kaira.models.generic.SequentialModel

Inheritance diagram for SequentialModel

class kaira.models.generic.SequentialModel(steps: Sequence[Callable] | None = None, *args: Any, **kwargs: Any)

Bases: ConfigurableModel

A model that processes steps sequentially.

Each step receives the output of the previous step as its input.

Methods

__init__	Initialize the sequential model.
add_step	Add a processing step to the model.
forward	Execute the model sequentially on the input data.
remove_step	Remove a processing step from the model.

__init__(steps: Sequence[Callable] | None = None, *args: Any, **kwargs: Any)

Initialize the sequential model.

Parameters:

• steps – Optional initial list of processing steps

• *args – Variable positional arguments passed to the base class.

• **kwargs – Variable keyword arguments passed to the base class.

forward(input_data: Any, *args: Any, **kwargs: Any) → Any

Execute the model sequentially on the input data.

Parameters:

• input_data – The initial data to process

• *args – Additional positional arguments passed to each step.

• **kwargs – Additional keyword arguments passed to each step.

Returns:

The final result after passing through all steps

add_step(step: Callable) → ConfigurableModel

Add a processing step to the model.

Parameters:

step – A callable that will be added to the processing pipeline. Must accept and return tensor-like objects.

Returns:

Self for method chaining

remove_step(index: int) → ConfigurableModel

Remove a processing step from the model.

Parameters:

index – The index of the step to remove

Returns:

Self for method chaining

Raises:

IndexError – If the index is out of range