CoreML ReflectionPad3d fails to load at runtime

🐛 Describe the bug

Models containing ReflectionPad3d appear to fail to load at runtime.

Repro:

import torch

from executorch.backends.apple.coreml.partition import CoreMLPartitioner
from executorch.exir import to_edge_transform_and_lower, EdgeCompileConfig, to_edge
from executorch.extension.pybindings.portable_lib import _load_for_executorch_from_buffer

class Model(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.pad = torch.nn.ReflectionPad3d(padding=2)
        
    def forward(self, x):
        return self.pad(x)

model = Model()
inputs = (
    torch.randn(1, 6, 6, 6, 6),
)

eager_outputs = model(*inputs)
#print(f"Eager: {eager_outputs.shape} {eager_outputs}")

ep = torch.export.export(model.eval(), inputs)
print(ep)

lowered = to_edge_transform_and_lower(
    ep,
    partitioner=[CoreMLPartitioner()],
    compile_config=EdgeCompileConfig(_check_ir_validity=False)
).to_executorch()

print(lowered.exported_program())

et_model = _load_for_executorch_from_buffer(lowered.buffer)
et_outputs = et_model([*inputs])[0]

et_outputs - eager_outputs

Output:

[ETCoreMLModelCompiler.mm:55] [Core ML]  Failed to compile model, error = Error Domain=com.apple.mlassetio Code=1 "Failed to parse the model specification. Error: Unable to parse ML Program: in operation aten_pad_default_cast_fp16: Padding for more than two dimensions only supports `$
[backend_delegate.mm:288] [Core ML] Model init failed Failed to compile model, error = Error Domain=com.apple.mlassetio Code=1 "Failed to parse the model specification. Error: Unable to parse ML Program: in operation aten_pad_default_cast_fp16: Padding for more than two dimension$
[coreml_backend_delegate.mm:193] CoreMLBackend: Failed to init the model.
[method.cpp:113] Init failed for backend CoreMLBackend: 0x23

Versions

coremltools version 8.3
executorch commit https://github.com/pytorch/executorch/commit/67b6009d6b3b67eee775c8ed2fe30eae6e0bb65c (Jun 14)

cc @kimishpatel @YifanShenSZ @cymbalrush @metascroy

Start by running the provided Python reproduction through CoreMLPartitioner, to_edge_transform_and_lower, and _load_for_executorch_from_buffer, focusing on the ReflectionPad3d conversion and the reported Core ML parse failure. Done means the lowered model loads at runtime and its output can be compared with the eager output without the padding error.