Fix config validation failures caused by NVTX pipeline wrappers

[shadeMe]

Description

When loading pipelines from a config file, the arguments passed to individual pipeline components are validated by pydantic during init. For this, the validation model attempts to parse the function signature of the component's c'tor/entry point in order to check if all mandatory parameters are present in the config file.

When using models_and_pipes_with_nvtx_range as an after_pipeline_creation callback, the methods of all pipeline components get replaced by an NVTX range wrapper before the above-mentioned validation takes place. This can be problematic for components that are implemented as Cython extension types - if the extension type is not compiled with Python bindings for its methods, they will have no signatures at runtime. This resulted in pydantic validating the wrapper's parameters against those in the config, which raised errors.

To avoid this, we no longer apply the wrapper to (Cython) methods that do not have signatures.

This PR also enables bindings for both the Pipe and TrainablePipe Cython classes, thereby adding support for methods that aren't overridden by their subclasses.

Types of change

Bug fix

Checklist

• I confirm that I have the right to submit this contribution under the project's MIT license.
• I ran the tests, and all new and existing tests passed.
• My changes don't require a change to the documentation, or if they do, I've added all required information.