For AoT deployments models often have multiple exported methods.
This patch enables something like this:
```
class TwoMethodsModule(torch.nn.Module):
def sin(self, x):
return torch.ops.aten.sin(x)
def cos(self, x):
return torch.ops.aten.cos(x)
example_args = torch_mlir.ExampleArgs()
example_args.add_method("sin", torch.ones(2, 3))
example_args.add_method("cos", torch.ones(2, 4))
print(torch_mlir.compile(TwoMethodsModule(), example_args))
```
In the
[long-term](https://github.com/llvm/torch-mlir/blob/main/docs/long_term_roadmap.md#tools-for-advanced-aot-deployments)
we will need to reconcile this with our story for stateful models and the
backend contract being purely functional. For now, this provides some basic
infra that seems harmless. Arguably, we could tighten up the backend contract
even more to only allow a single compiled function which would prohibit this or
require building out a layer above.
Fixes#1557
In some cases, users know that a traced graph is valid for a wider set
of shapes than they originally traced it with. Provide an option for
users to ignore the shapes in the traced graph when they know it is
legal.
Fixes#997
use_tracing=True was behaving unexpectedly because the handling of
single arguments was happening after the torch.jit.trace call.
This also fixes the check to specifically test for a torch.Tensor or
TensorPlaceholder so that both lists and tuples would be correctly
handled.