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Operations for reordering or swapping dimensions within multi-dimensional arrays.
Distinct from Array Operations: Distinct from general array operations: focuses on structural dimension manipulation rather than element-wise computation.
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This project is a machine learning array framework and tensor computation library designed for high-performance numerical computing. It provides a comprehensive suite of tools for constructing and training neural networks, featuring an automatic differentiation engine that facilitates gradient-based optimization and complex mathematical modeling. The library distinguishes itself through a unified memory architecture that allows data to be shared across CPU and GPU devices without explicit copies, significantly reducing data movement overhead. Its execution model relies on a lazy evaluation en
The library swaps two specified axes of an array to reorder its data structure while maintaining the underlying memory layout.