kaira.models.BaseModel
Inheritance diagram for BaseModel
- class kaira.models.BaseModel(*args: Any, **kwargs: Any)[source]
-
Abstract base class for all models in the Kaira framework.
This class extends PyTorch’s nn.Module and adds framework-specific functionality. All models should inherit from this class to ensure compatibility with the framework’s training, evaluation, and inference pipelines.
The class provides a consistent interface for model implementation while allowing flexibility in architecture design. It enforces proper initialization and forward pass implementation.
Methods
Initialize the model.
Define the forward pass computation.
Examples using
kaira.models.BaseModel
Projections and Cover Tests for Communication Systems
Projections and Cover Tests for Communication Systems
Sequential Model for Modular Neural Network Design
Sequential Model for Modular Neural Network Design- __init__(*args: Any, **kwargs: Any)[source]
Initialize the model.
- Parameters:
*args – Variable positional arguments.
**kwargs – Variable keyword arguments.
- abstract forward(*args: Any, **kwargs: Any) Any[source]
Define the forward pass computation.
This method should be implemented by all subclasses to define how input data is processed through the model to produce output.
- Parameters:
*args – Variable positional arguments for flexible input handling
**kwargs – Variable keyword arguments for optional parameters
- Returns:
Model output, type depends on specific implementation
- Return type:
Any
- Raises:
NotImplementedError – If the subclass does not implement this method
