TensorData
The fundamental data structure for tensor operations in the SKaiNET framework.
TensorData represents the core abstraction for all tensor-like data structures used throughout the neural network computation system. It combines element access capabilities with shape information, providing a unified interface for working with multi-dimensional data arrays.
This interface serves as the foundation for:
Neural network weight storage
Activation value containers
Gradient computation data structures
Input/output tensor representations
The generic type parameters allow for flexible data type support while maintaining type safety across different numerical precisions and value representations.
Parameters
the data type constraint extending DType, defining the numerical precision
the actual value type that will be stored and accessed