fix(runtime): give the TensorRT engine class an __eq__

[shoumikhin]

What is broken

tests/py/dynamo/models/test_export_serde.py::test_save_load_aoti is red on main:

NotImplementedError: '__eq__' is not implemented for __torch__.torch.classes.tensorrt.Engine
  File "torch/_subclasses/fake_tensor.py", line 1433, in __eq__
    return isinstance(other, _DispatchCacheKey) and self.key == other.key

Why

The engine class reports tracing_mode "real", so export hands the engine
object itself to the meta kernel instead of a fake stand-in. The engine then
ends up inside torch's fake tensor dispatch cache key. That cache hashes the
key and, on a hash match, compares with ==. The class defines no __eq__, so
the comparison raises.

Any second trace of an already compiled module hits this. torch_tensorrt.save
with retrace=True is one such path, which is why the AOT Inductor save test
fails.

torch has the same problem with its own torch::jit::OpaqueObject and solves it
the same way, see torch/csrc/jit/python/opaque_obj.h.

Fix

Define __eq__ on the class and compare by identity. Two handles to one engine
are one engine; two different engines are never equal. A comparison that says
"not equal" only costs a cache miss, so identity is both correct and the
cheapest correct answer.

Tested

This box has no TensorRT headers, so the library could not be rebuilt here.
Instead the same method was appended to the live class type at runtime, the way
torch::class_::defineMethod does, and the body of test_save_load_aoti was
run against the real engine class on an H100:

• without the method: the NotImplementedError above, every time
• with the method: save, load and run succeed, cosine similarity 1.000000

A second check on a minimal custom class with the same registration shape
(tracing_mode "real", __obj_flatten__, pickle) reproduces the failure on
re-export without __eq__ and passes with it.