I create an custom layer, also convert success in coremltools, but show log of warning log on CoreML.framework, like below

## To Reproduce
- I wrote a minimal demo to reproduce

```
import torch
import torch.nn as nn
import torch.nn.functional as F
import coremltools
from collections import OrderedDict

import coremltools.proto.FeatureTypes_pb2 as ft
from coremltools.converters.mil.mil import Builder as mb
from coremltools.converters.mil.frontend.torch.ops import (
_get_inputs as mil_get_inputs, is_symbolic,_get_scales_from_output_size
)
from coremltools.converters.mil import (
register_torch_op
)
from coremltools.converters.mil.mil.ops.defs._op_reqs import register_op
from coremltools.converters.mil.mil import (
Operation,
types
)
from coremltools.converters.mil.mil.input_type import (
InputSpec,
TensorInputType,
)

@register_torch_op(torch_alias=['grid_sample'], override=True)
def grid_sampler(context, node):
# https://github.com/pytorch/pytorch/blob/00d432a1ed179eff52a9d86a0630f623bf20a37a/aten/src/ATen/native/GridSampler.h#L10-L11
inputs = mil_get_inputs(context, node, expected=5)
x = mb.custom_op(
x=inputs[0],
coordinates=inputs[1],
name=node.name,
)
context.add(x)

@register_op(is_custom_op=True)
class custom_op(Operation):
input_spec = InputSpec(
x=TensorInputType(type_domain="T"),
coordinates=TensorInputType(type_domain="T"),
)

type_domains = {
"T": (types.fp16, types.fp32),
"U": (types.int32,),
}
bindings = {'class_name': 'CustomGridSample',
'input_order': ['coordinates', 'x'],
'description': "custom grid sampler!"
}

def __init__(self, **kwargs):
super(custom_op, self).__init__(**kwargs)

def type_inference(self):
input_shape = self.x.shape
coord_shape = self.coordinates.shape

ret_shape = list(input_shape)
ret_shape[2] = coord_shape[1] # Output height
ret_shape[3] = coord_shape[2] # Output width
return types.tensor(self.x.dtype, ret_shape)
########################################################################
######################## Test ml model ################################

IN_WH = 512
GRID_WH = 256

class TestModel(nn.Module):

def __init__(self):
super(TestModel, self).__init__()
self.conv1 = nn.Conv2d(in_channels=3, out_channels=16, kernel_size=3)
self.conv2 = nn.Conv2d(in_channels=16, out_channels=32, kernel_size=3)

def forward(self, x, grid):
x =F.relu(self.conv1(x))

x = F.grid_sample(x, grid)
x = F.relu(self.conv2(x))
return x

########################################################################
########################################################################

def convert(output_path):
torch_model = TestModel()
# torch_model = torch.jit.load('./flow_480x272_250103.pt', map_location='cpu')
example_input = torch.rand(1, 3, IN_WH, IN_WH)
example_grid = torch.ones(1, GRID_WH, GRID_WH, 2)
# example_input = torch.rand(1, 1, 272, 480)
# traced_model = torch.jit.trace(torch_model, (example_input, example_input))
traced_model = torch.export.export(torch_model, (example_input, example_grid))
mlmodel = coremltools.convert(
traced_model,
inputs=[
coremltools.TensorType(name="input0", shape=example_input.shape),
coremltools.TensorType(name="input1", shape=example_grid.shape),
],
convert_to="neuralnetwork",
# convert_to="milinternal",
# convert_to="mlprogram",
minimum_deployment_target=coremltools.target["iOS13"]
)
print(mlmodel)
mlmodel_path = output_path + ".mlmodel"
mlmodel.save(mlmodel_path)

print(f"Saved to {output_path}")

def main():
convert('test')

if __name__ == "__main__":
main()
```

using this code can generate an simplest nn net in mlmodel, then loading in objective-c project just the using API
```
id model = [MLModel modelWithContentsOfURL:modelUrl
error:&error];
```
will cause this error log dump in console.

I don't know whats wrong on this network infer...Also I cannot judge, this is coremltools bug ?or CoreML framework bug? or some bug in my custom op?

## System environment (please complete the following information):
- coremltools version: try 7.2, 8.0,8.1,
- pytorch version: 2.4.0, 2.4.1
- OS : try 14.4, 14.5

## Additional context
@YifanShenSZ I'm not sure if there are any bugs in my toy code, but if you have some free time, would you mind reviewing it for me?