Implement missing features on ModularPipeline

as i'm looking to take advantage of new `ModularPipeline` ask is to implement some currently missing features

my use case is to convert existing loaded model using standard pipeline into modular pipeline. that functionality was provided via #11915 and is now working.

first minor obstacle is that modular pipeline does not have defined params for execution
in standard pipeline i can inspect `__call__` signature to see which are allowed params
i currently work around this using
`possible = [input_param.name for input_param in model.blocks.inputs]`
please advise if this is acceptable

second one is that modular pipelines don't seem to implement normal callbacks at all (e.g. `callback_on_step_end_tensor_inputs`? at the minimum we need some kind of callback functionality to capture interim latents on each step

third is more cosmetic - modular pipeline does implement `set_progress_bar_config`, but its not doing anything as its not implement on actual block (tested with `StableDiffusionXLModularPipeline`)

cc @yiyixuxu @DN6 @sayakpaul

Beginne mit ModularPipeline und StableDiffusionXLModularPipeline und vergleiche ihr Ausführungsverhalten mit der __call__-Signatur der Standard-Pipeline. Überprüfe blocks.inputs, callback_on_step_end_tensor_inputs und set_progress_bar_config; als erledigt gilt die Aufgabe, wenn Ausführungsparameter, Callbacks für Zwischen-Latents und die Konfiguration der Fortschrittsanzeige erwartungsgemäß funktionieren.

Vom Indexierungsmodell aus dem Issue-Text verfasst.